US20040140994A1 - Method for objects segmentation in video sequences by object tracking and user assistance - Google Patents
Method for objects segmentation in video sequences by object tracking and user assistance Download PDFInfo
- Publication number
- US20040140994A1 US20040140994A1 US10/734,542 US73454203A US2004140994A1 US 20040140994 A1 US20040140994 A1 US 20040140994A1 US 73454203 A US73454203 A US 73454203A US 2004140994 A1 US2004140994 A1 US 2004140994A1
- Authority
- US
- United States
- Prior art keywords
- video
- segmented
- frame
- segmentation
- primarily
- Prior art date
- Legal status (The legal status 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 status listed.)
- Abandoned
Links
Images
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
- H04N19/162—User input
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/12—Edge-based segmentation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/10—Segmentation; Edge detection
- G06T7/174—Segmentation; Edge detection involving the use of two or more images
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
- G06T7/215—Motion-based segmentation
-
- G—PHYSICS
- G11—INFORMATION STORAGE
- G11B—INFORMATION STORAGE BASED ON RELATIVE MOVEMENT BETWEEN RECORD CARRIER AND TRANSDUCER
- G11B27/00—Editing; Indexing; Addressing; Timing or synchronising; Monitoring; Measuring tape travel
- G11B27/10—Indexing; Addressing; Timing or synchronising; Measuring tape travel
- G11B27/19—Indexing; Addressing; Timing or synchronising; Measuring tape travel by using information detectable on the record carrier
- G11B27/28—Indexing; Addressing; Timing or synchronising; Measuring tape travel by using information detectable on the record carrier by using information signals recorded by the same method as the main recording
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
- H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/20—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using video object coding
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2200/00—Indexing scheme for image data processing or generation, in general
- G06T2200/16—Indexing scheme for image data processing or generation, in general involving adaptation to the client's capabilities
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2200/00—Indexing scheme for image data processing or generation, in general
- G06T2200/24—Indexing scheme for image data processing or generation, in general involving graphical user interfaces [GUIs]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10016—Video; Image sequence
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
- G06T2207/20092—Interactive image processing based on input by user
- G06T2207/20104—Interactive definition of region of interest [ROI]
Definitions
- the present invention relates to a video object segmentation method for correctly segmenting a video into a plurality of video objects by a user's assistance and an object tracking, when a video object-oriented manipulation, an editing, an object-based user interaction, an object-based video coding and the like are performed in an apparatus such as a video editing, creating and compositing apparatus, and an object-based video codec (or encoder/decoder).
- an apparatus such as a video editing, creating and compositing apparatus, and an object-based video codec (or encoder/decoder).
- objects in image are automatically segmented based on the determination whether the brightness values of consecutive images are different or not, or are manipulatively segmented for every frame by user using an editing tool.
- the automatic segmentation method causes the problem in that the segmentation capability is varied in accordance with the threshold value on which it is determined that the brightness value between the consecutive images is changed, and the manipulative segmentation method has the problem in that it takes a considerably long time because the segmentation of every frame requires the user's direct manipulation work, thus it endows the user with the economical burden.
- the objective of the present invention is to provide a video object segmentation method for correctly segmenting a video object, in which the video objects to be firstly appeared in an image sequence are segmented in manual or in semi-manual, and then the following video frames are automatically segmented by an object-tracking based on the moving of the primarily segmented video object, for the sake of detecting an object from an image in a video system.
- a video object segmentation method applicable to a video system comprising the steps of: primarily segmenting an object existing in a frame of video sequence manually or semi-manually; and secondly segmenting the object within a video sequence including the primarily segmented object automatically.
- the video object segmentation method further includes the steps of: determining whether any scene change is made between consecutive frames or any new object other than the primarily segmented object appears within the frame being automatically segmented, when repeatedly performing the step of secondly segmenting for consecutive frames; and repeating the step of primarily segmenting, if the answer of the step of determining is positive.
- This method also includes the steps of examining the quality of automatically segmented results,; repeating the step of secondly segmenting, if the quality of automatically segmented results is satisfactory; and repeating the step of primarily segmenting, if the quality of automatically segmented results is not satisfactory.
- the step of primarily segmenting can be made by segmenting the object within the image in completely manual using an user interface tool, or by segmenting the object within the image in semi-manual, such that, if the user designates manually a rough boundary line of the object within the image, then the object within the image is automatically segmented based on the designation-related information and an image segmentation information.
- the step of secondly segmenting can be made by tracking the object region to which in the current frame the primarily segmented video object in the previous frame is moved, so as to segment the object within the frame of the consecutive frames.
- FIGS. 1 a and 1 b are diagrams of an exemplary video codec to which the method of the present invention may be applied.
- FIG. 2 is a flowchart for illustrating a preferred embodiment of a video object segmentation method according to the present invention.
- FIGS. 1 a and 1 b are exemplary diagrams of a video codec to which the method of the present invention can be applied.
- the video encoding part to which the method of this invention is applied includes a video object segmentation unit 101 for segmentation an externally input video sequences into video objects, a plurality of video object encoding units 102 for video-object-oriented coding the video objects inputted from the video object segmentation unit 101 according to the MPEG-4 (Moving Picture Expert Group-4) video coding algorithm so as for reducing the video object data, and a multiplexing unit 103 for multiplexing the reduced video object data inputted from the plurality of video object coding unit 102 according to the MPEG-4 multiplexing standard and then transmitting/storing the multiplexed bit stream.
- MPEG-4 Motion Picture Expert Group-4
- the video decoding part to which the method of this invention is applied includes a de-multiplexing unit 104 for de-multiplexing the transmitted/reproduced bit stream data, a plurality of video object decoding unit 105 for decoding the de-multiplexed video objects inputted from the de-multiplexing unit 104 , a picture compositing unit 106 for reconstructing a picture based on the decoded video objects inputted from the plurality of video object decoding unit 105 , and a display unit 107 for displaying the reconstructed picture of the picture compositing unit 106 to the display unit.
- a de-multiplexing unit 104 for de-multiplexing the transmitted/reproduced bit stream data
- a plurality of video object decoding unit 105 for decoding the de-multiplexed video objects inputted from the de-multiplexing unit 104
- a picture compositing unit 106 for reconstructing a picture based on the decoded video objects inputted from the plurality of video object decoding unit 105
- FIG. 2 is a flowchart of a video object segmentation method according to one embodiment of the present invention.
- the video objects appeared in the first frame of the video sequence or the newly appeared video objects in the consecutive frames are manually segmented by user or semi-manually segmented by user's manipulation based on the spatial information such as luminance, color or the like (see step 201 ).
- the user segments in manual the video objects shown in the first frame or the newly appeared video objects in the consecutive frames by using a simple user interface tool such as a mouse, or segments semi-manually them by user's manipulation based on spatial information. More specifically, if the user simply designates in manual a rough boundary line of the object within the frame, then the object within the frame is automatically segmented based on the designation-related information and an image segmentation information.
- the video object is defined and segmented by the user's manipulation. if it is one of the first frame of the video sequence, the frame on which the new object is revealed, or the frame on which a scene change is made from the previous frame,
- the video object is automatically segmented by performing object-tracking based on the moving of the video object which has been defined and segmented in the previous frame (step 202 ).
- an estimation is made for the object region to which the video object having been segmented in the previous frame is moved and the video object on the previous segmented mask is projected into the segmented mask of the present frame in accordance with the moved amount.
- an error and noise of the segmentation mask generated due to the projection is compensated and corrected, and then the pixel having an segmentation labeling uncertain due to the projection, for the segmentation mask, is segmented into an uncertain area.
- the spatial information such as the luminance and color information of the current frame
- the pixel of the uncertain area is segmented into the nearest video object.
- a median filter is used for the segmentation mask having been last segmented. This is for the sake that the outline of the video object is streamlined so as to give a visually good effect.
- step 203 it is analyzed whether a scene change is made or a newly appeared video object is in the next frame. That is, before segmentation of the video object, it is detected whether a scene change occurs in the consecutive frames or any newly appeared video object other than the segmented video objects exists.
- the objects which are newly appeared or exist in the changed scene are segmented by manually or semi-manually by user's assistance (step 201 ).
- step 204 it is determined whether the automatic segmentation result by object-tracking for the previous frame is satisfactory. This is that, since the segmentation by object-tracking is performed using the video object segmented in previous frame, the erroneous segmentation for the previous result cumulatively affects the following segmentation by object-tracking to become incorrect.
- the satisfaction examination for the segmentation result can be manually performed based on the user's determination or can be automatically performed.
- step 201 the segmentation process by user's assistance. Otherwise, in step 202 the segmentation process by object-tracking for the next frame is performed.
- the video object segmentation method segments the video object from the video sequences using various information such as a user's assistance, spatial information, temporal information of object-tracking and the like, so as to reduce the time required for segmentation and the user's endeavor and improve the correctness of the automatic video object segmentation.
- the desired object can be effectively segmented from the video sequences using an user's assistance, spatial information, temporal information related to object-tracking or the like.
- the video object intractable to be defined or segmented is manually or semi-manually segmented by user's assistance, and thus-segmented video object is automatically segmented by object-tracking.
- the effective combination of the automatic segmentation and the manual segmentation methods makes it possibly that the video objects are correctly segmented and the user's endeavor and time can be reduced.
- the method of the present invention has an effect that it can be applied to a video editing, creating and compositing apparatus, an object-based video codec or the like.
Abstract
A video object segmentation method is disclosed in the present invention. This video object segmentation method is for correctly segmenting video objects. In the video object segmentation method, the video objects to be firstly appeared in a video sequence are segmented in manual or semi-manual, and then the consecutive video frames is automatically segmented by an object-tracking based on the moving of the primarily segmented video object. In other words, the video object segmentation method applicable to a video system, comprises a first step of primarily segmenting objects existing in a frame of video sequence manually or semi-manually; and a second step of automatically segmenting the objects within the consecutive frames. This video object segmentation method can be adapted to a video system.
Description
- This application is a continuation of U.S. patent application Ser. No. 09/701,822 filed Jan. 26, 2001
- The present invention relates to a video object segmentation method for correctly segmenting a video into a plurality of video objects by a user's assistance and an object tracking, when a video object-oriented manipulation, an editing, an object-based user interaction, an object-based video coding and the like are performed in an apparatus such as a video editing, creating and compositing apparatus, and an object-based video codec (or encoder/decoder).
- According to conventional video object segmentation methods, objects in image are automatically segmented based on the determination whether the brightness values of consecutive images are different or not, or are manipulatively segmented for every frame by user using an editing tool.
- In the conventional video object segmentation methods, the automatic segmentation method causes the problem in that the segmentation capability is varied in accordance with the threshold value on which it is determined that the brightness value between the consecutive images is changed, and the manipulative segmentation method has the problem in that it takes a considerably long time because the segmentation of every frame requires the user's direct manipulation work, thus it endows the user with the economical burden.
- Accordingly, the present invention is devised for solve the above problems. The objective of the present invention is to provide a video object segmentation method for correctly segmenting a video object, in which the video objects to be firstly appeared in an image sequence are segmented in manual or in semi-manual, and then the following video frames are automatically segmented by an object-tracking based on the moving of the primarily segmented video object, for the sake of detecting an object from an image in a video system.
- To accomplish the objective of the present invention, there is provided a video object segmentation method applicable to a video system, comprising the steps of: primarily segmenting an object existing in a frame of video sequence manually or semi-manually; and secondly segmenting the object within a video sequence including the primarily segmented object automatically.
- In one preferred embodiment of the present invention, the video object segmentation method further includes the steps of: determining whether any scene change is made between consecutive frames or any new object other than the primarily segmented object appears within the frame being automatically segmented, when repeatedly performing the step of secondly segmenting for consecutive frames; and repeating the step of primarily segmenting, if the answer of the step of determining is positive. This method also includes the steps of examining the quality of automatically segmented results,; repeating the step of secondly segmenting, if the quality of automatically segmented results is satisfactory; and repeating the step of primarily segmenting, if the quality of automatically segmented results is not satisfactory.
- In addition, the step of primarily segmenting can be made by segmenting the object within the image in completely manual using an user interface tool, or by segmenting the object within the image in semi-manual, such that, if the user designates manually a rough boundary line of the object within the image, then the object within the image is automatically segmented based on the designation-related information and an image segmentation information. The step of secondly segmenting can be made by tracking the object region to which in the current frame the primarily segmented video object in the previous frame is moved, so as to segment the object within the frame of the consecutive frames.
- For a more complete understanding of the present invention and the advantage thereof, reference is now made to the following description taken in conjunction with the accompanying drawings in which:
- FIGS. 1a and 1 b are diagrams of an exemplary video codec to which the method of the present invention may be applied; and
- FIG. 2 is a flowchart for illustrating a preferred embodiment of a video object segmentation method according to the present invention.
- The preferred embodiment of the present invention will hereinafter be described in detail with reference to the accompanying drawings.
- FIGS. 1a and 1 b are exemplary diagrams of a video codec to which the method of the present invention can be applied.
- Referring to FIG. 1a, the video encoding part to which the method of this invention is applied, includes a video
object segmentation unit 101 for segmentation an externally input video sequences into video objects, a plurality of videoobject encoding units 102 for video-object-oriented coding the video objects inputted from the videoobject segmentation unit 101 according to the MPEG-4 (Moving Picture Expert Group-4) video coding algorithm so as for reducing the video object data, and amultiplexing unit 103 for multiplexing the reduced video object data inputted from the plurality of videoobject coding unit 102 according to the MPEG-4 multiplexing standard and then transmitting/storing the multiplexed bit stream. - Referring to FIG. 1b, the video decoding part to which the method of this invention is applied, includes a de-multiplexing
unit 104 for de-multiplexing the transmitted/reproduced bit stream data, a plurality of videoobject decoding unit 105 for decoding the de-multiplexed video objects inputted from the de-multiplexingunit 104, a picture compositingunit 106 for reconstructing a picture based on the decoded video objects inputted from the plurality of videoobject decoding unit 105, and adisplay unit 107 for displaying the reconstructed picture of the picture compositingunit 106 to the display unit. - FIG. 2 is a flowchart of a video object segmentation method according to one embodiment of the present invention.
- First, when the video intended to be segmented is input, the video objects appeared in the first frame of the video sequence or the newly appeared video objects in the consecutive frames, are manually segmented by user or semi-manually segmented by user's manipulation based on the spatial information such as luminance, color or the like (see step201).
- For example it is impossible that an exact mathematical modeling for the video object on video sequences can be made and the measure for segmenting the video objects can be defined. Thus, the user segments in manual the video objects shown in the first frame or the newly appeared video objects in the consecutive frames by using a simple user interface tool such as a mouse, or segments semi-manually them by user's manipulation based on spatial information. More specifically, if the user simply designates in manual a rough boundary line of the object within the frame, then the object within the frame is automatically segmented based on the designation-related information and an image segmentation information.
- Therefore, the video object is defined and segmented by the user's manipulation. if it is one of the first frame of the video sequence, the frame on which the new object is revealed, or the frame on which a scene change is made from the previous frame,
- Second, the video object is automatically segmented by performing object-tracking based on the moving of the video object which has been defined and segmented in the previous frame (step202).
- For example, an estimation is made for the object region to which the video object having been segmented in the previous frame is moved and the video object on the previous segmented mask is projected into the segmented mask of the present frame in accordance with the moved amount. Here, an error and noise of the segmentation mask generated due to the projection is compensated and corrected, and then the pixel having an segmentation labeling uncertain due to the projection, for the segmentation mask, is segmented into an uncertain area. Then using the spatial information such as the luminance and color information of the current frame, the pixel of the uncertain area is segmented into the nearest video object. Here, a median filter is used for the segmentation mask having been last segmented. This is for the sake that the outline of the video object is streamlined so as to give a visually good effect.
- Next, in
step 203, it is analyzed whether a scene change is made or a newly appeared video object is in the next frame. That is, before segmentation of the video object, it is detected whether a scene change occurs in the consecutive frames or any newly appeared video object other than the segmented video objects exists. - If the result of the analysis shows that any scene change is made or any new object exists in the frame, the objects which are newly appeared or exist in the changed scene are segmented by manually or semi-manually by user's assistance (step201).
- If the result of the analysis shows that there is no scene change and any new object does not exist in the frame, in
step 204 it is determined whether the automatic segmentation result by object-tracking for the previous frame is satisfactory. This is that, since the segmentation by object-tracking is performed using the video object segmented in previous frame, the erroneous segmentation for the previous result cumulatively affects the following segmentation by object-tracking to become incorrect. Here, the satisfaction examination for the segmentation result can be manually performed based on the user's determination or can be automatically performed. - When the segmentation result by object-tracking is “unacceptable”, in
step 201 the segmentation process by user's assistance. Otherwise, instep 202 the segmentation process by object-tracking for the next frame is performed. - According to one preferred embodiment of the present invention, the video object segmentation method segments the video object from the video sequences using various information such as a user's assistance, spatial information, temporal information of object-tracking and the like, so as to reduce the time required for segmentation and the user's endeavor and improve the correctness of the automatic video object segmentation.
- As described above, according to the present invention, the desired object can be effectively segmented from the video sequences using an user's assistance, spatial information, temporal information related to object-tracking or the like. Also the video object intractable to be defined or segmented is manually or semi-manually segmented by user's assistance, and thus-segmented video object is automatically segmented by object-tracking. In other words, the effective combination of the automatic segmentation and the manual segmentation methods makes it possibly that the video objects are correctly segmented and the user's endeavor and time can be reduced. Thus, the method of the present invention has an effect that it can be applied to a video editing, creating and compositing apparatus, an object-based video codec or the like.
- Although preferred embodiments of the present invention has been illustrated and described, various alternatives, modifications and equivalents may be used. Therefore, the foregoing description should not be taken as limiting the scope of the present invention which is defined by the appended claims.
Claims (7)
1. A video object segmentation method applicable to a video system, comprising the steps of:
a) primarily segmenting objects existing in a frame of a video sequence manually or semi-manually; and
b) automatically segmenting the objects within a video sequence including the primarily segmented object.
2. The video object segmentation method in accordance with claim 1 , further comprising the steps of:
c) determining whether any scene change is made between consecutive frames or any new object other than the primarily segmented object appears within the video sequence being automatically segmented, when repeatedly performing the step b) for consecutive frames; and
d) repeatedly performing the first step, if the answer of the step of determining is positive.
3. The video object segmentation method in accordance with claim 2 , further comprising the steps of:
e) examining the quality of automatically segmented results, if there is no scene change between consecutive frames and any new object other than the primarily segmented object does not appear within the video sequence being automatically segmented;
f) performing the second step, if the quality of automatically segmented results is satisfactory; and
g) repeatedly performing the first step, if the quality of automatically segmented results is not satisfactory.
4. The video object segmentation method in accordance with claim 1 , wherein the first step of primarily segmentation is made by segmenting the objects within the frame in completely manual using an user interface tool.
5. The video object segmentation method in accordance with claim 1 , wherein the first step of primarily segmentation is made by segmenting the object within the frame in semi-manual, such that, if the user designates manually a rough boundary line of the object within the frame, then the object within the frame is automatically segmented based on the designation-related information and an image segmentation information.
6. The video object segmentation method in accordance with claim 1 , wherein the second step of automatically segmentation comprises the step of:
tracking the object region in the current frame to which the primarily segmented video object in the previous frame is moved, so as to segment the object within the frame of the consecutive frames.
7. The video object segmentation method in accordance with claim 5 , wherein the image segmentation information is a spatial information including a brightness information and a color information.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US10/734,542 US20040140994A1 (en) | 1998-06-03 | 2003-12-12 | Method for objects segmentation in video sequences by object tracking and user assistance |
Applications Claiming Priority (4)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
KR1998-20687 | 1998-06-03 | ||
KR1019980020687A KR100327103B1 (en) | 1998-06-03 | 1998-06-03 | Method for objects sehmentation in video sequences by object tracking and assistance |
US09/701,822 US6707851B1 (en) | 1998-06-03 | 1998-10-26 | Method for objects segmentation in video sequences by object tracking and user assistance |
US10/734,542 US20040140994A1 (en) | 1998-06-03 | 2003-12-12 | Method for objects segmentation in video sequences by object tracking and user assistance |
Related Parent Applications (2)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US09/701,822 Continuation US6707851B1 (en) | 1998-06-03 | 1998-10-26 | Method for objects segmentation in video sequences by object tracking and user assistance |
PCT/KR1998/000335 Continuation WO1999063750A1 (en) | 1998-06-03 | 1998-10-26 | Method for objects segmentation in video sequences by object tracking and user assistance |
Publications (1)
Publication Number | Publication Date |
---|---|
US20040140994A1 true US20040140994A1 (en) | 2004-07-22 |
Family
ID=19538347
Family Applications (2)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US09/701,822 Expired - Lifetime US6707851B1 (en) | 1998-06-03 | 1998-10-26 | Method for objects segmentation in video sequences by object tracking and user assistance |
US10/734,542 Abandoned US20040140994A1 (en) | 1998-06-03 | 2003-12-12 | Method for objects segmentation in video sequences by object tracking and user assistance |
Family Applications Before (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US09/701,822 Expired - Lifetime US6707851B1 (en) | 1998-06-03 | 1998-10-26 | Method for objects segmentation in video sequences by object tracking and user assistance |
Country Status (5)
Country | Link |
---|---|
US (2) | US6707851B1 (en) |
EP (1) | EP1092317A1 (en) |
JP (1) | JP4302891B2 (en) |
KR (1) | KR100327103B1 (en) |
WO (1) | WO1999063750A1 (en) |
Cited By (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20070124766A1 (en) * | 2005-11-30 | 2007-05-31 | Broadcom Corporation | Video synthesizer |
US20090268808A1 (en) * | 2005-12-28 | 2009-10-29 | Ruijia Li | Novel user sensitive information adaptive video transcoding framework |
US20110096832A1 (en) * | 2009-10-23 | 2011-04-28 | Qualcomm Incorporated | Depth map generation techniques for conversion of 2d video data to 3d video data |
US8873855B2 (en) | 2012-03-08 | 2014-10-28 | Electronics And Telecommunications Research Institute | Apparatus and method for extracting foreground layer in image sequence |
US9990546B2 (en) | 2015-02-04 | 2018-06-05 | Alibaba Group Holding Limited | Method and apparatus for determining target region in video frame for target acquisition |
WO2019051608A1 (en) * | 2017-09-15 | 2019-03-21 | Imagine Communications Corp. | Systems and methods for production of fragmented video content |
US10762722B2 (en) | 2016-06-28 | 2020-09-01 | Nokia Technologies Oy | Apparatus for sharing objects of interest and associated methods |
Families Citing this family (19)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR100327103B1 (en) * | 1998-06-03 | 2002-09-17 | 한국전자통신연구원 | Method for objects sehmentation in video sequences by object tracking and assistance |
US6553069B1 (en) * | 1999-06-17 | 2003-04-22 | Samsung Electronics Co., Ltd. | Digital image segmenting method and device |
US20020174434A1 (en) * | 2001-05-18 | 2002-11-21 | Tsu-Chang Lee | Virtual broadband communication through bundling of a group of circuit switching and packet switching channels |
US20030026338A1 (en) * | 2001-08-03 | 2003-02-06 | Koninklijke Philips Electronics N.V. | Automated mask selection in object-based video encoding |
US20060268181A1 (en) * | 2003-02-21 | 2006-11-30 | Koninklijke Philips Electronics N.V. Groenewoudseweg 1 | Shot-cut detection |
KR100601933B1 (en) * | 2003-11-18 | 2006-07-14 | 삼성전자주식회사 | Method and apparatus of human detection and privacy protection method and system employing the same |
JP4241709B2 (en) * | 2005-10-11 | 2009-03-18 | ソニー株式会社 | Image processing device |
US8098885B2 (en) * | 2005-11-02 | 2012-01-17 | Microsoft Corporation | Robust online face tracking |
US8027513B2 (en) | 2007-03-23 | 2011-09-27 | Technion Research And Development Foundation Ltd. | Bitmap tracker for visual tracking under very general conditions |
US8233676B2 (en) * | 2008-03-07 | 2012-07-31 | The Chinese University Of Hong Kong | Real-time body segmentation system |
US8577156B2 (en) * | 2008-10-03 | 2013-11-05 | 3M Innovative Properties Company | Systems and methods for multi-perspective scene analysis |
KR101222482B1 (en) * | 2011-06-23 | 2013-01-15 | 브이씨에이 테크놀러지 엘티디 | People counter having set up interface and set up method thereof |
US8873892B2 (en) | 2012-08-21 | 2014-10-28 | Cognex Corporation | Trainable handheld optical character recognition systems and methods |
US10068153B2 (en) * | 2012-08-21 | 2018-09-04 | Cognex Corporation | Trainable handheld optical character recognition systems and methods |
GB2523330A (en) | 2014-02-20 | 2015-08-26 | Nokia Technologies Oy | Method, apparatus and computer program product for segmentation of objects in media content |
US9928592B2 (en) | 2016-03-14 | 2018-03-27 | Sensors Unlimited, Inc. | Image-based signal detection for object metrology |
US10007971B2 (en) | 2016-03-14 | 2018-06-26 | Sensors Unlimited, Inc. | Systems and methods for user machine interaction for image-based metrology |
US10757346B1 (en) | 2017-04-28 | 2020-08-25 | Flixbay Technologies, Inc. | Systems and methods for video extraction and insertion |
KR102498597B1 (en) | 2017-08-22 | 2023-02-14 | 삼성전자 주식회사 | Electronic device and method for identifying object based on setting region-of-interest by using the same |
Citations (16)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5329379A (en) * | 1992-10-22 | 1994-07-12 | International Business Machines Corporation | System and method of measuring fidelity of decompressed video signals and images |
US5715006A (en) * | 1993-09-28 | 1998-02-03 | Nec Corporation | apparatus for and method of motion compensation with boundarycorrection for moving picture |
US5764283A (en) * | 1995-12-29 | 1998-06-09 | Lucent Technologies Inc. | Method and apparatus for tracking moving objects in real time using contours of the objects and feature paths |
US5852673A (en) * | 1996-03-27 | 1998-12-22 | Chroma Graphics, Inc. | Method for general image manipulation and composition |
US5969755A (en) * | 1996-02-05 | 1999-10-19 | Texas Instruments Incorporated | Motion based event detection system and method |
US6031568A (en) * | 1997-09-11 | 2000-02-29 | Fujitsu Limited | Moving-target tracking apparatus |
US6075875A (en) * | 1996-09-30 | 2000-06-13 | Microsoft Corporation | Segmentation of image features using hierarchical analysis of multi-valued image data and weighted averaging of segmentation results |
US6137913A (en) * | 1998-08-05 | 2000-10-24 | Electronics And Telecommunications Research Institute | Method for segmenting moving picture objects by contour tracking |
US6173066B1 (en) * | 1996-05-21 | 2001-01-09 | Cybernet Systems Corporation | Pose determination and tracking by matching 3D objects to a 2D sensor |
US6230162B1 (en) * | 1998-06-20 | 2001-05-08 | International Business Machines Corporation | Progressive interleaved delivery of interactive descriptions and renderers for electronic publishing of merchandise |
US6295367B1 (en) * | 1997-06-19 | 2001-09-25 | Emtera Corporation | System and method for tracking movement of objects in a scene using correspondence graphs |
US6337917B1 (en) * | 1997-01-29 | 2002-01-08 | Levent Onural | Rule-based moving object segmentation |
US6400831B2 (en) * | 1998-04-02 | 2002-06-04 | Microsoft Corporation | Semantic video object segmentation and tracking |
US6456328B1 (en) * | 1996-12-18 | 2002-09-24 | Lucent Technologies Inc. | Object-oriented adaptive prefilter for low bit-rate video systems |
US6707851B1 (en) * | 1998-06-03 | 2004-03-16 | Electronics And Telecommunications Research Institute | Method for objects segmentation in video sequences by object tracking and user assistance |
US6738100B2 (en) * | 1996-06-07 | 2004-05-18 | Virage, Inc. | Method for detecting scene changes in a digital video stream |
Family Cites Families (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5101364A (en) * | 1990-02-09 | 1992-03-31 | Massachusetts Institute Of Technology | Method and facility for dynamic video composition and viewing |
US5635982A (en) * | 1994-06-27 | 1997-06-03 | Zhang; Hong J. | System for automatic video segmentation and key frame extraction for video sequences having both sharp and gradual transitions |
-
1998
- 1998-06-03 KR KR1019980020687A patent/KR100327103B1/en not_active IP Right Cessation
- 1998-10-26 EP EP98951788A patent/EP1092317A1/en not_active Ceased
- 1998-10-26 WO PCT/KR1998/000335 patent/WO1999063750A1/en active Application Filing
- 1998-10-26 JP JP2000552843A patent/JP4302891B2/en not_active Expired - Lifetime
- 1998-10-26 US US09/701,822 patent/US6707851B1/en not_active Expired - Lifetime
-
2003
- 2003-12-12 US US10/734,542 patent/US20040140994A1/en not_active Abandoned
Patent Citations (16)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5329379A (en) * | 1992-10-22 | 1994-07-12 | International Business Machines Corporation | System and method of measuring fidelity of decompressed video signals and images |
US5715006A (en) * | 1993-09-28 | 1998-02-03 | Nec Corporation | apparatus for and method of motion compensation with boundarycorrection for moving picture |
US5764283A (en) * | 1995-12-29 | 1998-06-09 | Lucent Technologies Inc. | Method and apparatus for tracking moving objects in real time using contours of the objects and feature paths |
US5969755A (en) * | 1996-02-05 | 1999-10-19 | Texas Instruments Incorporated | Motion based event detection system and method |
US5852673A (en) * | 1996-03-27 | 1998-12-22 | Chroma Graphics, Inc. | Method for general image manipulation and composition |
US6173066B1 (en) * | 1996-05-21 | 2001-01-09 | Cybernet Systems Corporation | Pose determination and tracking by matching 3D objects to a 2D sensor |
US6738100B2 (en) * | 1996-06-07 | 2004-05-18 | Virage, Inc. | Method for detecting scene changes in a digital video stream |
US6075875A (en) * | 1996-09-30 | 2000-06-13 | Microsoft Corporation | Segmentation of image features using hierarchical analysis of multi-valued image data and weighted averaging of segmentation results |
US6456328B1 (en) * | 1996-12-18 | 2002-09-24 | Lucent Technologies Inc. | Object-oriented adaptive prefilter for low bit-rate video systems |
US6337917B1 (en) * | 1997-01-29 | 2002-01-08 | Levent Onural | Rule-based moving object segmentation |
US6295367B1 (en) * | 1997-06-19 | 2001-09-25 | Emtera Corporation | System and method for tracking movement of objects in a scene using correspondence graphs |
US6031568A (en) * | 1997-09-11 | 2000-02-29 | Fujitsu Limited | Moving-target tracking apparatus |
US6400831B2 (en) * | 1998-04-02 | 2002-06-04 | Microsoft Corporation | Semantic video object segmentation and tracking |
US6707851B1 (en) * | 1998-06-03 | 2004-03-16 | Electronics And Telecommunications Research Institute | Method for objects segmentation in video sequences by object tracking and user assistance |
US6230162B1 (en) * | 1998-06-20 | 2001-05-08 | International Business Machines Corporation | Progressive interleaved delivery of interactive descriptions and renderers for electronic publishing of merchandise |
US6137913A (en) * | 1998-08-05 | 2000-10-24 | Electronics And Telecommunications Research Institute | Method for segmenting moving picture objects by contour tracking |
Cited By (10)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20070124766A1 (en) * | 2005-11-30 | 2007-05-31 | Broadcom Corporation | Video synthesizer |
US20090268808A1 (en) * | 2005-12-28 | 2009-10-29 | Ruijia Li | Novel user sensitive information adaptive video transcoding framework |
US9247244B2 (en) | 2005-12-28 | 2016-01-26 | Intel Corporation | User sensitive information adaptive video transcoding framework |
US20110096832A1 (en) * | 2009-10-23 | 2011-04-28 | Qualcomm Incorporated | Depth map generation techniques for conversion of 2d video data to 3d video data |
US8537200B2 (en) | 2009-10-23 | 2013-09-17 | Qualcomm Incorporated | Depth map generation techniques for conversion of 2D video data to 3D video data |
US8873855B2 (en) | 2012-03-08 | 2014-10-28 | Electronics And Telecommunications Research Institute | Apparatus and method for extracting foreground layer in image sequence |
US9990546B2 (en) | 2015-02-04 | 2018-06-05 | Alibaba Group Holding Limited | Method and apparatus for determining target region in video frame for target acquisition |
US10762722B2 (en) | 2016-06-28 | 2020-09-01 | Nokia Technologies Oy | Apparatus for sharing objects of interest and associated methods |
WO2019051608A1 (en) * | 2017-09-15 | 2019-03-21 | Imagine Communications Corp. | Systems and methods for production of fragmented video content |
US10863250B2 (en) | 2017-09-15 | 2020-12-08 | Imagine Communications Corp. | Systems and methods for production of fragmented video content |
Also Published As
Publication number | Publication date |
---|---|
US6707851B1 (en) | 2004-03-16 |
JP4302891B2 (en) | 2009-07-29 |
EP1092317A1 (en) | 2001-04-18 |
WO1999063750A1 (en) | 1999-12-09 |
JP2002517846A (en) | 2002-06-18 |
KR20000000823A (en) | 2000-01-15 |
KR100327103B1 (en) | 2002-09-17 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US6707851B1 (en) | Method for objects segmentation in video sequences by object tracking and user assistance | |
US6173077B1 (en) | Image segmentation | |
US6625333B1 (en) | Method for temporal interpolation of an image sequence using object-based image analysis | |
US6343141B1 (en) | Skin area detection for video image systems | |
KR101604601B1 (en) | Use of inpainting techniques for image correction | |
KR100301113B1 (en) | How to segment video objects by contour tracking | |
US5805221A (en) | Video signal coding system employing segmentation technique | |
JP2000513897A (en) | Image segmentation and object tracking method and corresponding system | |
US6115499A (en) | Repeat field detection using checkerboard pattern | |
WO2006054257A1 (en) | Motion vector field projection dealing with covering and uncovering | |
JP2002531020A (en) | Foreground information extraction method in stereoscopic image coding | |
US8135076B2 (en) | Error concealment apparatus and method | |
US8269885B2 (en) | Fade in/fade-out fallback in frame rate conversion and motion judder cancellation | |
US6707943B2 (en) | Method of monitoring the quality of distributed digital images by detecting false contours | |
US6687405B1 (en) | Image segmentation | |
US5623310A (en) | Apparatus for encoding a video signal employing a hierarchical image segmentation technique | |
EP0871332A2 (en) | Method and apparatus for coding a contour of an object employing temporal correlation thereof | |
US6369852B1 (en) | Analytical system for moving picture regeneration | |
US8582882B2 (en) | Unit for and method of segmentation using average homogeneity | |
EP1086592B1 (en) | Method and apparatus for background extraction for the reduction of number of coded blocks in video coding | |
JPH1013838A (en) | Motion vector detection method and its vector detector | |
KR0178234B1 (en) | Apparatus for grading a picture in an image encoder | |
JPH09322172A (en) | Method and device for cut point detection | |
Pronina et al. | Improving MPEG performance using frame partitioning | |
Codec et al. | Subjective Assessment of |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
STCB | Information on status: application discontinuation |
Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION |