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 PDF

Info

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
Application number
US10/734,542
Inventor
Jae Choi
Myoung Lee
Jin Kwak
Munchurl Kim
Chieteuk Ahn
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Individual
Original Assignee
Individual
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 Individual filed Critical Individual
Priority to US10/734,542 priority Critical patent/US20040140994A1/en
Publication of US20040140994A1 publication Critical patent/US20040140994A1/en
Abandoned legal-status Critical Current

Links

Images

Classifications

    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134Methods 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
    • H04N19/162User input
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/10Segmentation; Edge detection
    • G06T7/12Edge-based segmentation
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/10Segmentation; Edge detection
    • G06T7/174Segmentation; Edge detection involving the use of two or more images
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00Image analysis
    • G06T7/20Analysis of motion
    • G06T7/215Motion-based segmentation
    • GPHYSICS
    • G11INFORMATION STORAGE
    • G11BINFORMATION STORAGE BASED ON RELATIVE MOVEMENT BETWEEN RECORD CARRIER AND TRANSDUCER
    • G11B27/00Editing; Indexing; Addressing; Timing or synchronising; Monitoring; Measuring tape travel
    • G11B27/10Indexing; Addressing; Timing or synchronising; Measuring tape travel
    • G11B27/19Indexing; Addressing; Timing or synchronising; Measuring tape travel by using information detectable on the record carrier
    • G11B27/28Indexing; 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
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169Methods 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
    • H04N19/17Methods 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
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04NPICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/20Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using video object coding
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2200/00Indexing scheme for image data processing or generation, in general
    • G06T2200/16Indexing scheme for image data processing or generation, in general involving adaptation to the client's capabilities
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2200/00Indexing scheme for image data processing or generation, in general
    • G06T2200/24Indexing scheme for image data processing or generation, in general involving graphical user interfaces [GUIs]
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/10Image acquisition modality
    • G06T2207/10016Video; Image sequence
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06TIMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00Indexing scheme for image analysis or image enhancement
    • G06T2207/20Special algorithmic details
    • G06T2207/20092Interactive image processing based on input by user
    • G06T2207/20104Interactive 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

    CROSS REFERENCED TO RELATED APPLICATION
  • This application is a continuation of U.S. patent application Ser. No. 09/701,822 filed Jan. 26, 2001[0001]
  • TECHNICAL FIELD
  • 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). [0002]
  • BACKGROUND ART
  • 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. [0003]
  • 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. [0004]
  • 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. [0005]
  • DISCLOSURE OF INVENTION
  • 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. [0006]
  • 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. [0007]
  • 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. [0008]
  • BRIEF DESCRIPTION OF DRAWINGS
  • 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: [0009]
  • FIGS. 1[0010] a 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.[0011]
  • BEST MODE FOR CARRYING OUT THE INVENTION
  • The preferred embodiment of the present invention will hereinafter be described in detail with reference to the accompanying drawings. [0012]
  • FIGS. 1[0013] a and 1 b are exemplary diagrams of a video codec to which the method of the present invention can be applied.
  • Referring to FIG. 1[0014] a, 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.
  • Referring to FIG. 1[0015] b, 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.
  • FIG. 2 is a flowchart of a video object segmentation method according to one embodiment of the present invention. [0016]
  • 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 step [0017] 201).
  • 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. [0018]
  • 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, [0019]
  • 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 (step [0020] 202).
  • 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. [0021]
  • Next, in [0022] 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 (step [0023] 201).
  • If the result of the analysis shows that there is no scene change and any new object does not exist in the frame, in [0024] 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 [0025] 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.
  • 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. [0026]
  • 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. [0027]
  • 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. [0028]

Claims (7)

What is claimed is:
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.
US10/734,542 1998-06-03 2003-12-12 Method for objects segmentation in video sequences by object tracking and user assistance Abandoned US20040140994A1 (en)

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)

* Cited by examiner, † Cited by third party
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)

* Cited by examiner, † Cited by third party
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)

* Cited by examiner, † Cited by third party
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)

* Cited by examiner, † Cited by third party
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

Patent Citations (16)

* Cited by examiner, † Cited by third party
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)

* Cited by examiner, † Cited by third party
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