WO2010138952A2 - Gesture shortcuts - Google Patents

Gesture shortcuts Download PDF

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Publication number
WO2010138952A2
WO2010138952A2 PCT/US2010/036774 US2010036774W WO2010138952A2 WO 2010138952 A2 WO2010138952 A2 WO 2010138952A2 US 2010036774 W US2010036774 W US 2010036774W WO 2010138952 A2 WO2010138952 A2 WO 2010138952A2
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WO
WIPO (PCT)
Prior art keywords
gesture
user
shortcut
application
full version
Prior art date
Application number
PCT/US2010/036774
Other languages
French (fr)
Other versions
WO2010138952A3 (en
Inventor
Stephen Latta
Kevin Geisner
John Clavin
Kudo Tsunoda
Kathryn Stone Perez
Relja Markovic
Gregory N. Snook
Alex Kipman
Original Assignee
Microsoft Corporation
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Microsoft Corporation filed Critical Microsoft Corporation
Priority to EP10781372.7A priority Critical patent/EP2435892B1/en
Priority to RU2011148344/08A priority patent/RU2574830C2/en
Priority to CN201080024687.2A priority patent/CN102449576B/en
Priority to KR1020117028423A priority patent/KR101658937B1/en
Priority to BRPI1011212A priority patent/BRPI1011212B1/en
Priority to JP2012513349A priority patent/JP5775514B2/en
Publication of WO2010138952A2 publication Critical patent/WO2010138952A2/en
Publication of WO2010138952A3 publication Critical patent/WO2010138952A3/en

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Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/017Gesture based interaction, e.g. based on a set of recognized hand gestures
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/03Arrangements for converting the position or the displacement of a member into a coded form
    • G06F3/0304Detection arrangements using opto-electronic means
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/03Arrangements for converting the position or the displacement of a member into a coded form
    • G06F3/033Pointing devices displaced or positioned by the user, e.g. mice, trackballs, pens or joysticks; Accessories therefor
    • G06F3/0346Pointing devices displaced or positioned by the user, e.g. mice, trackballs, pens or joysticks; Accessories therefor with detection of the device orientation or free movement in a 3D space, e.g. 3D mice, 6-DOF [six degrees of freedom] pointers using gyroscopes, accelerometers or tilt-sensors
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/03Arrangements for converting the position or the displacement of a member into a coded form
    • G06F3/033Pointing devices displaced or positioned by the user, e.g. mice, trackballs, pens or joysticks; Accessories therefor
    • G06F3/038Control and interface arrangements therefor, e.g. drivers or device-embedded control circuitry
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/048Interaction techniques based on graphical user interfaces [GUI]
    • G06F3/0487Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser
    • G06F3/0488Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/01Input arrangements or combined input and output arrangements for interaction between user and computer
    • G06F3/048Interaction techniques based on graphical user interfaces [GUI]
    • G06F3/0487Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser
    • G06F3/0488Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures
    • G06F3/04883Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures for inputting data by handwriting, e.g. gesture or text
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00Arrangements for program control, e.g. control units
    • G06F9/06Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44Arrangements for executing specific programs

Definitions

  • a computing device receives a series of image data from a camera.
  • This camera may comprise a color camera (such as red-green-blue or RGB), a depth camera, and a three-dimensional (3D) camera.
  • This data may comprise separate depth and color images, a combined image that incorporates depth and color information, or a parsed image where objects are identified, such as people that are skeletal mapped.
  • This data captures motions or poses made by at least one user. These motions or poses may be recognized by the computing device as a type of input - gesture input. For a given gesture (e.g.
  • the computing device recognizes that either the shortcut of the gesture or the full version of the gesture has been performed by the user, it sends an indication of this to an application that uses gestures as input.
  • the computing device recognizes that only a single performance of the gesture has occurred, and indicates to the application as such.
  • the computing device recognizes that only a single performance of the gesture has occurred, and indicates to the application as such.
  • FIGs. IA and IB illustrate an example embodiment of a target recognition, analysis, and tracking system with a user playing a game.
  • FIG. 2 illustrates an example embodiment of a capture device that may be used in a target recognition, analysis, and tracking system.
  • FIG. 3 A illustrates an example embodiment of a computing environment that may be used to interpret one or more gestures in a target recognition, analysis, and tracking system.
  • FIG. 3B illustrates another example embodiment of a computing environment that may be used to interpret one or more gestures in a target recognition, analysis, and tracking system.
  • FIG. 4A illustrates a skeletal mapping of a user that has been generated from the target recognition, analysis, and tracking system of FIG. 2.
  • FIG. 4B illustrates further details of the gesture recognizer architecture shown in FIG. 2.
  • FIGs. 5A and 5B illustrates how gesture filters may be stacked to create more complex gesture filters.
  • FIGs. 6A, 6B, 6C, 6D, and 6E illustrate an example gesture that a user may make to signal for a "fair catch" in football video game.
  • FIGs. 7A, 7B, 7C, 7D and 7E illustrate the example "fair catch" gesture of FIGs. 6A-E as each frame of image data has been parsed to produce a skeletal map of the user.
  • FIG. 8A illustrates a user making a full running gesture.
  • FIG. 8B illustrates a user making a shortcut running gesture, the shortcut gesture comprising a subset of the movement of the full running gesture of FIG. 8 A.
  • FIG. 8C illustrates a user making a second type of shortcut running gesture, the second type of shortcut running gesture comprising movement separate from the full running gesture of FIG. 8 A.
  • FIG. 9 depicts example operational procedures for gesture shortcuts.
  • a user may control an application executing on a computing environment such as a game console, a computer, or the like by performing one or more gestures.
  • the gestures may be received by, for example, a capture device.
  • the capture device may capture a depth image of a scene.
  • the capture device may determine whether one or more targets or objects in the scene corresponds to a human target such as the user.
  • each of the targets may be flood filled and compared to a pattern of a human body model.
  • Each target or object that matches the human body model may then be scanned to generate a skeletal model associated therewith.
  • the skeletal model may then be provided to the computing environment such that the computing environment may track the skeletal model, render an avatar associated with the skeletal model, and may determine which controls to perform in an application executing on the computer environment based on, for example, gestures of the user that have been recognized from the skeletal model.
  • a gesture recognizer engine the architecture of which is described more fully below, is used to determine when a particular gesture has been made by the user.
  • FIGs. IA and IB illustrate an example embodiment of a configuration of a target recognition, analysis, and tracking system 10 with a user 18 playing a boxing game.
  • the target recognition, analysis, and tracking system 10 may be used to recognize, analyze, and/or track a human target such as the user 18.
  • the target recognition, analysis, and tracking system 10 may include a computing environment 12.
  • the computing environment 12 may be a computer, a gaming system or console, or the like.
  • the computing environment 12 may include hardware components and/or software components such that the computing environment 12 may be used to execute applications such as gaming applications, non-gaming applications, or the like.
  • the target recognition, analysis, and tracking system 10 may further include a capture device 20.
  • the capture device 20 may be, for example, a camera that may be used to visually monitor one or more users, such as the user 18, such that gestures performed by the one or more users may be captured, analyzed, and tracked to perform one or more controls or actions within an application, as will be described in more detail below.
  • the target recognition, analysis, and tracking system 10 may be connected to an audiovisual device 16 such as a television, a monitor, a high-definition television (HDTV), or the like that may provide game or application visuals and/or audio to a user such as the user 18.
  • the computing environment 12 may include a video adapter such as a graphics card and/or an audio adapter such as a sound card that may provide audiovisual signals associated with the game application, non-game application, or the like.
  • the audiovisual device 16 may receive the audiovisual signals from the computing environment 12 and may then output the game or application visuals and/or audio associated with the audiovisual signals to the user 18.
  • the audiovisual device 16 may be connected to the computing environment 12 via, for example, an S-Video cable, a coaxial cable, an HDMI cable, a DVI cable, a VGA cable, or the like.
  • the target recognition, analysis, and tracking system 10 may be used to recognize, analyze, and/or track a human target such as the user 18.
  • the user 18 may be tracked using the capture device 20 such that the movements of user 18 may be interpreted as controls that may be used to affect the application being executed by computer environment 12.
  • the user 18 may move his or her body to control the application.
  • the application executing on the computing environment 12 may be a boxing game that the user 18 may be playing.
  • the computing environment 12 may use the audiovisual device 16 to provide a visual representation of a boxing opponent 22 to the user 18.
  • the computing environment 12 may also use the audiovisual device 16 to provide a visual representation of a player avatar 24 that the user 18 may control with his or her movements.
  • the user 18 may throw a punch in physical space to cause the player avatar 24 to throw a punch in game space.
  • the computer environment 12 and the capture device 20 of the target recognition, analysis, and tracking system 10 may be used to recognize and analyze the punch of the user 18 in physical space such that the punch may be interpreted as a game control of the player avatar 24 in game space.
  • Other movements by the user 18 may also be interpreted as other controls or actions, such as controls to bob, weave, shuffle, block, jab, or throw a variety of different power punches. Furthermore, some movements may be interpreted as controls that may correspond to actions other than controlling the player avatar 24. For example, the player may use movements to end, pause, or save a game, select a level, view high scores, communicate with a friend, etc.
  • the human target such as the user 18 may have an object.
  • the user of an electronic game may be holding the object such that the motions of the player and the object may be used to adjust and/or control parameters of the game.
  • the motion of a player holding a racket may be tracked and utilized for controlling an on-screen racket in an electronic sports game.
  • the motion of a player holding an object may be tracked and utilized for controlling an on-screen weapon in an electronic combat game.
  • the target recognition, analysis, and tracking system 10 may further be used to interpret target movements as operating system and/or application controls that are outside the realm of games.
  • target movements as operating system and/or application controls that are outside the realm of games.
  • virtually any controllable aspect of an operating system and/or application may be controlled by movements of the target such as the user 18.
  • FIG. 2 illustrates an example embodiment of the capture device 20 that may be used in the target recognition, analysis, and tracking system 10.
  • the capture device 20 may be configured to capture video with depth information including a depth image that may include depth values via any suitable technique including, for example, time-of-flight, structured light, stereo image, or the like.
  • the capture device 20 may organize the calculated depth information into "Z layers," or layers that may be perpendicular to a Z axis extending from the depth camera along its line of sight.
  • the capture device 20 may include an image camera component 22.
  • the image camera component 22 may be a depth camera that may capture the depth image of a scene.
  • the depth image may include a two-dimensional (2-D) pixel area of the captured scene where each pixel in the 2-D pixel area may represent a length in, for example, centimeters, millimeters, or the like of an object in the captured scene from the camera.
  • 2-D two-dimensional
  • the image camera component 22 may include an IR light component 24, a three-dimensional (3-D) camera 26, and an RGB camera 28 that may be used to capture the depth image of a scene.
  • the IR light component 24 of the capture device 20 may emit an infrared light onto the scene and may then use sensors (not shown) to detect the backscattered light from the surface of one or more targets and objects in the scene using, for example, the 3-D camera 26 and/or the RGB camera 28.
  • pulsed infrared light may be used such that the time between an outgoing light pulse and a corresponding incoming light pulse may be measured and used to determine a physical distance from the capture device 20 to a particular location on the targets or objects in the scene. Additionally, in other example embodiments, the phase of the outgoing light wave may be compared to the phase of the incoming light wave to determine a phase shift. The phase shift may then be used to determine a physical distance from the capture device to a particular location on the targets or objects.
  • time-of-flight analysis may be used to indirectly determine a physical distance from the capture device 20 to a particular location on the targets or objects by analyzing the intensity of the reflected beam of light over time via various techniques including, for example, shuttered light pulse imaging.
  • the capture device 20 may use a structured light to capture depth information.
  • patterned light i.e., light displayed as a known pattern such as grid pattern or a stripe pattern
  • the IR light component 24 may be projected onto the scene via, for example, the IR light component 24.
  • the pattern may become deformed in response.
  • Such a deformation of the pattern may be captured by, for example, the 3-D camera 26 and/or the RGB camera 28 and may then be analyzed to determine a physical distance from the capture device to a particular location on the targets or objects.
  • the capture device 20 may include two or more physically separated cameras that may view a scene from different angles, to obtain visual stereo data that may be resolved to generate depth information
  • the capture device 20 may further include a microphone 30.
  • the microphone 30 may include a transducer or sensor that may receive and convert sound into an electrical signal. According to one embodiment, the microphone 30 may be used to reduce feedback between the capture device 20 and the computing environment 12 in the target recognition, analysis, and tracking system 10. Additionally, the microphone 30 may be used to receive audio signals that may also be provided by the user to control applications such as game applications, non-game applications, or the like that may be executed by the computing environment 12.
  • the capture device 20 may further include a processor 32 that may be in operative communication with the image camera component 22.
  • the processor 32 may include a standardized processor, a specialized processor, a microprocessor, or the like that may execute instructions that may include instructions for receiving the depth image, determining whether a suitable target may be included in the depth image, converting the suitable target into a skeletal representation or model of the target, or any other suitable instruction.
  • the capture device 20 may further include a memory component 34 that may store the instructions that may be executed by the processor 32, images or frames of images captured by the 3-D camera or RGB camera, or any other suitable information, images, or the like.
  • the memory component 34 may include random access memory (RAM), read only memory (ROM), cache, Flash memory, a hard disk, or any other suitable storage component.
  • RAM random access memory
  • ROM read only memory
  • Flash memory Flash memory
  • the memory component 34 may be a separate component in communication with the image capture component 22 and the processor 32.
  • the memory component 34 may be integrated into the processor 32 and/or the image capture component 22.
  • the capture device 20 may be in communication with the computing environment 12 via a communication link 36.
  • the communication link 36 may be a wired connection including, for example, a USB connection, a Firewire connection, an Ethernet cable connection, or the like and/or a wireless connection such as a wireless 802.1 Ib, g, a, or n connection.
  • the computing environment 12 may provide a clock to the capture device 20 that may be used to determine when to capture, for example, a scene via the communication link 36.
  • the capture device 20 may provide the depth information and images captured by, for example, the 3-D camera 26 and/or the RGB camera 28, and a skeletal model that may be generated by the capture device 20 to the computing environment 12 via the communication link 36.
  • the computing environment 12 may then use the skeletal model, depth information, and captured images to, for example, recognize user gestures and in response control an application such as a game or word processor.
  • the computing environment 12 may include a gestures recognizer engine 190.
  • the gestures recognizer engine 190 may include a collection of gesture filters, each comprising information concerning a gesture that may be performed by the skeletal model (as the user moves).
  • the data captured by the cameras 26, 28 and device 20 in the form of the skeletal model and movements associated with it may be compared to the gesture filters in the gesture recognizer engine 190 to identify when a user (as represented by the skeletal model) has performed one or more gestures. Those gestures may be associated with various controls of an application. Thus, the computing environment 12 may use the gesture recognizer engine 190 to interpret movements of the skeletal model and to control an application based on the movements.
  • FIG. 3 A illustrates an example embodiment of a computing environment that may be used to implement computing environment 12 of Figures 1A-2.
  • the computing environment may be a multimedia console 100, such as a gaming console.
  • the multimedia console 100 has a central processing unit (CPU) 101 having a level 1 cache 102, a level 2 cache 104, and a flash ROM (Read Only Memory) 106.
  • the level 1 cache 102 and a level 2 cache 104 temporarily store data and hence reduce the number of memory access cycles, thereby improving processing speed and throughput.
  • the CPU 101 may be provided having more than one core, and thus, additional level 1 and level 2 caches 102 and 104.
  • the flash ROM 106 may store executable code that is loaded during an initial phase of a boot process when the multimedia console 100 is powered ON.
  • a graphics processing unit (GPU) 108 and a video encoder/video codec (coder/decoder) 114 form a video processing pipeline for high speed and high resolution graphics processing. Data is carried from the graphics processing unit 108 to the video encoder/video codec 114 via a bus. The video processing pipeline outputs data to an A/V (audio/video) port 140 for transmission to a television or other display.
  • a memory controller 110 is connected to the GPU 108 to facilitate processor access to various types of memory 112, such as, but not limited to, a RAM (Random Access Memory).
  • the multimedia console 100 includes an I/O controller 120, a system management controller 122, an audio processing unit 123, a network interface controller 124, a first USB host controller 126, a second USB controller 128 and a front panel I/O subassembly 130 that are preferably implemented on a module 118.
  • the USB controllers 126 and 128 serve as hosts for peripheral controllers 142(1)-142(2), a wireless adapter 148, and an external memory device 146 (e.g., flash memory, external CD/DVD ROM drive, removable media, etc.).
  • the network interface 124 and/or wireless adapter 148 provide access to a network (e.g., the Internet, home network, etc.) and may be any of a wide variety of various wired or wireless adapter components including an Ethernet card, a modem, a Bluetooth module, a cable modem, and the like.
  • System memory 143 is provided to store application data that is loaded during the boot process.
  • a media drive 144 is provided and may comprise a DVD/CD drive, hard drive, or other removable media drive, etc.
  • the media drive 144 may be internal or external to the multimedia console 100.
  • Application data may be accessed via the media drive 144 for execution, playback, etc. by the multimedia console 100.
  • the media drive 144 is connected to the I/O controller 120 via a bus, such as a Serial ATA bus or other high speed connection (e.g., IEEE 1394).
  • the system management controller 122 provides a variety of service functions related to assuring availability of the multimedia console 100.
  • the audio processing unit 123 and an audio codec 132 form a corresponding audio processing pipeline with high fidelity and stereo processing. Audio data is carried between the audio processing unit 123 and the audio codec 132 via a communication link.
  • the audio processing pipeline outputs data to the A/V port 140 for reproduction by an external audio player or device having audio capabilities.
  • the front panel I/O subassembly 130 supports the functionality of the power button 150 and the eject button 152, as well as any LEDs (light emitting diodes) or other indicators exposed on the outer surface of the multimedia console 100.
  • a system power supply module 136 provides power to the components of the multimedia console 100.
  • a fan 138 cools the circuitry within the multimedia console 100.
  • the CPU 101, GPU 108, memory controller 110, and various other components within the multimedia console 100 are interconnected via one or more buses, including serial and parallel buses, a memory bus, a peripheral bus, and a processor or local bus using any of a variety of bus architectures.
  • bus architectures can include a Peripheral Component Interconnects (PCI) bus, PCI-Express bus, etc.
  • application data may be loaded from the system memory 143 into memory 112 and/or caches 102, 104 and executed on the CPU 101.
  • the application may present a graphical user interface that provides a consistent user experience when navigating to different media types available on the multimedia console 100.
  • applications and/or other media contained within the media drive 144 may be launched or played from the media drive 144 to provide additional functionalities to the multimedia console 100.
  • the multimedia console 100 may be operated as a standalone system by simply connecting the system to a television or other display. In this standalone mode, the multimedia console 100 allows one or more users to interact with the system, watch movies, or listen to music. However, with the integration of broadband connectivity made available through the network interface 124 or the wireless adapter 148, the multimedia console 100 may further be operated as a participant in a larger network community. [0051] When the multimedia console 100 is powered ON, a set amount of hardware resources are reserved for system use by the multimedia console operating system. These resources may include a reservation of memory (e.g., 16MB), CPU and GPU cycles (e.g., 5%), networking bandwidth (e.g., 8 kbs), etc. Because these resources are reserved at system boot time, the reserved resources do not exist from the application's view.
  • memory e.g. 16MB
  • CPU and GPU cycles e.g., 5%
  • networking bandwidth e.g., 8 kbs
  • the memory reservation preferably is large enough to contain the launch kernel, concurrent system applications and drivers.
  • the CPU reservation is preferably constant such that if the reserved CPU usage is not used by the system applications, an idle thread will consume any unused cycles.
  • lightweight messages generated by the system applications e.g., popups
  • the amount of memory required for an overlay depends on the overlay area size and the overlay preferably scales with screen resolution. Where a full user interface is used by the concurrent system application, it is preferable to use a resolution independent of application resolution. A sealer may be used to set this resolution such that the need to change frequency and cause a TV resynch is eliminated.
  • the multimedia console 100 boots and system resources are reserved, concurrent system applications execute to provide system functionalities.
  • the system functionalities are encapsulated in a set of system applications that execute within the reserved system resources described above.
  • the operating system kernel identifies threads that are system application threads versus gaming application threads.
  • the system applications are preferably scheduled to run on the CPU 101 at predetermined times and intervals in order to provide a consistent system resource view to the application. The scheduling is to minimize cache disruption for the gaming application running on the console.
  • a multimedia console application manager controls the gaming application audio level (e.g., mute, attenuate) when system applications are active.
  • Input devices e.g., controllers 142(1) and 142(2)
  • the input devices are not reserved resources, but are to be switched between system applications and the gaming application such that each will have a focus of the device.
  • the application manager preferably controls the switching of input stream, without knowledge the gaming application's knowledge and a driver maintains state information regarding focus switches.
  • the cameras 26, 28 and capture device 20 may define additionl input devices for the console 100.
  • FIG. 3B illustrates another example embodiment of a computing environment 220 that may be the computing environment 12 shown in FIGs. 1 A-2 used to interpret one or more gestures in a target recognition, analysis, and tracking system.
  • the computing system environment 220 is only one example of a suitable computing environment and is not intended to suggest any limitation as to the scope of use or functionality of the presently disclosed subject matter. Neither should the computing environment 220 be interpreted as having any dependency or requirement relating to any one or combination of components illustrated in the exemplary operating environment 220.
  • the various depicted computing elements may include circuitry configured to instantiate specific aspects of the present disclosure.
  • the term circuitry used in the disclosure can include specialized hardware components configured to perform function(s) by firmware or switches.
  • circuitry can include a general purpose processing unit, memory, etc., configured by software instructions that embody logic operable to perform function(s).
  • an implementer may write source code embodying logic and the source code can be compiled into machine readable code that can be processed by the general purpose processing unit. Since one can appreciate that the state of the art has evolved to a point where there is little difference between hardware, software, or a combination of hardware/software, the selection of hardware versus software to effectuate specific functions is a design choice left to an implementer. More specifically, one of skill in the art can appreciate that a software process can be transformed into an equivalent hardware structure, and a hardware structure can itself be transformed into an equivalent software process. Thus, the selection of a hardware implementation versus a software implementation is one of design choice and left to the implementer.
  • the computing environment 220 comprises a computer 241, which typically includes a variety of computer readable media.
  • Computer readable media can be any available media that can be accessed by computer 241 and includes both volatile and nonvolatile media, removable and non-removable media.
  • the system memory 222 includes computer storage media in the form of volatile and/or nonvolatile memory such as read only memory (ROM) 223 and random access memory (RAM) 260.
  • ROM read only memory
  • RAM random access memory
  • a basic input/output system 224 (BIOS) containing the basic routines that help to transfer information between elements within computer 241, such as during start-up, is typically stored in ROM 223.
  • BIOS basic input/output system 224
  • RAM 260 typically contains data and/or program modules that are immediately accessible to and/or presently being operated on by processing unit 259.
  • FIG. 3B illustrates operating system 225, application programs 226, other program modules 227, and program data 228.
  • the computer 241 may also include other removable/non-removable, volatile/nonvolatile computer storage media.
  • FIG. 3B illustrates a hard disk drive 238 that reads from or writes to non-removable, nonvolatile magnetic media, a magnetic disk drive 239 that reads from or writes to a removable, nonvolatile magnetic disk 254, and an optical disk drive 240 that reads from or writes to a removable, nonvolatile optical disk 253 such as a CD ROM or other optical media.
  • removable/non-removable, volatile/nonvolatile computer storage media that can be used in the exemplary operating environment include, but are not limited to, magnetic tape cassettes, flash memory cards, digital versatile disks, digital video tape, solid state RAM, solid state ROM, and the like.
  • the hard disk drive 238 is typically connected to the system bus 221 through an non-removable memory interface such as interface 234, and magnetic disk drive 239 and optical disk drive 240 are typically connected to the system bus 221 by a removable memory interface, such as interface 235.
  • the drives and their associated computer storage media discussed above and illustrated in FIG. 3B provide storage of computer readable instructions, data structures, program modules and other data for the computer 241.
  • hard disk drive 238 is illustrated as storing operating system 258, application programs 257, other program modules 256, and program data 255. Note that these components can either be the same as or different from operating system 225, application programs 226, other program modules 227, and program data 228.
  • Operating system 258, application programs 257, other program modules 256, and program data 255 are given different numbers here to illustrate that, at a minimum, they are different copies.
  • a user may enter commands and information into the computer 241 through input devices such as a keyboard 251 and pointing device 252, commonly referred to as a mouse, trackball or touch pad.
  • Other input devices may include a microphone, joystick, game pad, satellite dish, scanner, or the like.
  • These and other input devices are often connected to the processing unit 259 through a user input interface 236 that is coupled to the system bus, but may be connected by other interface and bus structures, such as a parallel port, game port or a universal serial bus (USB).
  • the cameras 26, 28 and capture device 20 may define additionl input devices for the console 100.
  • a monitor 242 or other type of display device is also connected to the system bus 221 via an interface, such as a video interface 232.
  • computers may also include other peripheral output devices such as speakers 244 and printer 243, which may be connected through a output peripheral interface 233.
  • the computer 241 may operate in a networked environment using logical connections to one or more remote computers, such as a remote computer 246.
  • the remote computer 246 may be a personal computer, a server, a router, a network PC, a peer device or other common network node, and typically includes many or all of the elements described above relative to the computer 241, although only a memory storage device 247 has been illustrated in FIG. 3B.
  • the logical connections depicted in FIG. 3B include a local area network (LAN) 245 and a wide area network (WAN) 249, but may also include other networks.
  • LAN local area network
  • WAN wide area network
  • Such networking environments are commonplace in offices, enterprise- wide computer networks, intranets and the Internet.
  • the computer 241 When used in a LAN networking environment, the computer 241 is connected to the LAN 245 through a network interface or adapter 237. When used in a WAN networking environment, the computer 241 typically includes a modem 250 or other means for establishing communications over the WAN 249, such as the Internet.
  • the modem 250 which may be internal or external, may be connected to the system bus 221 via the user input interface 236, or other appropriate mechanism.
  • program modules depicted relative to the computer 241, or portions thereof may be stored in the remote memory storage device.
  • FIG. 3B illustrates remote application programs 248 as residing on memory device 247. It will be appreciated that the network connections shown are exemplary and other means of establishing a communications link between the computers may be used.
  • FIG. 4A depicts an example skeletal mapping of a user that may be generated from the capture device 20.
  • a variety of joints and bones are identified: each hand 302, each forearm 304, each elbow 306, each bicep 308, each shoulder 310, each hip 312, each thigh 314, each knee 316, each foreleg 318, each foot 320, the head 322, the torso 324, the top 326 and bottom 328 of the spine, and the waist 330.
  • additional features may be identified, such as the bones and joints of the fingers or toes, or individual features of the face, such as the nose and eyes.
  • a user may create gestures.
  • a gesture comprises a motion or pose by a user that may be captured as image data and parsed for meaning.
  • a gesture may be dynamic, comprising a motion, such as mimicking throwing a ball.
  • a gesture may be a static pose, such as holding one's crossed forearms 304 in front of his torso 324.
  • a gesture may also incorporate props, such as by swinging a mock sword.
  • a gesture may comprise more than one body part, such as clapping the hands 302 together, or a subtler motion, such as pursing one's lips.
  • Gestures may be used for input in a general computing context. For instance, various motions of the hands 302 or other body parts may correspond to common system wide tasks such as navigate up or down in a hierarchical list, open a file, close a file, and save a file. Gestures may also be used in a video-game-specific context, depending on the game. For instance, with a driving game, various motions of the hands 302 and feet 320 may correspond to steering a vehicle in a direction, shifting gears, accelerating, and breaking.
  • a user may generate a gesture that corresponds to walking or running, by walking or running in place himself.
  • the user may alternately lift and drop each leg 312- 320 to mimic walking without moving.
  • the system may parse this gesture by analyzing each hip 312 and each thigh 314.
  • a step may be recognized when one hip-thigh angle (as measured relative to a vertical line, wherein a standing leg has a hip-thigh angle of 0°, and a forward horizontally extended leg has a hip-thigh angle of 90°) exceeds a certain threshold relative to the other thigh.
  • a walk or run may be recognized after some number of consecutive steps by alternating legs. The time between the two most recent steps may be thought of as a period. After some number of periods where that threshold angle is not met, the system may determine that the walk or running gesture has ceased.
  • an application may set values for parameters associated with this gesture. These parameters may include the above threshold angle, the number of steps required to initiate a walk or run gesture, a number of periods where no step occurs to end the gesture, and a threshold period that determines whether the gesture is a walk or a run. A fast period may correspond to a run, as the user will be moving his legs quickly, and a slower period may correspond to a walk.
  • a gesture may be associated with a set of default parameters at first that the application may override with its own parameters. In this scenario, an application is not forced to provide parameters, but may instead use a set of default parameters that allow the gesture to be recognized in the absence of application-defined parameters.
  • a baseline "yes or no” as to whether a gesture is occurring.
  • a confidence level which corresponds to the likelihood that the user's tracked movement corresponds to the gesture. This could be a linear scale that ranges over floating point numbers between 0 and 1, inclusive. Wherein an application receiving this gesture information cannot accept false-positives as input, it may use only those recognized gestures that have a high confidence level, such as at least .95. Where an application must recognize every instance of the gesture, even at the cost of false- positives, it may use gestures that have at least a much lower confidence level, such as those merely greater than .2.
  • the gesture may have an output for the time between the two most recent steps, and where only a first step has been registered, this may be set to a reserved value, such as -1 (since the time between any two steps must be positive).
  • the gesture may also have an output for the highest thigh angle reached during the most recent step.
  • Another exemplary gesture is a "heel lift jump.”
  • a user may create the gesture by raising his heels off the ground, but keeping his toes planted.
  • the user may jump into the air where his feet 320 leave the ground entirely.
  • the system may parse the skeleton for this gesture by analyzing the angle relation of the shoulders 310, hips 312 and knees 316 to see if they are in a position of alignment equal to standing up straight. Then these points and upper 326 and lower 328 spine points may be monitored for any upward acceleration. A sufficient combination of acceleration may trigger a jump gesture.
  • an application may set values for parameters associated with this gesture.
  • the parameters may include the above acceleration threshold, which determines how fast some combination of the user's shoulders 310, hips 312 and knees 316 must move upward to trigger the gesture, as well as a maximum angle of alignment between the shoulders 310, hips 312 and knees 316 at which a jump may still be triggered.
  • the outputs may comprise a confidence level, as well as the user's body angle at the time of the jump.
  • Setting parameters for a gesture based on the particulars of the application that will receive the gesture is important in accurately identifying gestures. Properly identifying gestures and the intent of a user greatly helps in creating a positive user experience. Where a gesture recognizer system is too sensitive, and even a slight forward motion of the hand 302 is interpreted as a throw, the user may become frustrated because gestures are being recognized where he has no intent to make a gesture, and thus, he lacks control over the system. Where a gesture recognizer system is not sensitive enough, the system may not recognize conscious attempts by the user to make a throwing gesture, frustrating him in a similar manner. At either end of the sensitivity spectrum, the user becomes frustrated because he cannot properly provide input to the system.
  • Another parameter to a gesture may be a distance moved.
  • a user's gestures control the actions of an avatar in a virtual environment
  • that avatar may be arm's length from a ball. If the user wishes to interact with the ball and grab it, this may require the user to extend his arm 302-310 to full length while making the grab gesture. In this situation, a similar grab gesture where the user only partially extends his arm 302-310 may not achieve the result of interacting with the ball.
  • a gesture or a portion thereof may have as a parameter a volume of space in which it must occur.
  • This volume of space may typically be expressed in relation to the body where a gesture comprises body movement.
  • a football throwing gesture for a right-handed user may be recognized only in the volume of space no lower than the right shoulder 310a, and on the same side of the head 322 as the throwing arm 302a-310a. It may not be necessary to define all bounds of a volume, such as with this throwing gesture, where an outer bound away from the body is left undefined, and the volume extends out indefinitely, or to the edge of scene that is being monitored.
  • FIG. 4B provides further details of one exemplary embodiment of the gesture recognizer engine 190 of FIG. 2.
  • the gesture recognizer engine 190 may comprise at least one filter 418 to determine a gesture or gestures.
  • a filter 418 comprises information defining a gesture 426 (hereinafter referred to as a "gesture") along with parameters 428, or metadata, for that gesture.
  • a gesture which comprises motion of one of the hands from behind the rear of the body to past the front of the body
  • a gesture 426 comprising information representing the movement of one of the hands of the user from behind the rear of the body to past the front of the body, as that movement would be captured by the depth camera.
  • Parameters 428 may then be set for that gesture 426.
  • a parameter 428 may be a threshold velocity that the hand has to reach, a distance the hand must travel (either absolute, or relative to the size of the user as a whole), and a confidence rating by the recognizer engine that the gesture occurred.
  • These parameters 428 for the gesture 426 may vary between applications, between contexts of a single application, or within one context of one application over time.
  • Filters may be modular or interchangeable.
  • a filter has a number of inputs, each of those inputs having a type, and a number of outputs, each of those outputs having a type.
  • a first filter may be replaced with a second filter that has the same number and types of inputs and outputs as the first filter without altering any other aspect of the recognizer engine architecture. For instance, there may be a first filter for driving that takes as input skeletal data and outputs a confidence that the gesture associated with the filter is occurring and an angle of steering.
  • a filter need not have a parameter.
  • a "user height” filter that returns the user's height may not allow for any parameters that may be tuned.
  • An alternate "user height” filter may have tunable parameters - such as to whether to account for a user's footwear, hairstyle, headwear and posture in determining the user's height.
  • Inputs to a filter may comprise things such as joint data about a user's joint position, like angles formed by the bones that meet at the joint, RGB color data from the scene, and the rate of change of an aspect of the user.
  • Outputs from a filter may comprise things such as the confidence that a given gesture is being made, the speed at which a gesture motion is made, and a time at which a gesture motion is made.
  • a context may be a cultural context, and it may be an environmental context.
  • a cultural context refers to the culture of a user using a system. Different cultures may use similar gestures to impart markedly different meanings. For instance, an American user who wishes to tell another user to "look” or "use his eyes” may put his index finger on his head close to the distal side of his eye. However, to an Italian user, this gesture may be interpreted as a reference to the mafia.
  • the gesture recognizer engine 190 may have a base recognizer engine 416 that provides functionality to a gesture filter 418.
  • the functionality that the recognizer engine 416 implements includes an input-over-time archive that tracks recognized gestures and other input, a Hidden Markov Model implementation (where the modeled system is assumed to be a Markov process - one where a present state encapsulates any past state information necessary to determine a future state, so no other past state information must be maintained for this purpose - with unknown parameters, and hidden parameters are determined from the observable data), as well as other functionality required to solve particular instances of gesture recognition.
  • Filters 418 are loaded and implemented on top of the base recognizer engine 416 and can utilize services provided by the engine 416 to all filters 418.
  • the base recognizer engine 416 processes received data to determine whether it meets the requirements of any filter 418. Since these provided services, such as parsing the input, are provided once by the base recognizer engine 416 rather than by each filter 418, such a service need only be processed once in a period of time as opposed to once per filter 418 for that period, so the processing required to determine gestures is reduced.
  • An application may use the filters 418 provided by the recognizer engine 190, or it may provide its own filter 418, which plugs in to the base recognizer engine 416.
  • all filters 418 have a common interface to enable this plug-in characteristic.
  • all filters 418 may utilize parameters 428, so a single gesture tool as described below may be used to debug and tune the entire filter system 418.
  • these parameters 428 may be tuned for an application or a context of an application by a gesture tool 420.
  • the gesture tool 420 comprises a plurality of sliders 422, each slider 422 corresponding to a parameter 428, as well as a pictoral representation of a body 424.
  • the body 424 may demonstrate both actions that would be recognized as the gesture with those parameters 428 and actions that would not be recognized as the gesture with those parameters 428, identified as such. This visualization of the parameters 428 of gestures provides an effective means to both debug and fine tune a gesture.
  • FIG. 5 depicts more complex gestures or filters 418 created from stacked gestures or filters 418.
  • Gestures can stack on each other. That is, more than one gesture may be expressed by a user at a single time. For instance, rather than disallowing any input but a throw when a throwing gesture is made, or requiring that a user remain motionless save for the components of the gesture (e.g. stand still while making a throwing gesture that involves only one arm). Where gestures stack, a user may make a jumping gesture and a throwing gesture simultaneously, and both of these gestures will be recognized by the gesture engine.
  • FIG. 5 A depicts a simple gesture filter 418 according to the stacking paradigm.
  • the IFilter filter 502 is a basic filter 418 that may be used in every gesture filter.
  • IFilter 502 takes user position data 504 and outputs a confidence level 506 that a gesture has occurred. It also feeds that position data 504 into a Steering Wheel filter 508 that takes it as an input and outputs an angle to which the user is steering (e.g. 40 degrees to the right of the user's current bearing) 510.
  • FIG. 5B depicts a more complex gesture that stacks filters 418 onto the gesture filter of FIG. 5 A.
  • ITracking filter 512 receives position data 504 from IFilter 502 and outputs the amount of progress the user has made through a gesture 514.
  • ITracking 512 also feeds position data 504 to GreaseLightning 516 and EBrake 518, which are filters 418 regarding other gestures that may be made in operating a vehicle, such as using the emergency brake.
  • FIG. 6 depicts an example gesture that a user 602 may make to signal for a "fair catch" in a football video game. These figures depict the user at points in time, with FIG.
  • FIG. 6A being the first point in time
  • FIG. 6E being the last point in time.
  • Each of these figures may correspond to a snapshot or frame of image data as captured by a depth camera 402, though not necessarily consecutive frames of image data, as the depth camera 402 may be able to capture frames more rapidly than the user may cover the distance. For instance, this gesture may occur over a period of 3 seconds, and where a depth camera captures data at 40 frames per second, it would capture 60 frames of image data while the user 602 made this fair catch gesture.
  • the user 602 begins with his arms 604 down at his sides. He then raises them up and above his shoulders as depicted in FIG. 6B and then further up, to the approximate level of his head, as depicted in FIG.
  • FIG. 7 depicts the example "fair catch" gesture of FIG. 5 as each frame of image data has been parsed to produce a skeletal map of the user.
  • the system having produced a skeletal map from the depth image of the user, may now determine how that user's body moves over time, and from that, parse the gesture.
  • FIG. 7 A the user's shoulders 310, are above his elbows 306, which in turn are above his hands 302.
  • the shoulders 310, elbows 306 and hands 302 are then at a uniform level in FIG. 7B.
  • the system detects in FIG. 7C that the hands 302 are above the elbows, which are above the shoulders 310.
  • FIG. 7D the user has returned to the position of FIG. 7B, where the shoulders 310, elbows 306 and hands 302 are at a uniform level.
  • FIG. 7E the user returns to the position of FIG. 7C, where the hands 302 are above the elbows, which are above the shoulders 310.
  • the capture device 20 captures a series of still images, such that in any one image the user appears to be stationary, the user is moving in the course of performing this gesture (as opposed to a stationary gesture, as discussed supra).
  • the system is able to take this series of poses in each still image, and from that determine the confidence level of the moving gesture that the user is making.
  • the application using the filter 418 for the fair catch gesture 426 may tune the associated parameters 428 to best serve the specifics of the application. For instance, the positions in FIGs. 7C and 7E may be recognized any time the user has his hands 302 above his shoulders 310, without regard to elbow 306 position. A set of parameters that are more strict may require that the hands 302 be above the head 310 and that the elbows 306 be both above the shoulders 310 and between the head 322 and the hands 302.
  • FIGs. 8A-C illustrate a user making the same system-recognized running gesture through different captured movements and poses.
  • FIG. 8A illustrates a user making a full running gesture.
  • User 18 is captured by capture device 20.
  • User 18 creates the full running gesture by running in place - alternately lifting each of his knees to approximately waist height then dropping the leg down to the ground.
  • This version of the full running gesture is a periodic gesture in that user 18 repeats the motions that comprise the gesture for the duration that he wants the gesture to last.
  • FIG. 8B illustrates a user making a shortcut running gesture, the shortcut gesture comprising a subset of the movement of the full running gesture of FIG. 8 A.
  • the shortcut gesture comprises a subset of the movement of the full gesture of FIG. 8 A - where the user in FIG. 8 A repeatedly lifts and drops his knees, here the user lifts his knee once and holds that pose.
  • the full gesture of FIG. 8 A involves periodic movement
  • the shortcut gesture involves a series of non-repeated movements, or a series of movements where the series as a whole is not repeated.
  • user 18 drops his knee down to a standing pose when he wishes to end the gesture. In an embodiment, this act of dropping the knee may also comprise a subset of the full gesture. In an embodiment, computing environment 12 determines that this movement is to end the gesture shortcut rather than produce the full gesture when user 18 holds his knee at approximately hip level for more than a specified amount of time, serial
  • FIG. 8C illustrates a user making a second type of shortcut running gesture, the second type of shortcut running gesture comprising movement separate from the full running gesture of FIG. 8 A.
  • user 18 takes one step forward and holds this pose with one foot in front of the other, both feet on the ground, for the duration that he wishes to produce the running gesture. This position is not found in the full running gesture of FIG. 8 A.
  • User 18 may end the gesture by stepping back to a standing pose. This gesture is similar to that of FIG. 8B in that both involve movement to initiate the gesture, then holding a pose to maintain the gesture, and movement to end the gesture.
  • FIG. 9 illustrates example operating procedures for gesture shortcuts.
  • one gesture input to a computing device may be recognized by the computing device as a result of a plurality of ways performed by a user.
  • this plurality of ways that a gesture may be performed by a user comprises a full version of the gesture and a shortcut of the gesture.
  • Gesture shortcuts may be used in a variety of application contexts. For instance, running gesture shortcuts may be used in applications that involve running, like a track and field game. Text input shortcuts may be used in a text input context of an application. For example, the user may use sign language gestures to input text. A full version of a word gesture may comprise signing each letter of the word, such as H-E-A-R- T. A shortcut for the "heart" word gesture may comprise a single gesture for heart, such from the user forming hands into a representation of a heart. Such a sign language may comprise American Sign Language (ASL).
  • ASL American Sign Language
  • a gesture shortcut may involve different body parts than the corresponding full version of a gesture. For instance, where a user lacks use of his legs, and the full version of a running gesture involves running in place, the shortcut of the gesture may involve mimicking a running motion with the user's hands.
  • Optional operation 902 depicts receiving user input corresponding to defining the shortcut of the gesture. For instance, the user, either by being prompted by the computing device or through indicating to the computing device his desire to do so, may make a motion or pose that is captured by a capture device and stored as a way to perform the gesture.
  • gesture shortcut may then refine the gesture shortcut on the system. For instance, where gestures are recognized using filters and corresponding parameters, he may tune the parameters of his gesture shortcut in ways as discussed above.
  • the shortcut of the gesture corresponds to a full version of a second gesture.
  • a gesture shortcut may correspond to a plurality of full gestures, and where the user defines a shortcut, he may indicate that the shortcut is to correspond to a plurality of full gestures. For instance, in a context of printing a text file, the user may define one gesture shortcut that corresponds to the full gesture of selecting the paper orientation to be portrait, the full gesture of selecting four copies to print, and the full gesture of selecting a specific printer to print from.
  • gestures are recognized through gesture filters and parameters
  • the shortcut of a gesture and the full version of a gesture may use the same gesture filter, but a different value for one or more parameters.
  • the full version of a "ball throw" gesture may require that the user move his hand from behind his torso to approximately arm's length in front of his torso.
  • the shortcut may reduce the required distance that the hand must travel such that the hand must neither be extended as far back nor as far forward. This may be effectuated for changing a parameter value or values, such as one for "minimum hand distance.”
  • Operation 904 depicts receiving data captured by a capture device, the data corresponding to a user-performed gesture.
  • the capture device may capture a scene that contains all of the user, such as from the floor to the ceiling and to the wall on each side of a room at the distance in which the user is located.
  • the capture device may also capture a scene that contains only part of the user, such as the user from the abdomen up as he or she sits at a desk.
  • the capture device may also capture an object controlled by the user, such as a prop camera that the user holds in his or her hand.
  • Optional operation 906 depicts determining from the application to process the data with the shortcut of the gesture.
  • An application may limit the shortcuts that are used as input in some way. For instance, in a track and field game, running may be considered integral to the process and the application may disallow or disable a shortcut for a running gesture, requiring a user to make a full running gesture when he wishes to run. In contrast, in a first-person shooter game, running may be considered ancillary to use of the game, so use of a shortcut for a running gesture may be allowed. In this first- person shooter game, mechanics for discharging a firearm may be considered integral to the process, and the application may disallow or disable shortcuts for an aiming or firing gesture.
  • a user may perform both shortcuts for gestures and full versions of gestures that are recognized, in the same manner that a user may simultaneously perform multiple gestures, as discussed previously.
  • the user may simultaneously make the shortcut for the running gesture, and the full version of the aiming gesture.
  • this determination to process the data with the shortcut of the gesture originates from the user. For instance, which shortcuts to process may correspond to a difficulty level of the application that the user selects. Where the user chooses the lowest difficulty level, all shortcuts may be processed. As the user increases the difficulty level, the number of allowed shortcuts to process may decrease, until the highest difficulty level where no shortcuts are processed.
  • This determination may change over time to be adaptive to user ability. For instance, a default setting of allowed shortcuts may be implemented at the start of an application session, and the allowed shortcuts may be increased or decreased during the session as the user shows his ability to perform gestures well, or lack of such ability. Further, as the user tires during the course of a session, or increases in competence, the allowed shortcuts may be increased or decreased to correspond to his current state of ability.
  • Operation 908 depicts processing the data to determine an output corresponding to whether the user performed a shortcut of a gesture, the shortcut of the gesture corresponding to a full version of the gesture. In an embodiment, this output may comprise a confidence level that the gesture occurred. In an embodiment, this may comprise an indication as to whether a full version of a gesture or a gesture shortcut was observed.
  • Operation 910 depicts sending the output corresponding to the shortcut of the gesture to the application. Where the present operations are performed by the application, the output may be sent to a component of the application that takes processed user input and maps it to in-application actions.
  • Optional operation 912 depicts processing the data to determine an output corresponding to whether the user performed the full version of the gesture, and sending the output corresponding to the full version of the gesture to the application.
  • the shortcut of the gesture comprises user movement that comprises a subset of user movement that comprises the full version of the gesture.
  • the output corresponding to the shortcut of the gesture corresponds to a high likelihood that the user triggered the gesture
  • the output corresponding to the full version of the gesture corresponds to a high likelihood that the user triggered the gesture
  • the application recognizes only one user gesture.
  • the shortcut of the gesture comprises a subset of the full version of the gesture
  • when the user performs the full version of the gesture he will also perform the shortcut of the gesture.
  • two gestures may be recognized.
  • the shortcut of the gesture and the full version of the gesture are recognized within a prescribed period of time (one that may be gesture and/or user specific), only one is used as input and the other is disregarded.
  • the output corresponding to the shortcut of the gesture corresponds to a high likelihood that the user triggered the gesture
  • the output corresponding to the full version of the gesture corresponds to a high likelihood that the user triggered the gesture
  • the application uses an output corresponding to the full version of the gesture to add detail to the gesture.
  • a full version of a "jump" gesture may comprise the user jumping.
  • a shortcut of that "jump” gesture may comprise the initial motions of the full version of the gesture - a crouch and rise - and output a confidence level that the gesture was performed.
  • the application may process this by displaying the user's avatar as jumping.
  • the application may use a height that the user physically jumps to display the avatar as jumping a corresponding height to add detail to the currently-processed jump shorcut. If the user performed only the shortcut of the jump gesture, the application may have the avatar jump a default height. [0118] In an embodiment, where the user performs a shortcut of a gesture, it may correspond to lesser in-application accomplishment than if where the user performs the full version of the gesture.
  • the user may receive fewer points than had he performed the given trick using the full version of the skateboarding trick gesture.

Abstract

Systems, methods and computer readable media are disclosed for gesture shortcuts. A user's movement or body position is captured by a capture device of a system, and is used as input to control the system. For a system-recognized gesture, there may be a full version of the gesture and a shortcut of the gesture. Where the system recognizes that either the full version of the gesture or the shortcut of the gesture has been performed, it sends an indication that the system-recognized gesture was observed to a corresponding application. Where the shortcut comprises a subset of the full version of the gesture, and both the shortcut and the full version of the gesture are recognized as the user performs the full version of the gesture, the system recognizes that only a single performance of the gesture has occurred, and indicates to the application as such.

Description

GESTURE SHORTCUTS
BACKGROUND
[0001] Many computing applications such as computer games, multimedia applications, office applications or the like use controls to allow users to manipulate game characters or other aspects of an application. Typically such controls are input using, for example, controllers, remotes, keyboards, mice, or the like. Unfortunately, such controls can be difficult to learn, thus creating a barrier between a user and such games and applications. Furthermore, such controls may be different than actual game actions or other application actions for which the controls are used. For example, a game control that causes a game character to swing a baseball bat may not correspond to an actual motion of swinging the baseball bat. SUMMARY OF THE INVENTION
[0002] Disclosed herein are systems and methods for gesture shortcuts. [0003] In an embodiment, a computing device receives a series of image data from a camera. This camera may comprise a color camera (such as red-green-blue or RGB), a depth camera, and a three-dimensional (3D) camera. This data may comprise separate depth and color images, a combined image that incorporates depth and color information, or a parsed image where objects are identified, such as people that are skeletal mapped. This data captures motions or poses made by at least one user. These motions or poses may be recognized by the computing device as a type of input - gesture input. For a given gesture (e.g. navigate up), there may be a full version of the gesture that the user may make and a shortcut of the gesture that the user may make, the shortcut of the gesture generally requiring less time, movement, or difficulty of movement for the user. [0004] Where the computing device recognizes that either the shortcut of the gesture or the full version of the gesture has been performed by the user, it sends an indication of this to an application that uses gestures as input.
[0005] In an embodiment where the shortcut comprises a subset of the full version of the gesture, and both the shortcut and the full version of the gesture are recognized as the user performs the full version of the gesture, the computing device recognizes that only a single performance of the gesture has occurred, and indicates to the application as such. [0006] The foregoing is a summary and thus contains, by necessity, simplifications, generalizations and omissions of detail. It may be appreciated that the summary is illustrative only and is not intended to be in any way limiting. BRIEF DESCRIPTION OF THE DRAWINGS [0007] The systems, methods, and computer readable media for gesture shortcuts in accordance with this specification are further described with reference to the accompanying drawings in which:
[0008] FIGs. IA and IB illustrate an example embodiment of a target recognition, analysis, and tracking system with a user playing a game. [0009] FIG. 2 illustrates an example embodiment of a capture device that may be used in a target recognition, analysis, and tracking system.
[0010] FIG. 3 A illustrates an example embodiment of a computing environment that may be used to interpret one or more gestures in a target recognition, analysis, and tracking system. [0011] FIG. 3B illustrates another example embodiment of a computing environment that may be used to interpret one or more gestures in a target recognition, analysis, and tracking system.
[0012] FIG. 4A illustrates a skeletal mapping of a user that has been generated from the target recognition, analysis, and tracking system of FIG. 2. [0013] FIG. 4B illustrates further details of the gesture recognizer architecture shown in FIG. 2.
[0014] FIGs. 5A and 5B illustrates how gesture filters may be stacked to create more complex gesture filters.
[0015] FIGs. 6A, 6B, 6C, 6D, and 6E illustrate an example gesture that a user may make to signal for a "fair catch" in football video game.
[0016] FIGs. 7A, 7B, 7C, 7D and 7E illustrate the example "fair catch" gesture of FIGs. 6A-E as each frame of image data has been parsed to produce a skeletal map of the user.
[0017] FIG. 8A illustrates a user making a full running gesture. [0018] FIG. 8B illustrates a user making a shortcut running gesture, the shortcut gesture comprising a subset of the movement of the full running gesture of FIG. 8 A.
[0019] FIG. 8C illustrates a user making a second type of shortcut running gesture, the second type of shortcut running gesture comprising movement separate from the full running gesture of FIG. 8 A. [0020] FIG. 9 depicts example operational procedures for gesture shortcuts.
DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS
[0021] As will be described herein, a user may control an application executing on a computing environment such as a game console, a computer, or the like by performing one or more gestures. According to one embodiment, the gestures may be received by, for example, a capture device. For example, the capture device may capture a depth image of a scene. In one embodiment, the capture device may determine whether one or more targets or objects in the scene corresponds to a human target such as the user. To determine whether a target or object in the scene corresponds a human target, each of the targets may be flood filled and compared to a pattern of a human body model. Each target or object that matches the human body model may then be scanned to generate a skeletal model associated therewith. The skeletal model may then be provided to the computing environment such that the computing environment may track the skeletal model, render an avatar associated with the skeletal model, and may determine which controls to perform in an application executing on the computer environment based on, for example, gestures of the user that have been recognized from the skeletal model. A gesture recognizer engine, the architecture of which is described more fully below, is used to determine when a particular gesture has been made by the user. [0022] FIGs. IA and IB illustrate an example embodiment of a configuration of a target recognition, analysis, and tracking system 10 with a user 18 playing a boxing game. In an example embodiment, the target recognition, analysis, and tracking system 10 may be used to recognize, analyze, and/or track a human target such as the user 18. [0023] As shown in FIG. IA, the target recognition, analysis, and tracking system 10 may include a computing environment 12. The computing environment 12 may be a computer, a gaming system or console, or the like. According to an example embodiment, the computing environment 12 may include hardware components and/or software components such that the computing environment 12 may be used to execute applications such as gaming applications, non-gaming applications, or the like. [0024] As shown in FIG. IA, the target recognition, analysis, and tracking system 10 may further include a capture device 20. The capture device 20 may be, for example, a camera that may be used to visually monitor one or more users, such as the user 18, such that gestures performed by the one or more users may be captured, analyzed, and tracked to perform one or more controls or actions within an application, as will be described in more detail below.
[0025] According to one embodiment, the target recognition, analysis, and tracking system 10 may be connected to an audiovisual device 16 such as a television, a monitor, a high-definition television (HDTV), or the like that may provide game or application visuals and/or audio to a user such as the user 18. For example, the computing environment 12 may include a video adapter such as a graphics card and/or an audio adapter such as a sound card that may provide audiovisual signals associated with the game application, non-game application, or the like. The audiovisual device 16 may receive the audiovisual signals from the computing environment 12 and may then output the game or application visuals and/or audio associated with the audiovisual signals to the user 18. According to one embodiment, the audiovisual device 16 may be connected to the computing environment 12 via, for example, an S-Video cable, a coaxial cable, an HDMI cable, a DVI cable, a VGA cable, or the like. [0026] As shown in FIGs. IA and IB, the target recognition, analysis, and tracking system 10 may be used to recognize, analyze, and/or track a human target such as the user 18. For example, the user 18 may be tracked using the capture device 20 such that the movements of user 18 may be interpreted as controls that may be used to affect the application being executed by computer environment 12. Thus, according to one embodiment, the user 18 may move his or her body to control the application.
[0027] As shown in FIGs. IA and IB, in an example embodiment, the application executing on the computing environment 12 may be a boxing game that the user 18 may be playing. For example, the computing environment 12 may use the audiovisual device 16 to provide a visual representation of a boxing opponent 22 to the user 18. The computing environment 12 may also use the audiovisual device 16 to provide a visual representation of a player avatar 24 that the user 18 may control with his or her movements. For example, as shown in FIG. IB, the user 18 may throw a punch in physical space to cause the player avatar 24 to throw a punch in game space. Thus, according to an example embodiment, the computer environment 12 and the capture device 20 of the target recognition, analysis, and tracking system 10 may be used to recognize and analyze the punch of the user 18 in physical space such that the punch may be interpreted as a game control of the player avatar 24 in game space.
[0028] Other movements by the user 18 may also be interpreted as other controls or actions, such as controls to bob, weave, shuffle, block, jab, or throw a variety of different power punches. Furthermore, some movements may be interpreted as controls that may correspond to actions other than controlling the player avatar 24. For example, the player may use movements to end, pause, or save a game, select a level, view high scores, communicate with a friend, etc. [0029] In example embodiments, the human target such as the user 18 may have an object. In such embodiments, the user of an electronic game may be holding the object such that the motions of the player and the object may be used to adjust and/or control parameters of the game. For example, the motion of a player holding a racket may be tracked and utilized for controlling an on-screen racket in an electronic sports game. In another example embodiment, the motion of a player holding an object may be tracked and utilized for controlling an on-screen weapon in an electronic combat game.
[0030] According to other example embodiments, the target recognition, analysis, and tracking system 10 may further be used to interpret target movements as operating system and/or application controls that are outside the realm of games. For example, virtually any controllable aspect of an operating system and/or application may be controlled by movements of the target such as the user 18.
[0031] FIG. 2 illustrates an example embodiment of the capture device 20 that may be used in the target recognition, analysis, and tracking system 10. According to an example embodiment, the capture device 20 may be configured to capture video with depth information including a depth image that may include depth values via any suitable technique including, for example, time-of-flight, structured light, stereo image, or the like. According to one embodiment, the capture device 20 may organize the calculated depth information into "Z layers," or layers that may be perpendicular to a Z axis extending from the depth camera along its line of sight. [0032] As shown in FIG. 2, the capture device 20 may include an image camera component 22. According to an example embodiment, the image camera component 22 may be a depth camera that may capture the depth image of a scene. The depth image may include a two-dimensional (2-D) pixel area of the captured scene where each pixel in the 2-D pixel area may represent a length in, for example, centimeters, millimeters, or the like of an object in the captured scene from the camera.
[0033] As shown in FIG. 2, according to an example embodiment, the image camera component 22 may include an IR light component 24, a three-dimensional (3-D) camera 26, and an RGB camera 28 that may be used to capture the depth image of a scene. For example, in time-of-flight analysis, the IR light component 24 of the capture device 20 may emit an infrared light onto the scene and may then use sensors (not shown) to detect the backscattered light from the surface of one or more targets and objects in the scene using, for example, the 3-D camera 26 and/or the RGB camera 28. In some embodiments, pulsed infrared light may be used such that the time between an outgoing light pulse and a corresponding incoming light pulse may be measured and used to determine a physical distance from the capture device 20 to a particular location on the targets or objects in the scene. Additionally, in other example embodiments, the phase of the outgoing light wave may be compared to the phase of the incoming light wave to determine a phase shift. The phase shift may then be used to determine a physical distance from the capture device to a particular location on the targets or objects.
[0034] According to another example embodiment, time-of-flight analysis may be used to indirectly determine a physical distance from the capture device 20 to a particular location on the targets or objects by analyzing the intensity of the reflected beam of light over time via various techniques including, for example, shuttered light pulse imaging.
[0035] In another example embodiment, the capture device 20 may use a structured light to capture depth information. In such an analysis, patterned light (i.e., light displayed as a known pattern such as grid pattern or a stripe pattern) may be projected onto the scene via, for example, the IR light component 24. Upon striking the surface of one or more targets or objects in the scene, the pattern may become deformed in response. Such a deformation of the pattern may be captured by, for example, the 3-D camera 26 and/or the RGB camera 28 and may then be analyzed to determine a physical distance from the capture device to a particular location on the targets or objects.
[0036] According to another embodiment, the capture device 20 may include two or more physically separated cameras that may view a scene from different angles, to obtain visual stereo data that may be resolved to generate depth information
[0037] The capture device 20 may further include a microphone 30. The microphone 30 may include a transducer or sensor that may receive and convert sound into an electrical signal. According to one embodiment, the microphone 30 may be used to reduce feedback between the capture device 20 and the computing environment 12 in the target recognition, analysis, and tracking system 10. Additionally, the microphone 30 may be used to receive audio signals that may also be provided by the user to control applications such as game applications, non-game applications, or the like that may be executed by the computing environment 12. [0038] In an example embodiment, the capture device 20 may further include a processor 32 that may be in operative communication with the image camera component 22. The processor 32 may include a standardized processor, a specialized processor, a microprocessor, or the like that may execute instructions that may include instructions for receiving the depth image, determining whether a suitable target may be included in the depth image, converting the suitable target into a skeletal representation or model of the target, or any other suitable instruction.
[0039] The capture device 20 may further include a memory component 34 that may store the instructions that may be executed by the processor 32, images or frames of images captured by the 3-D camera or RGB camera, or any other suitable information, images, or the like. According to an example embodiment, the memory component 34 may include random access memory (RAM), read only memory (ROM), cache, Flash memory, a hard disk, or any other suitable storage component. As shown in FIG. 2, in one embodiment, the memory component 34 may be a separate component in communication with the image capture component 22 and the processor 32. According to another embodiment, the memory component 34 may be integrated into the processor 32 and/or the image capture component 22.
[0040] As shown in FIG. 2, the capture device 20 may be in communication with the computing environment 12 via a communication link 36. The communication link 36 may be a wired connection including, for example, a USB connection, a Firewire connection, an Ethernet cable connection, or the like and/or a wireless connection such as a wireless 802.1 Ib, g, a, or n connection. According to one embodiment, the computing environment 12 may provide a clock to the capture device 20 that may be used to determine when to capture, for example, a scene via the communication link 36. [0041] Additionally, the capture device 20 may provide the depth information and images captured by, for example, the 3-D camera 26 and/or the RGB camera 28, and a skeletal model that may be generated by the capture device 20 to the computing environment 12 via the communication link 36. The computing environment 12 may then use the skeletal model, depth information, and captured images to, for example, recognize user gestures and in response control an application such as a game or word processor. For example, as shown, in FIG. 2, the computing environment 12 may include a gestures recognizer engine 190. The gestures recognizer engine 190 may include a collection of gesture filters, each comprising information concerning a gesture that may be performed by the skeletal model (as the user moves). The data captured by the cameras 26, 28 and device 20 in the form of the skeletal model and movements associated with it may be compared to the gesture filters in the gesture recognizer engine 190 to identify when a user (as represented by the skeletal model) has performed one or more gestures. Those gestures may be associated with various controls of an application. Thus, the computing environment 12 may use the gesture recognizer engine 190 to interpret movements of the skeletal model and to control an application based on the movements.
[0042] FIG. 3 A illustrates an example embodiment of a computing environment that may be used to implement computing environment 12 of Figures 1A-2. The computing environment may be a multimedia console 100, such as a gaming console. As shown in FIG. 3 A, the multimedia console 100 has a central processing unit (CPU) 101 having a level 1 cache 102, a level 2 cache 104, and a flash ROM (Read Only Memory) 106. The level 1 cache 102 and a level 2 cache 104 temporarily store data and hence reduce the number of memory access cycles, thereby improving processing speed and throughput. The CPU 101 may be provided having more than one core, and thus, additional level 1 and level 2 caches 102 and 104. The flash ROM 106 may store executable code that is loaded during an initial phase of a boot process when the multimedia console 100 is powered ON.
[0043] A graphics processing unit (GPU) 108 and a video encoder/video codec (coder/decoder) 114 form a video processing pipeline for high speed and high resolution graphics processing. Data is carried from the graphics processing unit 108 to the video encoder/video codec 114 via a bus. The video processing pipeline outputs data to an A/V (audio/video) port 140 for transmission to a television or other display. A memory controller 110 is connected to the GPU 108 to facilitate processor access to various types of memory 112, such as, but not limited to, a RAM (Random Access Memory). [0044] The multimedia console 100 includes an I/O controller 120, a system management controller 122, an audio processing unit 123, a network interface controller 124, a first USB host controller 126, a second USB controller 128 and a front panel I/O subassembly 130 that are preferably implemented on a module 118. The USB controllers 126 and 128 serve as hosts for peripheral controllers 142(1)-142(2), a wireless adapter 148, and an external memory device 146 (e.g., flash memory, external CD/DVD ROM drive, removable media, etc.). The network interface 124 and/or wireless adapter 148 provide access to a network (e.g., the Internet, home network, etc.) and may be any of a wide variety of various wired or wireless adapter components including an Ethernet card, a modem, a Bluetooth module, a cable modem, and the like. [0045] System memory 143 is provided to store application data that is loaded during the boot process. A media drive 144 is provided and may comprise a DVD/CD drive, hard drive, or other removable media drive, etc. The media drive 144 may be internal or external to the multimedia console 100. Application data may be accessed via the media drive 144 for execution, playback, etc. by the multimedia console 100. The media drive 144 is connected to the I/O controller 120 via a bus, such as a Serial ATA bus or other high speed connection (e.g., IEEE 1394).
[0046] The system management controller 122 provides a variety of service functions related to assuring availability of the multimedia console 100. The audio processing unit 123 and an audio codec 132 form a corresponding audio processing pipeline with high fidelity and stereo processing. Audio data is carried between the audio processing unit 123 and the audio codec 132 via a communication link. The audio processing pipeline outputs data to the A/V port 140 for reproduction by an external audio player or device having audio capabilities. [0047] The front panel I/O subassembly 130 supports the functionality of the power button 150 and the eject button 152, as well as any LEDs (light emitting diodes) or other indicators exposed on the outer surface of the multimedia console 100. A system power supply module 136 provides power to the components of the multimedia console 100. A fan 138 cools the circuitry within the multimedia console 100. [0048] The CPU 101, GPU 108, memory controller 110, and various other components within the multimedia console 100 are interconnected via one or more buses, including serial and parallel buses, a memory bus, a peripheral bus, and a processor or local bus using any of a variety of bus architectures. By way of example, such architectures can include a Peripheral Component Interconnects (PCI) bus, PCI-Express bus, etc.
[0049] When the multimedia console 100 is powered ON, application data may be loaded from the system memory 143 into memory 112 and/or caches 102, 104 and executed on the CPU 101. The application may present a graphical user interface that provides a consistent user experience when navigating to different media types available on the multimedia console 100. In operation, applications and/or other media contained within the media drive 144 may be launched or played from the media drive 144 to provide additional functionalities to the multimedia console 100.
[0050] The multimedia console 100 may be operated as a standalone system by simply connecting the system to a television or other display. In this standalone mode, the multimedia console 100 allows one or more users to interact with the system, watch movies, or listen to music. However, with the integration of broadband connectivity made available through the network interface 124 or the wireless adapter 148, the multimedia console 100 may further be operated as a participant in a larger network community. [0051] When the multimedia console 100 is powered ON, a set amount of hardware resources are reserved for system use by the multimedia console operating system. These resources may include a reservation of memory (e.g., 16MB), CPU and GPU cycles (e.g., 5%), networking bandwidth (e.g., 8 kbs), etc. Because these resources are reserved at system boot time, the reserved resources do not exist from the application's view.
[0052] In particular, the memory reservation preferably is large enough to contain the launch kernel, concurrent system applications and drivers. The CPU reservation is preferably constant such that if the reserved CPU usage is not used by the system applications, an idle thread will consume any unused cycles. [0053] With regard to the GPU reservation, lightweight messages generated by the system applications (e.g., popups) are displayed by using a GPU interrupt to schedule code to render popup into an overlay. The amount of memory required for an overlay depends on the overlay area size and the overlay preferably scales with screen resolution. Where a full user interface is used by the concurrent system application, it is preferable to use a resolution independent of application resolution. A sealer may be used to set this resolution such that the need to change frequency and cause a TV resynch is eliminated.
[0054] After the multimedia console 100 boots and system resources are reserved, concurrent system applications execute to provide system functionalities. The system functionalities are encapsulated in a set of system applications that execute within the reserved system resources described above. The operating system kernel identifies threads that are system application threads versus gaming application threads. The system applications are preferably scheduled to run on the CPU 101 at predetermined times and intervals in order to provide a consistent system resource view to the application. The scheduling is to minimize cache disruption for the gaming application running on the console.
[0055] When a concurrent system application requires audio, audio processing is scheduled asynchronously to the gaming application due to time sensitivity. A multimedia console application manager (described below) controls the gaming application audio level (e.g., mute, attenuate) when system applications are active. [0056] Input devices (e.g., controllers 142(1) and 142(2)) are shared by gaming applications and system applications. The input devices are not reserved resources, but are to be switched between system applications and the gaming application such that each will have a focus of the device. The application manager preferably controls the switching of input stream, without knowledge the gaming application's knowledge and a driver maintains state information regarding focus switches. The cameras 26, 28 and capture device 20 may define additionl input devices for the console 100.
[0057] FIG. 3B illustrates another example embodiment of a computing environment 220 that may be the computing environment 12 shown in FIGs. 1 A-2 used to interpret one or more gestures in a target recognition, analysis, and tracking system. The computing system environment 220 is only one example of a suitable computing environment and is not intended to suggest any limitation as to the scope of use or functionality of the presently disclosed subject matter. Neither should the computing environment 220 be interpreted as having any dependency or requirement relating to any one or combination of components illustrated in the exemplary operating environment 220. In some embodiments the various depicted computing elements may include circuitry configured to instantiate specific aspects of the present disclosure. For example, the term circuitry used in the disclosure can include specialized hardware components configured to perform function(s) by firmware or switches. In other examples embodiments the term circuitry can include a general purpose processing unit, memory, etc., configured by software instructions that embody logic operable to perform function(s). In example embodiments where circuitry includes a combination of hardware and software, an implementer may write source code embodying logic and the source code can be compiled into machine readable code that can be processed by the general purpose processing unit. Since one can appreciate that the state of the art has evolved to a point where there is little difference between hardware, software, or a combination of hardware/software, the selection of hardware versus software to effectuate specific functions is a design choice left to an implementer. More specifically, one of skill in the art can appreciate that a software process can be transformed into an equivalent hardware structure, and a hardware structure can itself be transformed into an equivalent software process. Thus, the selection of a hardware implementation versus a software implementation is one of design choice and left to the implementer.
[0058] In FIG. 3B, the computing environment 220 comprises a computer 241, which typically includes a variety of computer readable media. Computer readable media can be any available media that can be accessed by computer 241 and includes both volatile and nonvolatile media, removable and non-removable media. The system memory 222 includes computer storage media in the form of volatile and/or nonvolatile memory such as read only memory (ROM) 223 and random access memory (RAM) 260. A basic input/output system 224 (BIOS), containing the basic routines that help to transfer information between elements within computer 241, such as during start-up, is typically stored in ROM 223. RAM 260 typically contains data and/or program modules that are immediately accessible to and/or presently being operated on by processing unit 259. By way of example, and not limitation, FIG. 3B illustrates operating system 225, application programs 226, other program modules 227, and program data 228.
[0059] The computer 241 may also include other removable/non-removable, volatile/nonvolatile computer storage media. By way of example only, FIG. 3B illustrates a hard disk drive 238 that reads from or writes to non-removable, nonvolatile magnetic media, a magnetic disk drive 239 that reads from or writes to a removable, nonvolatile magnetic disk 254, and an optical disk drive 240 that reads from or writes to a removable, nonvolatile optical disk 253 such as a CD ROM or other optical media. Other removable/non-removable, volatile/nonvolatile computer storage media that can be used in the exemplary operating environment include, but are not limited to, magnetic tape cassettes, flash memory cards, digital versatile disks, digital video tape, solid state RAM, solid state ROM, and the like. The hard disk drive 238 is typically connected to the system bus 221 through an non-removable memory interface such as interface 234, and magnetic disk drive 239 and optical disk drive 240 are typically connected to the system bus 221 by a removable memory interface, such as interface 235.
[0060] The drives and their associated computer storage media discussed above and illustrated in FIG. 3B, provide storage of computer readable instructions, data structures, program modules and other data for the computer 241. In FIG. 3B, for example, hard disk drive 238 is illustrated as storing operating system 258, application programs 257, other program modules 256, and program data 255. Note that these components can either be the same as or different from operating system 225, application programs 226, other program modules 227, and program data 228. Operating system 258, application programs 257, other program modules 256, and program data 255 are given different numbers here to illustrate that, at a minimum, they are different copies. A user may enter commands and information into the computer 241 through input devices such as a keyboard 251 and pointing device 252, commonly referred to as a mouse, trackball or touch pad. Other input devices (not shown) may include a microphone, joystick, game pad, satellite dish, scanner, or the like. These and other input devices are often connected to the processing unit 259 through a user input interface 236 that is coupled to the system bus, but may be connected by other interface and bus structures, such as a parallel port, game port or a universal serial bus (USB). The cameras 26, 28 and capture device 20 may define additionl input devices for the console 100. A monitor 242 or other type of display device is also connected to the system bus 221 via an interface, such as a video interface 232. In addition to the monitor, computers may also include other peripheral output devices such as speakers 244 and printer 243, which may be connected through a output peripheral interface 233.
[0061] The computer 241 may operate in a networked environment using logical connections to one or more remote computers, such as a remote computer 246. The remote computer 246 may be a personal computer, a server, a router, a network PC, a peer device or other common network node, and typically includes many or all of the elements described above relative to the computer 241, although only a memory storage device 247 has been illustrated in FIG. 3B. The logical connections depicted in FIG. 3B include a local area network (LAN) 245 and a wide area network (WAN) 249, but may also include other networks. Such networking environments are commonplace in offices, enterprise- wide computer networks, intranets and the Internet. [0062] When used in a LAN networking environment, the computer 241 is connected to the LAN 245 through a network interface or adapter 237. When used in a WAN networking environment, the computer 241 typically includes a modem 250 or other means for establishing communications over the WAN 249, such as the Internet. The modem 250, which may be internal or external, may be connected to the system bus 221 via the user input interface 236, or other appropriate mechanism. In a networked environment, program modules depicted relative to the computer 241, or portions thereof, may be stored in the remote memory storage device. By way of example, and not limitation, FIG. 3B illustrates remote application programs 248 as residing on memory device 247. It will be appreciated that the network connections shown are exemplary and other means of establishing a communications link between the computers may be used.
[0063] FIG. 4A depicts an example skeletal mapping of a user that may be generated from the capture device 20. In this embodiment, a variety of joints and bones are identified: each hand 302, each forearm 304, each elbow 306, each bicep 308, each shoulder 310, each hip 312, each thigh 314, each knee 316, each foreleg 318, each foot 320, the head 322, the torso 324, the top 326 and bottom 328 of the spine, and the waist 330. Where more points are tracked, additional features may be identified, such as the bones and joints of the fingers or toes, or individual features of the face, such as the nose and eyes. [0064] Through moving his body, a user may create gestures. A gesture comprises a motion or pose by a user that may be captured as image data and parsed for meaning. A gesture may be dynamic, comprising a motion, such as mimicking throwing a ball. A gesture may be a static pose, such as holding one's crossed forearms 304 in front of his torso 324. A gesture may also incorporate props, such as by swinging a mock sword. A gesture may comprise more than one body part, such as clapping the hands 302 together, or a subtler motion, such as pursing one's lips.
[0065] Gestures may be used for input in a general computing context. For instance, various motions of the hands 302 or other body parts may correspond to common system wide tasks such as navigate up or down in a hierarchical list, open a file, close a file, and save a file. Gestures may also be used in a video-game-specific context, depending on the game. For instance, with a driving game, various motions of the hands 302 and feet 320 may correspond to steering a vehicle in a direction, shifting gears, accelerating, and breaking.
[0066] A user may generate a gesture that corresponds to walking or running, by walking or running in place himself. The user may alternately lift and drop each leg 312- 320 to mimic walking without moving. The system may parse this gesture by analyzing each hip 312 and each thigh 314. A step may be recognized when one hip-thigh angle (as measured relative to a vertical line, wherein a standing leg has a hip-thigh angle of 0°, and a forward horizontally extended leg has a hip-thigh angle of 90°) exceeds a certain threshold relative to the other thigh. A walk or run may be recognized after some number of consecutive steps by alternating legs. The time between the two most recent steps may be thought of as a period. After some number of periods where that threshold angle is not met, the system may determine that the walk or running gesture has ceased.
[0067] Given a "walk or run" gesture, an application may set values for parameters associated with this gesture. These parameters may include the above threshold angle, the number of steps required to initiate a walk or run gesture, a number of periods where no step occurs to end the gesture, and a threshold period that determines whether the gesture is a walk or a run. A fast period may correspond to a run, as the user will be moving his legs quickly, and a slower period may correspond to a walk. [0068] A gesture may be associated with a set of default parameters at first that the application may override with its own parameters. In this scenario, an application is not forced to provide parameters, but may instead use a set of default parameters that allow the gesture to be recognized in the absence of application-defined parameters. [0069] There are a variety of outputs that may be associated with the gesture.
There may be a baseline "yes or no" as to whether a gesture is occurring. There also may be a confidence level, which corresponds to the likelihood that the user's tracked movement corresponds to the gesture. This could be a linear scale that ranges over floating point numbers between 0 and 1, inclusive. Wherein an application receiving this gesture information cannot accept false-positives as input, it may use only those recognized gestures that have a high confidence level, such as at least .95. Where an application must recognize every instance of the gesture, even at the cost of false- positives, it may use gestures that have at least a much lower confidence level, such as those merely greater than .2. The gesture may have an output for the time between the two most recent steps, and where only a first step has been registered, this may be set to a reserved value, such as -1 (since the time between any two steps must be positive). The gesture may also have an output for the highest thigh angle reached during the most recent step.
[0070] Another exemplary gesture is a "heel lift jump." In this, a user may create the gesture by raising his heels off the ground, but keeping his toes planted.
Alternatively, the user may jump into the air where his feet 320 leave the ground entirely. The system may parse the skeleton for this gesture by analyzing the angle relation of the shoulders 310, hips 312 and knees 316 to see if they are in a position of alignment equal to standing up straight. Then these points and upper 326 and lower 328 spine points may be monitored for any upward acceleration. A sufficient combination of acceleration may trigger a jump gesture.
[0071] Given this "heel lift jump" gesture, an application may set values for parameters associated with this gesture. The parameters may include the above acceleration threshold, which determines how fast some combination of the user's shoulders 310, hips 312 and knees 316 must move upward to trigger the gesture, as well as a maximum angle of alignment between the shoulders 310, hips 312 and knees 316 at which a jump may still be triggered.
[0072] The outputs may comprise a confidence level, as well as the user's body angle at the time of the jump. [0073] Setting parameters for a gesture based on the particulars of the application that will receive the gesture is important in accurately identifying gestures. Properly identifying gestures and the intent of a user greatly helps in creating a positive user experience. Where a gesture recognizer system is too sensitive, and even a slight forward motion of the hand 302 is interpreted as a throw, the user may become frustrated because gestures are being recognized where he has no intent to make a gesture, and thus, he lacks control over the system. Where a gesture recognizer system is not sensitive enough, the system may not recognize conscious attempts by the user to make a throwing gesture, frustrating him in a similar manner. At either end of the sensitivity spectrum, the user becomes frustrated because he cannot properly provide input to the system.
[0074] Another parameter to a gesture may be a distance moved. Where a user's gestures control the actions of an avatar in a virtual environment, that avatar may be arm's length from a ball. If the user wishes to interact with the ball and grab it, this may require the user to extend his arm 302-310 to full length while making the grab gesture. In this situation, a similar grab gesture where the user only partially extends his arm 302-310 may not achieve the result of interacting with the ball.
[0075] A gesture or a portion thereof may have as a parameter a volume of space in which it must occur. This volume of space may typically be expressed in relation to the body where a gesture comprises body movement. For instance, a football throwing gesture for a right-handed user may be recognized only in the volume of space no lower than the right shoulder 310a, and on the same side of the head 322 as the throwing arm 302a-310a. It may not be necessary to define all bounds of a volume, such as with this throwing gesture, where an outer bound away from the body is left undefined, and the volume extends out indefinitely, or to the edge of scene that is being monitored. [0076] FIG. 4B provides further details of one exemplary embodiment of the gesture recognizer engine 190 of FIG. 2. As shown, the gesture recognizer engine 190 may comprise at least one filter 418 to determine a gesture or gestures. A filter 418 comprises information defining a gesture 426 (hereinafter referred to as a "gesture") along with parameters 428, or metadata, for that gesture. For instance, a throw, which comprises motion of one of the hands from behind the rear of the body to past the front of the body, may be implemented as a gesture 426 comprising information representing the movement of one of the hands of the user from behind the rear of the body to past the front of the body, as that movement would be captured by the depth camera. Parameters 428 may then be set for that gesture 426. Where the gesture 426 is a throw, a parameter 428 may be a threshold velocity that the hand has to reach, a distance the hand must travel (either absolute, or relative to the size of the user as a whole), and a confidence rating by the recognizer engine that the gesture occurred. These parameters 428 for the gesture 426 may vary between applications, between contexts of a single application, or within one context of one application over time.
[0077] Filters may be modular or interchangeable. In an embodiment, a filter has a number of inputs, each of those inputs having a type, and a number of outputs, each of those outputs having a type. In this situation, a first filter may be replaced with a second filter that has the same number and types of inputs and outputs as the first filter without altering any other aspect of the recognizer engine architecture. For instance, there may be a first filter for driving that takes as input skeletal data and outputs a confidence that the gesture associated with the filter is occurring and an angle of steering. Where one wishes to substitute this first driving filter with a second driving filter - perhaps because the second driving filter is more efficient and requires fewer processing resources - one may do so by simply replacing the first filter with the second filter so long as the second filter has those same inputs and outputs - one input of skeletal data type, and two outputs of confidence type and angle type.
[0078] A filter need not have a parameter. For instance, a "user height" filter that returns the user's height may not allow for any parameters that may be tuned. An alternate "user height" filter may have tunable parameters - such as to whether to account for a user's footwear, hairstyle, headwear and posture in determining the user's height. [0079] Inputs to a filter may comprise things such as joint data about a user's joint position, like angles formed by the bones that meet at the joint, RGB color data from the scene, and the rate of change of an aspect of the user. Outputs from a filter may comprise things such as the confidence that a given gesture is being made, the speed at which a gesture motion is made, and a time at which a gesture motion is made.
[0080] A context may be a cultural context, and it may be an environmental context. A cultural context refers to the culture of a user using a system. Different cultures may use similar gestures to impart markedly different meanings. For instance, an American user who wishes to tell another user to "look" or "use his eyes" may put his index finger on his head close to the distal side of his eye. However, to an Italian user, this gesture may be interpreted as a reference to the mafia.
[0081] Similarly, there may be different contexts among different environments of a single application. Take a first-person shooter game that involves operating a motor vehicle. While the user is on foot, making a fist with the fingers towards the ground and extending the fist in front and away from the body may represent a punching gesture. While the user is in the driving context, that same motion may represent a "gear shifting" gesture. There may also be one or more menu environments, where the user can save his game, select among his character's equipment or perform similar actions that do not comprise direct game-play. In that environment, this same gesture may have a third meaning, such as to select something or to advance to another screen.
[0082] The gesture recognizer engine 190 may have a base recognizer engine 416 that provides functionality to a gesture filter 418. In an embodiment, the functionality that the recognizer engine 416 implements includes an input-over-time archive that tracks recognized gestures and other input, a Hidden Markov Model implementation (where the modeled system is assumed to be a Markov process - one where a present state encapsulates any past state information necessary to determine a future state, so no other past state information must be maintained for this purpose - with unknown parameters, and hidden parameters are determined from the observable data), as well as other functionality required to solve particular instances of gesture recognition.
[0083] Filters 418 are loaded and implemented on top of the base recognizer engine 416 and can utilize services provided by the engine 416 to all filters 418. In an embodiment, the base recognizer engine 416 processes received data to determine whether it meets the requirements of any filter 418. Since these provided services, such as parsing the input, are provided once by the base recognizer engine 416 rather than by each filter 418, such a service need only be processed once in a period of time as opposed to once per filter 418 for that period, so the processing required to determine gestures is reduced.
[0084] An application may use the filters 418 provided by the recognizer engine 190, or it may provide its own filter 418, which plugs in to the base recognizer engine 416. In an embodiment, all filters 418 have a common interface to enable this plug-in characteristic. Further, all filters 418 may utilize parameters 428, so a single gesture tool as described below may be used to debug and tune the entire filter system 418.
[0085] These parameters 428 may be tuned for an application or a context of an application by a gesture tool 420. In an embodiment, the gesture tool 420 comprises a plurality of sliders 422, each slider 422 corresponding to a parameter 428, as well as a pictoral representation of a body 424. As a parameter 428 is adjusted with a corresponding slider 422, the body 424 may demonstrate both actions that would be recognized as the gesture with those parameters 428 and actions that would not be recognized as the gesture with those parameters 428, identified as such. This visualization of the parameters 428 of gestures provides an effective means to both debug and fine tune a gesture.
[0086] FIG. 5 depicts more complex gestures or filters 418 created from stacked gestures or filters 418. Gestures can stack on each other. That is, more than one gesture may be expressed by a user at a single time. For instance, rather than disallowing any input but a throw when a throwing gesture is made, or requiring that a user remain motionless save for the components of the gesture (e.g. stand still while making a throwing gesture that involves only one arm). Where gestures stack, a user may make a jumping gesture and a throwing gesture simultaneously, and both of these gestures will be recognized by the gesture engine.
[0087] FIG. 5 A depicts a simple gesture filter 418 according to the stacking paradigm. The IFilter filter 502 is a basic filter 418 that may be used in every gesture filter. IFilter 502 takes user position data 504 and outputs a confidence level 506 that a gesture has occurred. It also feeds that position data 504 into a Steering Wheel filter 508 that takes it as an input and outputs an angle to which the user is steering (e.g. 40 degrees to the right of the user's current bearing) 510.
[0088] FIG. 5B depicts a more complex gesture that stacks filters 418 onto the gesture filter of FIG. 5 A. In addition to IFilter 502 and Steering Wheel 508, there is an ITracking filter 512 that receives position data 504 from IFilter 502 and outputs the amount of progress the user has made through a gesture 514. ITracking 512 also feeds position data 504 to GreaseLightning 516 and EBrake 518, which are filters 418 regarding other gestures that may be made in operating a vehicle, such as using the emergency brake. [0089] FIG. 6 depicts an example gesture that a user 602 may make to signal for a "fair catch" in a football video game. These figures depict the user at points in time, with FIG. 6A being the first point in time, and FIG. 6E being the last point in time. Each of these figures may correspond to a snapshot or frame of image data as captured by a depth camera 402, though not necessarily consecutive frames of image data, as the depth camera 402 may be able to capture frames more rapidly than the user may cover the distance. For instance, this gesture may occur over a period of 3 seconds, and where a depth camera captures data at 40 frames per second, it would capture 60 frames of image data while the user 602 made this fair catch gesture. [0090] In FIG. 6A, the user 602 begins with his arms 604 down at his sides. He then raises them up and above his shoulders as depicted in FIG. 6B and then further up, to the approximate level of his head, as depicted in FIG. 6C. From there, he lowers his arms 604 to shoulder level, as depicted in FIG. 6D, and then again raises them up, to the approximate level of his head, as depicted in FIG. 6E. Where a system captures these positions by the user 602 without any intervening position that may signal that the gesture is cancelled, or another gesture is being made, it may have the fair catch gesture filter output a high confidence level that the user 602 made the fair catch gesture.
[0091] FIG. 7 depicts the example "fair catch" gesture of FIG. 5 as each frame of image data has been parsed to produce a skeletal map of the user. The system, having produced a skeletal map from the depth image of the user, may now determine how that user's body moves over time, and from that, parse the gesture.
[0092] In FIG. 7 A, the user's shoulders 310, are above his elbows 306, which in turn are above his hands 302. The shoulders 310, elbows 306 and hands 302 are then at a uniform level in FIG. 7B. The system then detects in FIG. 7C that the hands 302 are above the elbows, which are above the shoulders 310. In FIG. 7D, the user has returned to the position of FIG. 7B, where the shoulders 310, elbows 306 and hands 302 are at a uniform level. In the final position of the gesture, shown in FIG. 7E, the user returns to the position of FIG. 7C, where the hands 302 are above the elbows, which are above the shoulders 310.
[0093] While the capture device 20 captures a series of still images, such that in any one image the user appears to be stationary, the user is moving in the course of performing this gesture (as opposed to a stationary gesture, as discussed supra). The system is able to take this series of poses in each still image, and from that determine the confidence level of the moving gesture that the user is making.
[0094] In performing the gesture, a user is unlikely to be able to create an angle as formed by his right shoulder 310a, right elbow 306a and right hand 302a of, for example, between 140° and 145°. So, the application using the filter 418 for the fair catch gesture 426 may tune the associated parameters 428 to best serve the specifics of the application. For instance, the positions in FIGs. 7C and 7E may be recognized any time the user has his hands 302 above his shoulders 310, without regard to elbow 306 position. A set of parameters that are more strict may require that the hands 302 be above the head 310 and that the elbows 306 be both above the shoulders 310 and between the head 322 and the hands 302. Additionally, the parameters 428 for a fair catch gesture 426 may require that the user move from the position of FIG. 7A through the position of FIG. 7E within a specified period of time, such as 1.5 seconds, and if the user takes more than 1.5 seconds to move through these positions, it will not be recognized as the fair catch 418, and a very low confidence level may be output. [0095] FIGs. 8A-C illustrate a user making the same system-recognized running gesture through different captured movements and poses.
[0096] FIG. 8A illustrates a user making a full running gesture. User 18 is captured by capture device 20. User 18 creates the full running gesture by running in place - alternately lifting each of his knees to approximately waist height then dropping the leg down to the ground. This version of the full running gesture is a periodic gesture in that user 18 repeats the motions that comprise the gesture for the duration that he wants the gesture to last.
[0097] FIG. 8B illustrates a user making a shortcut running gesture, the shortcut gesture comprising a subset of the movement of the full running gesture of FIG. 8 A. To make this version of the shortcut running gesture, user 18 lifts one of his legs such that his knee is approximately at hip level, and holds this pose. This gesture shortcut comprises a subset of the movement of the full gesture of FIG. 8 A - where the user in FIG. 8 A repeatedly lifts and drops his knees, here the user lifts his knee once and holds that pose. While the full gesture of FIG. 8 A involves periodic movement, in this embodiment, the shortcut gesture involves a series of non-repeated movements, or a series of movements where the series as a whole is not repeated. In an embodiment, user 18 drops his knee down to a standing pose when he wishes to end the gesture. In an embodiment, this act of dropping the knee may also comprise a subset of the full gesture. In an embodiment, computing environment 12 determines that this movement is to end the gesture shortcut rather than produce the full gesture when user 18 holds his knee at approximately hip level for more than a specified amount of time, serial
[0098] FIG. 8C illustrates a user making a second type of shortcut running gesture, the second type of shortcut running gesture comprising movement separate from the full running gesture of FIG. 8 A. Here, user 18 takes one step forward and holds this pose with one foot in front of the other, both feet on the ground, for the duration that he wishes to produce the running gesture. This position is not found in the full running gesture of FIG. 8 A. User 18 may end the gesture by stepping back to a standing pose. This gesture is similar to that of FIG. 8B in that both involve movement to initiate the gesture, then holding a pose to maintain the gesture, and movement to end the gesture. [0099] FIG. 9 illustrates example operating procedures for gesture shortcuts. As discussed above, one gesture input to a computing device may be recognized by the computing device as a result of a plurality of ways performed by a user. In an embodiment, this plurality of ways that a gesture may be performed by a user comprises a full version of the gesture and a shortcut of the gesture.
[0100] Gesture shortcuts may be used in a variety of application contexts. For instance, running gesture shortcuts may be used in applications that involve running, like a track and field game. Text input shortcuts may be used in a text input context of an application. For example, the user may use sign language gestures to input text. A full version of a word gesture may comprise signing each letter of the word, such as H-E-A-R- T. A shortcut for the "heart" word gesture may comprise a single gesture for heart, such from the user forming hands into a representation of a heart. Such a sign language may comprise American Sign Language (ASL).
[0101] A gesture shortcut may involve different body parts than the corresponding full version of a gesture. For instance, where a user lacks use of his legs, and the full version of a running gesture involves running in place, the shortcut of the gesture may involve mimicking a running motion with the user's hands.
[0102] Optional operation 902 depicts receiving user input corresponding to defining the shortcut of the gesture. For instance, the user, either by being prompted by the computing device or through indicating to the computing device his desire to do so, may make a motion or pose that is captured by a capture device and stored as a way to perform the gesture.
[0103] In an embodiment, where the user has defined a gesture shortcut through his movement or pose, he may then refine the gesture shortcut on the system. For instance, where gestures are recognized using filters and corresponding parameters, he may tune the parameters of his gesture shortcut in ways as discussed above.
[0104] In an embodiment, the shortcut of the gesture corresponds to a full version of a second gesture. A gesture shortcut may correspond to a plurality of full gestures, and where the user defines a shortcut, he may indicate that the shortcut is to correspond to a plurality of full gestures. For instance, in a context of printing a text file, the user may define one gesture shortcut that corresponds to the full gesture of selecting the paper orientation to be portrait, the full gesture of selecting four copies to print, and the full gesture of selecting a specific printer to print from. [0105] In an embodiment where gestures are recognized through gesture filters and parameters, the shortcut of a gesture and the full version of a gesture may use the same gesture filter, but a different value for one or more parameters. For instance, the full version of a "ball throw" gesture may require that the user move his hand from behind his torso to approximately arm's length in front of his torso. The shortcut may reduce the required distance that the hand must travel such that the hand must neither be extended as far back nor as far forward. This may be effectuated for changing a parameter value or values, such as one for "minimum hand distance."
[0106] Operation 904 depicts receiving data captured by a capture device, the data corresponding to a user-performed gesture. The capture device may capture a scene that contains all of the user, such as from the floor to the ceiling and to the wall on each side of a room at the distance in which the user is located. The capture device may also capture a scene that contains only part of the user, such as the user from the abdomen up as he or she sits at a desk. The capture device may also capture an object controlled by the user, such as a prop camera that the user holds in his or her hand.
[0107] Optional operation 906 depicts determining from the application to process the data with the shortcut of the gesture. An application may limit the shortcuts that are used as input in some way. For instance, in a track and field game, running may be considered integral to the process and the application may disallow or disable a shortcut for a running gesture, requiring a user to make a full running gesture when he wishes to run. In contrast, in a first-person shooter game, running may be considered ancillary to use of the game, so use of a shortcut for a running gesture may be allowed. In this first- person shooter game, mechanics for discharging a firearm may be considered integral to the process, and the application may disallow or disable shortcuts for an aiming or firing gesture.
[0108] In an embodiment, a user may perform both shortcuts for gestures and full versions of gestures that are recognized, in the same manner that a user may simultaneously perform multiple gestures, as discussed previously. Using the first-person shooter example, the user may simultaneously make the shortcut for the running gesture, and the full version of the aiming gesture.
[0109] In an embodiment, this determination to process the data with the shortcut of the gesture originates from the user. For instance, which shortcuts to process may correspond to a difficulty level of the application that the user selects. Where the user chooses the lowest difficulty level, all shortcuts may be processed. As the user increases the difficulty level, the number of allowed shortcuts to process may decrease, until the highest difficulty level where no shortcuts are processed.
[0110] This determination may change over time to be adaptive to user ability. For instance, a default setting of allowed shortcuts may be implemented at the start of an application session, and the allowed shortcuts may be increased or decreased during the session as the user shows his ability to perform gestures well, or lack of such ability. Further, as the user tires during the course of a session, or increases in competence, the allowed shortcuts may be increased or decreased to correspond to his current state of ability. [0111] Operation 908 depicts processing the data to determine an output corresponding to whether the user performed a shortcut of a gesture, the shortcut of the gesture corresponding to a full version of the gesture. In an embodiment, this output may comprise a confidence level that the gesture occurred. In an embodiment, this may comprise an indication as to whether a full version of a gesture or a gesture shortcut was observed.
[0112] Operation 910 depicts sending the output corresponding to the shortcut of the gesture to the application. Where the present operations are performed by the application, the output may be sent to a component of the application that takes processed user input and maps it to in-application actions. [0113] Optional operation 912 depicts processing the data to determine an output corresponding to whether the user performed the full version of the gesture, and sending the output corresponding to the full version of the gesture to the application.
[0114] In an embodiment, the shortcut of the gesture comprises user movement that comprises a subset of user movement that comprises the full version of the gesture. [0115] In an embodiment, the output corresponding to the shortcut of the gesture corresponds to a high likelihood that the user triggered the gesture, the output corresponding to the full version of the gesture corresponds to a high likelihood that the user triggered the gesture, and the application recognizes only one user gesture. Where the shortcut of the gesture comprises a subset of the full version of the gesture, when the user performs the full version of the gesture he will also perform the shortcut of the gesture. Thus, for one intended gesture input, two gestures may be recognized. In an embodiment, where both the shortcut of the gesture and the full version of the gesture are recognized within a prescribed period of time (one that may be gesture and/or user specific), only one is used as input and the other is disregarded. [0116] In an embodiment, the output corresponding to the shortcut of the gesture corresponds to a high likelihood that the user triggered the gesture, the output corresponding to the full version of the gesture corresponds to a high likelihood that the user triggered the gesture, and the application uses an output corresponding to the full version of the gesture to add detail to the gesture. Where the shortcut of the gesture is recognized and processed (such as a corresponding animation or result is displayed on a display device) as an input by the application, and then the full version of the gesture is recognized while the shortcut of the gesture is being processed, output from the full version of the gesture may be used in the processing. [0117] For example, a full version of a "jump" gesture may comprise the user jumping. A shortcut of that "jump" gesture may comprise the initial motions of the full version of the gesture - a crouch and rise - and output a confidence level that the gesture was performed. As a result of observing the shortcut of the jump gesture, the application may process this by displaying the user's avatar as jumping. While this occurs, if the user completes the full version of the jump gesture by continuing to rise and leaving the ground with both feet, the application may use a height that the user physically jumps to display the avatar as jumping a corresponding height to add detail to the currently-processed jump shorcut. If the user performed only the shortcut of the jump gesture, the application may have the avatar jump a default height. [0118] In an embodiment, where the user performs a shortcut of a gesture, it may correspond to lesser in-application accomplishment than if where the user performs the full version of the gesture. For instance, in a skateboarding game that ranks a user's performance with points scored, where the user performs a given trick using the shortcut of a skateboarding trick gesture, the user may receive fewer points than had he performed the given trick using the full version of the skateboarding trick gesture. Conclusion
[0119] While the present disclosure has been described in connection with the preferred aspects, as illustrated in the various figures, it is understood that other similar aspects may be used or modifications and additions may be made to the described aspects for performing the same function of the present disclosure without deviating therefrom. Therefore, the present disclosure should not be limited to any single aspect, but rather construed in breadth and scope in accordance with the appended claims. For example, the various procedures described herein may be implemented with hardware or software, or a combination of both. Thus, the methods and apparatus of the disclosed embodiments, or certain aspects or portions thereof, may take the form of program code (i.e., instructions) embodied in tangible media, such as floppy diskettes, CD-ROMs, hard drives, or any other machine-readable storage medium. When the program code is loaded into and executed by a machine, such as a computer, the machine becomes an apparatus configured for practicing the disclosed embodiments. In addition to the specific implementations explicitly set forth herein, other aspects and implementations will be apparent from consideration of the specification disclosed herein. It is intended that the specification and illustrated implementations be considered as examples only.

Claims

What is Claimed:
1. A method for using a gesture shortcut in a system that takes user (18) gestures as input to an application, comprising: receiving data captured by a capture device (20), the data corresponding to a user- performed gesture (902); processing the data to determine an output corresponding to whether the user performed a shortcut of a gesture, the shortcut of the gesture corresponding to a full version of the gesture (908); and sending the output corresponding to the shortcut of the gesture to the application (910).
2. The method of claim 1, further comprising: processing the data to determine an output corresponding to whether the user performed the full version of the gesture; and sending the output corresponding to the full version of the gesture to the application.
3. The method of claim 2, wherein the shortcut of the gesture comprises user movement that comprises a subset of user movement that comprises the full version of the gesture.
4. The method of claim 3, wherein the output corresponding to the shortcut of the gesture corresponds to a high likelihood that the user triggered the gesture, the output corresponding to the full version of the gesture corresponds to a high likelihood that the user triggered the gesture, and the application recognizes that the user has performed only one user gesture.
5. The method of claim 3, wherein the output corresponding to the shortcut of the gesture corresponds to a high likelihood that the user triggered the gesture, the output corresponding to the full version of the gesture corresponds to a high likelihood that the user triggered the gesture, and the application uses an output corresponding to the full version of the gesture to add detail to the gesture.
6. The method of claim 1, further comprising: receiving user input corresponding to defining the shortcut of the gesture.
7. The method of claim 1, wherein the shortcut of the gesture also corresponds to a full version of a second gesture.
8. The method of claim 1, wherein the shortcut of the gesture corresponds to a gesture filter and at least one parameter, the full version of the gesture corresponds to the gesture filter and the at least one parameter, and the value of at least one parameter corresponding to the shortcut of the gesture differs from the value of at least one parameter corresponding to the full version of the gesture.
9. The method of claim 1, further comprising: determining from the application to process the data with the shortcut of the gesture before processing the data to determine the output corresponding to whether the user performed the shortcut of the gesture.
10. The method of claim 9, wherein the operation of processing the data to determine an output corresponding to whether the user performed a shortcut of a gesture is performed only after receiving an indication from a user that such processing is desired.
11. The method of claim 1 , wherein the user performing the shortcut of the gesture corresponds to a smaller achievement than the user performing the full version of the gesture.
12. A system for using a gesture shortcut in a system that takes user (18) gestures as input to an application, comprising: a capture device (20) for generating data corresponding to a user-performed gesture; a processor (101) that receives the data captured by the capture device, processes the data to determine an output corresponding to whether the user performed a shortcut of a gesture, the shortcut of the gesture corresponding to a full version of the gesture, and sends the output corresponding to the shortcut of the gesture to the application.
13. The system of claim 12, wherein the processor also processes the data to determine an output corresponding to whether the user performed the full version of the gesture, and sends the output corresponding to the full version of the gesture to the application.
14. The system of claim 13, wherein the shortcut of the gesture comprises user movement that comprises a subset of user movement that comprises the full version of the gesture.
15. The system of claim 13, wherein the output corresponding to the shortcut of the gesture corresponds to a high likelihood that the user triggered the gesture, the output corresponding to the full version of the gesture corresponds to a high likelihood that the user triggered the gesture, and the application recognizes only one user gesture.
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Cited By (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20120016720A (en) * 2010-08-17 2012-02-27 엘지전자 주식회사 Display apparatus and controlling method thereof
JP2013037675A (en) * 2011-06-23 2013-02-21 Omek Interactive Ltd System and method for close-range movement tracking
JP2014501415A (en) * 2011-01-05 2014-01-20 ソフトキネティック ソフトウェア User interface method and system based on natural gestures
WO2014126509A1 (en) * 2013-02-12 2014-08-21 Permyakov Aleksandr Mihailovich Soccer game simulation for the game-based training of soccer players
US9398243B2 (en) 2011-01-06 2016-07-19 Samsung Electronics Co., Ltd. Display apparatus controlled by motion and motion control method thereof
US9513711B2 (en) 2011-01-06 2016-12-06 Samsung Electronics Co., Ltd. Electronic device controlled by a motion and controlling method thereof using different motions to activate voice versus motion recognition
EP3165413A1 (en) * 2015-11-05 2017-05-10 Aisin Seiki Kabushiki Kaisha Operation input detection device and control device for vehicular opening-closing body
US11048333B2 (en) 2011-06-23 2021-06-29 Intel Corporation System and method for close-range movement tracking

Families Citing this family (41)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR101633332B1 (en) * 2009-09-30 2016-06-24 엘지전자 주식회사 Mobile terminal and Method of controlling the same
CN106943743A (en) * 2011-02-11 2017-07-14 漳州市爵晟电子科技有限公司 A kind of human-computer interaction control system
US10146329B2 (en) * 2011-02-25 2018-12-04 Nokia Technologies Oy Method and apparatus for providing different user interface effects for different motion gestures and motion properties
US9857868B2 (en) 2011-03-19 2018-01-02 The Board Of Trustees Of The Leland Stanford Junior University Method and system for ergonomic touch-free interface
US8840466B2 (en) * 2011-04-25 2014-09-23 Aquifi, Inc. Method and system to create three-dimensional mapping in a two-dimensional game
US8657683B2 (en) 2011-05-31 2014-02-25 Microsoft Corporation Action selection gesturing
US8740702B2 (en) 2011-05-31 2014-06-03 Microsoft Corporation Action trigger gesturing
US8845431B2 (en) 2011-05-31 2014-09-30 Microsoft Corporation Shape trace gesturing
US8751972B2 (en) * 2011-09-20 2014-06-10 Google Inc. Collaborative gesture-based input language
US9628843B2 (en) * 2011-11-21 2017-04-18 Microsoft Technology Licensing, Llc Methods for controlling electronic devices using gestures
US8854433B1 (en) 2012-02-03 2014-10-07 Aquifi, Inc. Method and system enabling natural user interface gestures with an electronic system
EP2650754A3 (en) * 2012-03-15 2014-09-24 Omron Corporation Gesture recognition apparatus, electronic device, gesture recognition method, control program, and recording medium
US9098739B2 (en) 2012-06-25 2015-08-04 Aquifi, Inc. Systems and methods for tracking human hands using parts based template matching
US9111135B2 (en) 2012-06-25 2015-08-18 Aquifi, Inc. Systems and methods for tracking human hands using parts based template matching using corresponding pixels in bounded regions of a sequence of frames that are a specified distance interval from a reference camera
US8836768B1 (en) 2012-09-04 2014-09-16 Aquifi, Inc. Method and system enabling natural user interface gestures with user wearable glasses
US9092665B2 (en) 2013-01-30 2015-07-28 Aquifi, Inc Systems and methods for initializing motion tracking of human hands
US9129155B2 (en) 2013-01-30 2015-09-08 Aquifi, Inc. Systems and methods for initializing motion tracking of human hands using template matching within bounded regions determined using a depth map
US10134267B2 (en) 2013-02-22 2018-11-20 Universal City Studios Llc System and method for tracking a passive wand and actuating an effect based on a detected wand path
US9298266B2 (en) 2013-04-02 2016-03-29 Aquifi, Inc. Systems and methods for implementing three-dimensional (3D) gesture based graphical user interfaces (GUI) that incorporate gesture reactive interface objects
KR102163996B1 (en) * 2013-04-03 2020-10-13 삼성전자 주식회사 Apparatus and Method for improving performance of non-contact type recognition function in a user device
KR102148809B1 (en) 2013-04-22 2020-08-27 삼성전자주식회사 Apparatus, method and computer readable recording medium for displaying shortcut window
EP3007786A1 (en) 2013-06-14 2016-04-20 Intercontinental Great Brands LLC Interactive video games
US9798388B1 (en) 2013-07-31 2017-10-24 Aquifi, Inc. Vibrotactile system to augment 3D input systems
US9423946B2 (en) 2013-08-12 2016-08-23 Apple Inc. Context sensitive actions in response to touch input
TWI537767B (en) * 2013-10-04 2016-06-11 財團法人工業技術研究院 System and method of multi-user coaching inside a tunable motion-sensing range
US20160262685A1 (en) 2013-11-12 2016-09-15 Highland Instruments, Inc. Motion analysis systemsand methods of use thereof
US9507417B2 (en) 2014-01-07 2016-11-29 Aquifi, Inc. Systems and methods for implementing head tracking based graphical user interfaces (GUI) that incorporate gesture reactive interface objects
US9619105B1 (en) 2014-01-30 2017-04-11 Aquifi, Inc. Systems and methods for gesture based interaction with viewpoint dependent user interfaces
US9430038B2 (en) * 2014-05-01 2016-08-30 Microsoft Technology Licensing, Llc World-locked display quality feedback
US9361732B2 (en) * 2014-05-01 2016-06-07 Microsoft Technology Licensing, Llc Transitions between body-locked and world-locked augmented reality
US10061058B2 (en) 2014-05-21 2018-08-28 Universal City Studios Llc Tracking system and method for use in surveying amusement park equipment
US10025990B2 (en) 2014-05-21 2018-07-17 Universal City Studios Llc System and method for tracking vehicles in parking structures and intersections
US9433870B2 (en) 2014-05-21 2016-09-06 Universal City Studios Llc Ride vehicle tracking and control system using passive tracking elements
US9429398B2 (en) 2014-05-21 2016-08-30 Universal City Studios Llc Optical tracking for controlling pyrotechnic show elements
US10207193B2 (en) 2014-05-21 2019-02-19 Universal City Studios Llc Optical tracking system for automation of amusement park elements
US9616350B2 (en) 2014-05-21 2017-04-11 Universal City Studios Llc Enhanced interactivity in an amusement park environment using passive tracking elements
US9600999B2 (en) 2014-05-21 2017-03-21 Universal City Studios Llc Amusement park element tracking system
US10238979B2 (en) 2014-09-26 2019-03-26 Universal City Sudios LLC Video game ride
CN108970112A (en) * 2018-07-05 2018-12-11 腾讯科技(深圳)有限公司 The method of adjustment and device of posture, storage medium, electronic device
AU2022210589A1 (en) * 2021-01-20 2023-09-07 Apple Inc. Methods for interacting with objects in an environment
US20230038709A1 (en) * 2021-07-28 2023-02-09 Purdue Research Foundation System and Method for Authoring Freehand Interactive Augmented Reality Applications

Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1408443A1 (en) 2002-10-07 2004-04-14 Sony France S.A. Method and apparatus for analysing gestures produced by a human, e.g. for commanding apparatus by gesture recognition
US20080270896A1 (en) 2007-04-27 2008-10-30 Per Ola Kristensson System and method for preview and selection of words

Family Cites Families (232)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4288078A (en) * 1979-11-20 1981-09-08 Lugo Julio I Game apparatus
US4695953A (en) * 1983-08-25 1987-09-22 Blair Preston E TV animation interactively controlled by the viewer
US4630910A (en) * 1984-02-16 1986-12-23 Robotic Vision Systems, Inc. Method of measuring in three-dimensions at high speed
US4627620A (en) * 1984-12-26 1986-12-09 Yang John P Electronic athlete trainer for improving skills in reflex, speed and accuracy
US4645458A (en) * 1985-04-15 1987-02-24 Harald Phillip Athletic evaluation and training apparatus
US4702475A (en) * 1985-08-16 1987-10-27 Innovating Training Products, Inc. Sports technique and reaction training system
US4843568A (en) * 1986-04-11 1989-06-27 Krueger Myron W Real time perception of and response to the actions of an unencumbered participant/user
US4711543A (en) * 1986-04-14 1987-12-08 Blair Preston E TV animation interactively controlled by the viewer
US4796997A (en) * 1986-05-27 1989-01-10 Synthetic Vision Systems, Inc. Method and system for high-speed, 3-D imaging of an object at a vision station
US5184295A (en) * 1986-05-30 1993-02-02 Mann Ralph V System and method for teaching physical skills
US4751642A (en) * 1986-08-29 1988-06-14 Silva John M Interactive sports simulation system with physiological sensing and psychological conditioning
US4809065A (en) * 1986-12-01 1989-02-28 Kabushiki Kaisha Toshiba Interactive system and related method for displaying data to produce a three-dimensional image of an object
US4817950A (en) * 1987-05-08 1989-04-04 Goo Paul E Video game control unit and attitude sensor
US5239464A (en) * 1988-08-04 1993-08-24 Blair Preston E Interactive video system providing repeated switching of multiple tracks of actions sequences
US5239463A (en) * 1988-08-04 1993-08-24 Blair Preston E Method and apparatus for player interaction with animated characters and objects
US4901362A (en) * 1988-08-08 1990-02-13 Raytheon Company Method of recognizing patterns
US4893183A (en) * 1988-08-11 1990-01-09 Carnegie-Mellon University Robotic vision system
JPH02199526A (en) * 1988-10-14 1990-08-07 David G Capper Control interface apparatus
US4925189A (en) * 1989-01-13 1990-05-15 Braeunig Thomas F Body-mounted video game exercise device
US5229756A (en) * 1989-02-07 1993-07-20 Yamaha Corporation Image control apparatus
US5469740A (en) * 1989-07-14 1995-11-28 Impulse Technology, Inc. Interactive video testing and training system
JPH03103822U (en) * 1990-02-13 1991-10-29
US5101444A (en) * 1990-05-18 1992-03-31 Panacea, Inc. Method and apparatus for high speed object location
US5148154A (en) * 1990-12-04 1992-09-15 Sony Corporation Of America Multi-dimensional user interface
US5534917A (en) * 1991-05-09 1996-07-09 Very Vivid, Inc. Video image based control system
US5417210A (en) * 1992-05-27 1995-05-23 International Business Machines Corporation System and method for augmentation of endoscopic surgery
US5295491A (en) * 1991-09-26 1994-03-22 Sam Technology, Inc. Non-invasive human neurocognitive performance capability testing method and system
US6054991A (en) * 1991-12-02 2000-04-25 Texas Instruments Incorporated Method of modeling player position and movement in a virtual reality system
CA2101633A1 (en) 1991-12-03 1993-06-04 Barry J. French Interactive video testing and training system
US5875108A (en) * 1991-12-23 1999-02-23 Hoffberg; Steven M. Ergonomic man-machine interface incorporating adaptive pattern recognition based control system
JPH07325934A (en) 1992-07-10 1995-12-12 Walt Disney Co:The Method and equipment for provision of graphics enhanced to virtual world
US5999908A (en) 1992-08-06 1999-12-07 Abelow; Daniel H. Customer-based product design module
US5320538A (en) * 1992-09-23 1994-06-14 Hughes Training, Inc. Interactive aircraft training system and method
IT1257294B (en) * 1992-11-20 1996-01-12 DEVICE SUITABLE TO DETECT THE CONFIGURATION OF A PHYSIOLOGICAL-DISTAL UNIT, TO BE USED IN PARTICULAR AS AN ADVANCED INTERFACE FOR MACHINES AND CALCULATORS.
US5495576A (en) * 1993-01-11 1996-02-27 Ritchey; Kurtis J. Panoramic image based virtual reality/telepresence audio-visual system and method
US5690582A (en) * 1993-02-02 1997-11-25 Tectrix Fitness Equipment, Inc. Interactive exercise apparatus
JP2799126B2 (en) * 1993-03-26 1998-09-17 株式会社ナムコ Video game device and game input device
US5405152A (en) * 1993-06-08 1995-04-11 The Walt Disney Company Method and apparatus for an interactive video game with physical feedback
US5454043A (en) * 1993-07-30 1995-09-26 Mitsubishi Electric Research Laboratories, Inc. Dynamic and static hand gesture recognition through low-level image analysis
US5423554A (en) * 1993-09-24 1995-06-13 Metamedia Ventures, Inc. Virtual reality game method and apparatus
US5980256A (en) * 1993-10-29 1999-11-09 Carmein; David E. E. Virtual reality system with enhanced sensory apparatus
JP3419050B2 (en) * 1993-11-19 2003-06-23 株式会社日立製作所 Input device
US5347306A (en) * 1993-12-17 1994-09-13 Mitsubishi Electric Research Laboratories, Inc. Animated electronic meeting place
JP2552427B2 (en) * 1993-12-28 1996-11-13 コナミ株式会社 Tv play system
US5577981A (en) * 1994-01-19 1996-11-26 Jarvik; Robert Virtual reality exercise machine and computer controlled video system
US5580249A (en) * 1994-02-14 1996-12-03 Sarcos Group Apparatus for simulating mobility of a human
US5597309A (en) * 1994-03-28 1997-01-28 Riess; Thomas Method and apparatus for treatment of gait problems associated with parkinson's disease
US5385519A (en) * 1994-04-19 1995-01-31 Hsu; Chi-Hsueh Running machine
US5524637A (en) * 1994-06-29 1996-06-11 Erickson; Jon W. Interactive system for measuring physiological exertion
JPH0844490A (en) 1994-07-28 1996-02-16 Matsushita Electric Ind Co Ltd Interface device
US5563988A (en) * 1994-08-01 1996-10-08 Massachusetts Institute Of Technology Method and system for facilitating wireless, full-body, real-time user interaction with a digitally represented visual environment
US6714665B1 (en) 1994-09-02 2004-03-30 Sarnoff Corporation Fully automated iris recognition system utilizing wide and narrow fields of view
US5516105A (en) * 1994-10-06 1996-05-14 Exergame, Inc. Acceleration activated joystick
US5638300A (en) * 1994-12-05 1997-06-10 Johnson; Lee E. Golf swing analysis system
JPH08161292A (en) * 1994-12-09 1996-06-21 Matsushita Electric Ind Co Ltd Method and system for detecting congestion degree
US5594469A (en) 1995-02-21 1997-01-14 Mitsubishi Electric Information Technology Center America Inc. Hand gesture machine control system
US5682229A (en) * 1995-04-14 1997-10-28 Schwartz Electro-Optics, Inc. Laser range camera
US5913727A (en) * 1995-06-02 1999-06-22 Ahdoot; Ned Interactive movement and contact simulation game
JP3481631B2 (en) 1995-06-07 2003-12-22 ザ トラスティース オブ コロンビア ユニヴァーシティー イン ザ シティー オブ ニューヨーク Apparatus and method for determining a three-dimensional shape of an object using relative blur in an image due to active illumination and defocus
IL114278A (en) 1995-06-22 2010-06-16 Microsoft Internat Holdings B Camera and method
JP3869005B2 (en) 1995-06-22 2007-01-17 3ディブイ・システムズ・リミテッド Telecentric stereoscopic camera and method
US5682196A (en) * 1995-06-22 1997-10-28 Actv, Inc. Three-dimensional (3D) video presentation system providing interactive 3D presentation with personalized audio responses for multiple viewers
US5702323A (en) * 1995-07-26 1997-12-30 Poulton; Craig K. Electronic exercise enhancer
US6308565B1 (en) 1995-11-06 2001-10-30 Impulse Technology Ltd. System and method for tracking and assessing movement skills in multidimensional space
US6073489A (en) * 1995-11-06 2000-06-13 French; Barry J. Testing and training system for assessing the ability of a player to complete a task
US6098458A (en) 1995-11-06 2000-08-08 Impulse Technology, Ltd. Testing and training system for assessing movement and agility skills without a confining field
US6430997B1 (en) 1995-11-06 2002-08-13 Trazer Technologies, Inc. System and method for tracking and assessing movement skills in multidimensional space
US6176782B1 (en) 1997-12-22 2001-01-23 Philips Electronics North America Corp. Motion-based command generation technology
US5933125A (en) * 1995-11-27 1999-08-03 Cae Electronics, Ltd. Method and apparatus for reducing instability in the display of a virtual environment
US5641288A (en) * 1996-01-11 1997-06-24 Zaenglein, Jr.; William G. Shooting simulating process and training device using a virtual reality display screen
WO1997041925A1 (en) 1996-05-08 1997-11-13 Real Vision Corporation Real time simulation using position sensing
US6173066B1 (en) 1996-05-21 2001-01-09 Cybernet Systems Corporation Pose determination and tracking by matching 3D objects to a 2D sensor
US5982389A (en) * 1996-06-17 1999-11-09 Microsoft Corporation Generating optimized motion transitions for computer animated objects
US5989157A (en) * 1996-08-06 1999-11-23 Walton; Charles A. Exercising system with electronic inertial game playing
AU3954997A (en) * 1996-08-14 1998-03-06 Nurakhmed Nurislamovich Latypov Method for following and imaging a subject's three-dimensional position and orientation, method for presenting a virtual space to a subject, and systems for implementing said methods
JP3064928B2 (en) * 1996-09-20 2000-07-12 日本電気株式会社 Subject extraction method
EP0849697B1 (en) 1996-12-20 2003-02-12 Hitachi Europe Limited A hand gesture recognition system and method
US6009210A (en) * 1997-03-05 1999-12-28 Digital Equipment Corporation Hands-free interface to a virtual reality environment using head tracking
JP3862348B2 (en) 1997-03-19 2006-12-27 東京電力株式会社 Motion capture system
US6100896A (en) * 1997-03-24 2000-08-08 Mitsubishi Electric Information Technology Center America, Inc. System for designing graphical multi-participant environments
US5877803A (en) * 1997-04-07 1999-03-02 Tritech Mircoelectronics International, Ltd. 3-D image detector
US6215898B1 (en) 1997-04-15 2001-04-10 Interval Research Corporation Data processing system and method
JP3077745B2 (en) 1997-07-31 2000-08-14 日本電気株式会社 Data processing method and apparatus, information storage medium
US6188777B1 (en) 1997-08-01 2001-02-13 Interval Research Corporation Method and apparatus for personnel detection and tracking
US6289112B1 (en) 1997-08-22 2001-09-11 International Business Machines Corporation System and method for determining block direction in fingerprint images
US6720949B1 (en) 1997-08-22 2004-04-13 Timothy R. Pryor Man machine interfaces and applications
AUPO894497A0 (en) 1997-09-02 1997-09-25 Xenotech Research Pty Ltd Image processing method and apparatus
JP2001517782A (en) 1997-09-24 2001-10-09 スリーディーヴィー システムズ リミテッド Acoustic imaging system
EP0905644A3 (en) 1997-09-26 2004-02-25 Matsushita Electric Industrial Co., Ltd. Hand gesture recognizing device
US6141463A (en) 1997-10-10 2000-10-31 Electric Planet Interactive Method and system for estimating jointed-figure configurations
US6101289A (en) 1997-10-15 2000-08-08 Electric Planet, Inc. Method and apparatus for unencumbered capture of an object
AU1099899A (en) 1997-10-15 1999-05-03 Electric Planet, Inc. Method and apparatus for performing a clean background subtraction
US6072494A (en) * 1997-10-15 2000-06-06 Electric Planet, Inc. Method and apparatus for real-time gesture recognition
US6130677A (en) 1997-10-15 2000-10-10 Electric Planet, Inc. Interactive computer vision system
WO1999019840A1 (en) 1997-10-15 1999-04-22 Electric Planet, Inc. A system and method for generating an animatable character
US6181343B1 (en) 1997-12-23 2001-01-30 Philips Electronics North America Corp. System and method for permitting three-dimensional navigation through a virtual reality environment using camera-based gesture inputs
EP1059970A2 (en) 1998-03-03 2000-12-20 Arena, Inc, System and method for tracking and assessing movement skills in multidimensional space
US6159100A (en) 1998-04-23 2000-12-12 Smith; Michael D. Virtual reality game
US6077201A (en) * 1998-06-12 2000-06-20 Cheng; Chau-Yang Exercise bicycle
US20010008561A1 (en) 1999-08-10 2001-07-19 Paul George V. Real-time object tracking system
US6801637B2 (en) 1999-08-10 2004-10-05 Cybernet Systems Corporation Optical body tracker
US7121946B2 (en) 1998-08-10 2006-10-17 Cybernet Systems Corporation Real-time head tracking system for computer games and other applications
US6950534B2 (en) 1998-08-10 2005-09-27 Cybernet Systems Corporation Gesture-controlled interfaces for self-service machines and other applications
US6681031B2 (en) 1998-08-10 2004-01-20 Cybernet Systems Corporation Gesture-controlled interfaces for self-service machines and other applications
US7036094B1 (en) 1998-08-10 2006-04-25 Cybernet Systems Corporation Behavior recognition system
IL126284A (en) 1998-09-17 2002-12-01 Netmor Ltd System and method for three dimensional positioning and tracking
EP0991011B1 (en) 1998-09-28 2007-07-25 Matsushita Electric Industrial Co., Ltd. Method and device for segmenting hand gestures
US6501515B1 (en) 1998-10-13 2002-12-31 Sony Corporation Remote control system
AU1930700A (en) 1998-12-04 2000-06-26 Interval Research Corporation Background estimation and segmentation based on range and color
US6147678A (en) 1998-12-09 2000-11-14 Lucent Technologies Inc. Video hand image-three-dimensional computer interface with multiple degrees of freedom
AU1574899A (en) 1998-12-16 2000-07-03 3Dv Systems Ltd. Self gating photosurface
US6570555B1 (en) 1998-12-30 2003-05-27 Fuji Xerox Co., Ltd. Method and apparatus for embodied conversational characters with multimodal input/output in an interface device
US6363160B1 (en) 1999-01-22 2002-03-26 Intel Corporation Interface using pattern recognition and tracking
US7003134B1 (en) 1999-03-08 2006-02-21 Vulcan Patents Llc Three dimensional object pose estimation which employs dense depth information
US6299308B1 (en) 1999-04-02 2001-10-09 Cybernet Systems Corporation Low-cost non-imaging eye tracker system for computer control
US6614422B1 (en) 1999-11-04 2003-09-02 Canesta, Inc. Method and apparatus for entering data using a virtual input device
US6503195B1 (en) 1999-05-24 2003-01-07 University Of North Carolina At Chapel Hill Methods and systems for real-time structured light depth extraction and endoscope using real-time structured light depth extraction
US6476834B1 (en) 1999-05-28 2002-11-05 International Business Machines Corporation Dynamic creation of selectable items on surfaces
US6873723B1 (en) 1999-06-30 2005-03-29 Intel Corporation Segmenting three-dimensional video images using stereo
US6738066B1 (en) 1999-07-30 2004-05-18 Electric Plant, Inc. System, method and article of manufacture for detecting collisions between video images generated by a camera and an object depicted on a display
US7113918B1 (en) 1999-08-01 2006-09-26 Electric Planet, Inc. Method for video enabled electronic commerce
US7050606B2 (en) 1999-08-10 2006-05-23 Cybernet Systems Corporation Tracking and gesture recognition system particularly suited to vehicular control applications
US7224384B1 (en) 1999-09-08 2007-05-29 3Dv Systems Ltd. 3D imaging system
US6512838B1 (en) * 1999-09-22 2003-01-28 Canesta, Inc. Methods for enhancing performance and data acquired from three-dimensional image systems
US7050177B2 (en) 2002-05-22 2006-05-23 Canesta, Inc. Method and apparatus for approximating depth of an object's placement onto a monitored region with applications to virtual interface devices
US20030132950A1 (en) 2001-11-27 2003-07-17 Fahri Surucu Detecting, classifying, and interpreting input events based on stimuli in multiple sensory domains
US7006236B2 (en) 2002-05-22 2006-02-28 Canesta, Inc. Method and apparatus for approximating depth of an object's placement onto a monitored region with applications to virtual interface devices
US6690618B2 (en) 2001-04-03 2004-02-10 Canesta, Inc. Method and apparatus for approximating a source position of a sound-causing event for determining an input used in operating an electronic device
DE19960180B4 (en) 1999-12-14 2006-03-09 Rheinmetall W & M Gmbh Method for producing an explosive projectile
US6674877B1 (en) * 2000-02-03 2004-01-06 Microsoft Corporation System and method for visually tracking occluded objects in real time
US6663491B2 (en) * 2000-02-18 2003-12-16 Namco Ltd. Game apparatus, storage medium and computer program that adjust tempo of sound
US6633294B1 (en) 2000-03-09 2003-10-14 Seth Rosenthal Method and apparatus for using captured high density motion for animation
SE0000850D0 (en) 2000-03-13 2000-03-13 Pink Solution Ab Recognition arrangement
EP1152261A1 (en) 2000-04-28 2001-11-07 CSEM Centre Suisse d'Electronique et de Microtechnique SA Device and method for spatially resolved photodetection and demodulation of modulated electromagnetic waves
US6640202B1 (en) 2000-05-25 2003-10-28 International Business Machines Corporation Elastic sensor mesh system for 3-dimensional measurement, mapping and kinematics applications
US6731799B1 (en) 2000-06-01 2004-05-04 University Of Washington Object segmentation with background extraction and moving boundary techniques
US6788809B1 (en) 2000-06-30 2004-09-07 Intel Corporation System and method for gesture recognition in three dimensions using stereo imaging and color vision
US7227526B2 (en) 2000-07-24 2007-06-05 Gesturetek, Inc. Video-based image control system
US7058204B2 (en) 2000-10-03 2006-06-06 Gesturetek, Inc. Multiple camera control system
JP3725460B2 (en) 2000-10-06 2005-12-14 株式会社ソニー・コンピュータエンタテインメント Image processing apparatus, image processing method, recording medium, computer program, semiconductor device
US7039676B1 (en) 2000-10-31 2006-05-02 International Business Machines Corporation Using video image analysis to automatically transmit gestures over a network in a chat or instant messaging session
RU2201618C2 (en) 2001-03-23 2003-03-27 Супрун Антон Евгеньевич Method for entering information onto microterminal residing in users hand, in particular radiophone receiver, pager, organizer
US6539931B2 (en) * 2001-04-16 2003-04-01 Koninklijke Philips Electronics N.V. Ball throwing assistant
US7259747B2 (en) 2001-06-05 2007-08-21 Reactrix Systems, Inc. Interactive video display system
US8035612B2 (en) 2002-05-28 2011-10-11 Intellectual Ventures Holding 67 Llc Self-contained interactive video display system
AU2002315456A1 (en) 2001-06-22 2003-01-08 Canesta, Inc. Method and system to display a virtual input device
JP3420221B2 (en) 2001-06-29 2003-06-23 株式会社コナミコンピュータエンタテインメント東京 GAME DEVICE AND PROGRAM
US6937742B2 (en) 2001-09-28 2005-08-30 Bellsouth Intellectual Property Corporation Gesture activated home appliance
AU2002362085A1 (en) 2001-12-07 2003-07-09 Canesta Inc. User interface for electronic devices
WO2003071410A2 (en) 2002-02-15 2003-08-28 Canesta, Inc. Gesture recognition system using depth perceptive sensors
AU2003219926A1 (en) 2002-02-26 2003-09-09 Canesta, Inc. Method and apparatus for recognizing objects
JP3932942B2 (en) 2002-03-25 2007-06-20 ソニー株式会社 Text input method and apparatus, and text input program
US7310431B2 (en) 2002-04-10 2007-12-18 Canesta, Inc. Optical methods for remotely measuring objects
DE50302813D1 (en) 2002-04-19 2006-05-18 Iee Sarl SAFETY DEVICE FOR A VEHICLE
US7710391B2 (en) 2002-05-28 2010-05-04 Matthew Bell Processing an image utilizing a spatially varying pattern
US7348963B2 (en) 2002-05-28 2008-03-25 Reactrix Systems, Inc. Interactive video display system
US7170492B2 (en) 2002-05-28 2007-01-30 Reactrix Systems, Inc. Interactive video display system
US7489812B2 (en) 2002-06-07 2009-02-10 Dynamic Digital Depth Research Pty Ltd. Conversion and encoding techniques
US7883415B2 (en) 2003-09-15 2011-02-08 Sony Computer Entertainment Inc. Method and apparatus for adjusting a view of a scene being displayed according to tracked head motion
US7623115B2 (en) 2002-07-27 2009-11-24 Sony Computer Entertainment Inc. Method and apparatus for light input device
US7646372B2 (en) 2003-09-15 2010-01-12 Sony Computer Entertainment Inc. Methods and systems for enabling direction detection when interfacing with a computer program
US7151530B2 (en) 2002-08-20 2006-12-19 Canesta, Inc. System and method for determining an input selected by a user through a virtual interface
US7576727B2 (en) 2002-12-13 2009-08-18 Matthew Bell Interactive directed light/sound system
JP4235729B2 (en) 2003-02-03 2009-03-11 国立大学法人静岡大学 Distance image sensor
US8745541B2 (en) * 2003-03-25 2014-06-03 Microsoft Corporation Architecture for controlling a computer using hand gestures
US7886236B2 (en) 2003-03-28 2011-02-08 Microsoft Corporation Dynamic feedback for gestures
EP1477924B1 (en) 2003-03-31 2007-05-02 HONDA MOTOR CO., Ltd. Gesture recognition apparatus, method and program
GB0311177D0 (en) 2003-05-15 2003-06-18 Qinetiq Ltd Non contact human-computer interface
WO2004107266A1 (en) * 2003-05-29 2004-12-09 Honda Motor Co., Ltd. Visual tracking using depth data
US8072470B2 (en) 2003-05-29 2011-12-06 Sony Computer Entertainment Inc. System and method for providing a real-time three-dimensional interactive environment
WO2004111687A2 (en) 2003-06-12 2004-12-23 Honda Motor Co., Ltd. Target orientation estimation using depth sensing
US7874917B2 (en) 2003-09-15 2011-01-25 Sony Computer Entertainment Inc. Methods and systems for enabling depth and direction detection when interfacing with a computer program
US7536032B2 (en) 2003-10-24 2009-05-19 Reactrix Systems, Inc. Method and system for processing captured image information in an interactive video display system
KR20050065198A (en) 2003-12-24 2005-06-29 한국전자통신연구원 Three-dimensional motion command recognizer using motion of user
JP3847753B2 (en) 2004-01-30 2006-11-22 株式会社ソニー・コンピュータエンタテインメント Image processing apparatus, image processing method, recording medium, computer program, semiconductor device
FI117308B (en) * 2004-02-06 2006-08-31 Nokia Corp gesture Control
EP1743277A4 (en) 2004-04-15 2011-07-06 Gesturetek Inc Tracking bimanual movements
US7308112B2 (en) * 2004-05-14 2007-12-11 Honda Motor Co., Ltd. Sign based human-machine interaction
US7519223B2 (en) 2004-06-28 2009-04-14 Microsoft Corporation Recognizing gestures and using gestures for interacting with software applications
US7704135B2 (en) 2004-08-23 2010-04-27 Harrison Jr Shelton E Integrated game system, method, and device
US7991220B2 (en) 2004-09-01 2011-08-02 Sony Computer Entertainment Inc. Augmented reality game system using identification information to display a virtual object in association with a position of a real object
US7319385B2 (en) * 2004-09-17 2008-01-15 Nokia Corporation Sensor data sharing
EP1645944B1 (en) 2004-10-05 2012-08-15 Sony France S.A. A content-management interface
JP4449723B2 (en) 2004-12-08 2010-04-14 ソニー株式会社 Image processing apparatus, image processing method, and program
KR20060070280A (en) 2004-12-20 2006-06-23 한국전자통신연구원 Apparatus and its method of user interface using hand gesture recognition
EP1849123A2 (en) 2005-01-07 2007-10-31 GestureTek, Inc. Optical flow based tilt sensor
US7430312B2 (en) 2005-01-07 2008-09-30 Gesturetek, Inc. Creating 3D images of objects by illuminating with infrared patterns
ES2791718T3 (en) 2005-01-07 2020-11-05 Qualcomm Inc Detection and tracking of objects in images
CN1306367C (en) 2005-02-06 2007-03-21 赖银樑 Multifunctional man-machine interactive sports equipment
WO2006086508A2 (en) 2005-02-08 2006-08-17 Oblong Industries, Inc. System and method for genture based control system
US8009871B2 (en) 2005-02-08 2011-08-30 Microsoft Corporation Method and system to segment depth images and to detect shapes in three-dimensionally acquired data
KR100688743B1 (en) 2005-03-11 2007-03-02 삼성전기주식회사 Manufacturing method of PCB having multilayer embedded passive-chips
WO2006099597A2 (en) * 2005-03-17 2006-09-21 Honda Motor Co., Ltd. Pose estimation based on critical point analysis
WO2006124935A2 (en) 2005-05-17 2006-11-23 Gesturetek, Inc. Orientation-sensitive signal output
DE602005010696D1 (en) 2005-08-12 2008-12-11 Mesa Imaging Ag Highly sensitive, fast pixel for use in an image sensor
US20080026838A1 (en) 2005-08-22 2008-01-31 Dunstan James E Multi-player non-role-playing virtual world games: method for two-way interaction between participants and multi-player virtual world games
US7450736B2 (en) 2005-10-28 2008-11-11 Honda Motor Co., Ltd. Monocular tracking of 3D human motion with a coordinated mixture of factor analyzers
GB2431717A (en) 2005-10-31 2007-05-02 Sony Uk Ltd Scene analysis
US8094928B2 (en) * 2005-11-14 2012-01-10 Microsoft Corporation Stereo video for gaming
US20070117628A1 (en) * 2005-11-19 2007-05-24 Stanley Mark J Method and apparatus for providing realistic gun motion input to a video game
US20070130547A1 (en) * 2005-12-01 2007-06-07 Navisense, Llc Method and system for touchless user interface control
US20070159468A1 (en) * 2006-01-10 2007-07-12 Saxby Don T Touchpad control of character actions in a virtual environment using gestures
US7667686B2 (en) * 2006-02-01 2010-02-23 Memsic, Inc. Air-writing and motion sensing input for portable devices
EP1999547A4 (en) 2006-02-16 2011-10-12 Ftk Technologies Ltd A system and method of inputting data into a computing system
US7433024B2 (en) 2006-02-27 2008-10-07 Prime Sense Ltd. Range mapping using speckle decorrelation
US8146018B2 (en) * 2006-04-28 2012-03-27 Nintendo Co., Ltd. Gesture-based control of multiple game characters and other animated objects
US8601379B2 (en) 2006-05-07 2013-12-03 Sony Computer Entertainment Inc. Methods for interactive communications with real time effects and avatar environment interaction
US7721207B2 (en) 2006-05-31 2010-05-18 Sony Ericsson Mobile Communications Ab Camera based control
JP4848515B2 (en) 2006-06-12 2011-12-28 国立大学法人九州工業大学 Avatar motion control system, program and method thereof
US8169421B2 (en) * 2006-06-19 2012-05-01 Cypress Semiconductor Corporation Apparatus and method for detecting a touch-sensor pad gesture
US20080040692A1 (en) * 2006-06-29 2008-02-14 Microsoft Corporation Gesture input
US9696808B2 (en) * 2006-07-13 2017-07-04 Northrop Grumman Systems Corporation Hand-gesture recognition method
US7701439B2 (en) * 2006-07-13 2010-04-20 Northrop Grumman Corporation Gesture recognition simulation system and method
US8395658B2 (en) 2006-09-07 2013-03-12 Sony Computer Entertainment Inc. Touch screen-like user interface that does not require actual touching
JP5395323B2 (en) 2006-09-29 2014-01-22 ブレインビジョン株式会社 Solid-state image sensor
JP2010507163A (en) 2006-10-18 2010-03-04 コーニンクレッカ フィリップス エレクトロニクス エヌ ヴィ Electronic system control using surface interaction
US20080134102A1 (en) 2006-12-05 2008-06-05 Sony Ericsson Mobile Communications Ab Method and system for detecting movement of an object
US8351646B2 (en) * 2006-12-21 2013-01-08 Honda Motor Co., Ltd. Human pose estimation and tracking using label assignment
US7412077B2 (en) 2006-12-29 2008-08-12 Motorola, Inc. Apparatus and methods for head pose estimation and head gesture detection
US20090262074A1 (en) * 2007-01-05 2009-10-22 Invensense Inc. Controlling and accessing content using motion processing on mobile devices
GB0703974D0 (en) 2007-03-01 2007-04-11 Sony Comp Entertainment Europe Entertainment device
US7729530B2 (en) 2007-03-03 2010-06-01 Sergey Antonov Method and apparatus for 3-D data input to a personal computer with a multimedia oriented operating system
US7852262B2 (en) 2007-08-16 2010-12-14 Cybernet Systems Corporation Wireless mobile indoor/outdoor tracking system
WO2009059065A1 (en) 2007-10-30 2009-05-07 Hewlett-Packard Development Company, L.P. Interactive display system with collaborative gesture detection
US20090221368A1 (en) * 2007-11-28 2009-09-03 Ailive Inc., Method and system for creating a shared game space for a networked game
GB2455316B (en) * 2007-12-04 2012-08-15 Sony Corp Image processing apparatus and method
US8149210B2 (en) 2007-12-31 2012-04-03 Microsoft International Holdings B.V. Pointing device and method
TW200937254A (en) * 2008-02-29 2009-09-01 Inventec Appliances Corp A method for inputting control commands and a handheld device thereof
US9772689B2 (en) * 2008-03-04 2017-09-26 Qualcomm Incorporated Enhanced gesture-based image manipulation
CN201254344Y (en) 2008-08-20 2009-06-10 中国农业科学院草原研究所 Plant specimens and seed storage
US8499251B2 (en) 2009-01-07 2013-07-30 Microsoft Corporation Virtual page turn
JP2014021864A (en) 2012-07-20 2014-02-03 Mizuho Information & Research Institute Inc Input support program and input support device

Patent Citations (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP1408443A1 (en) 2002-10-07 2004-04-14 Sony France S.A. Method and apparatus for analysing gestures produced by a human, e.g. for commanding apparatus by gesture recognition
US20080270896A1 (en) 2007-04-27 2008-10-30 Per Ola Kristensson System and method for preview and selection of words

Cited By (12)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR20120016720A (en) * 2010-08-17 2012-02-27 엘지전자 주식회사 Display apparatus and controlling method thereof
KR101676881B1 (en) 2010-08-17 2016-11-16 엘지전자 주식회사 Display apparatus and controlling method thereof
JP2014501415A (en) * 2011-01-05 2014-01-20 ソフトキネティック ソフトウェア User interface method and system based on natural gestures
JP2014225288A (en) * 2011-01-05 2014-12-04 ソフトキネティック ソフトウェア User interface method and system based on natural gesture
US9081419B2 (en) 2011-01-05 2015-07-14 Softkinetic Software Natural gesture based user interface methods and systems
US9398243B2 (en) 2011-01-06 2016-07-19 Samsung Electronics Co., Ltd. Display apparatus controlled by motion and motion control method thereof
US9513711B2 (en) 2011-01-06 2016-12-06 Samsung Electronics Co., Ltd. Electronic device controlled by a motion and controlling method thereof using different motions to activate voice versus motion recognition
KR101795574B1 (en) * 2011-01-06 2017-11-13 삼성전자주식회사 Electronic device controled by a motion, and control method thereof
JP2013037675A (en) * 2011-06-23 2013-02-21 Omek Interactive Ltd System and method for close-range movement tracking
US11048333B2 (en) 2011-06-23 2021-06-29 Intel Corporation System and method for close-range movement tracking
WO2014126509A1 (en) * 2013-02-12 2014-08-21 Permyakov Aleksandr Mihailovich Soccer game simulation for the game-based training of soccer players
EP3165413A1 (en) * 2015-11-05 2017-05-10 Aisin Seiki Kabushiki Kaisha Operation input detection device and control device for vehicular opening-closing body

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