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Title: US7142600: Occlusion/disocclusion detection using K-means clustering near object boundary with comparison of average motion of clusters to object and background motions
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Country: US United States of America

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Inventor: Schonfeld, Dan; Glenview, IL, United States of America
Hariharakrishnan, Karthik; Chicago, IL, United States of America
Raffy, Philippe; Sunnyvale, CA, United States of America
Yassa, Fathy; Soquel, CA, United States of America

Assignee: NeoMagic Corp., Santa Clara, CA, United States of America
other patents from NEOMAGIC CORP. (719584) (approx. 58)
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Published / Filed: 2006-11-28 / 2003-04-21

Application Number: US2003000249577

IPC Code: Advanced: H04B 1/66; H04N 7/12; H04N 11/02; H04N 11/04;
Core: H04N 11/00; more...

ECLA Code: G06T7/20A; H04N7/26J; H04N7/26M2; H04N7/50;

U.S. Class: 375/240.16;

Field of Search: Non/00e

Priority Number:
2003-04-21  US2003000249577
2003-01-11  US2003000248348

Abstract:     An object in a video sequence is tracked by object masks generated for frames in the sequence. Macroblocks are motion compensated to predict the new object mask. Large differences between the next frame and the current frame detect suspect regions that may be obscured in the next frame. The motion vectors in the object are clustered using a K-means algorithm. The cluster centroid motion vectors are compared to an average motion vector of each suspect region. When the motion differences are small, the suspect region is considered part of the object and removed from the object mask as an occlusion. Large differences between the prior frame and the current frame detect suspected newly-uncovered regions. The average motion vector of each suspect region is compared to cluster centroid motion vectors. When the motion differences are small, the suspect region is added to the object mask as a disocclusion.

Attorney, Agent or Firm: Auvinen, Stuart T. ;

Primary / Asst. Examiners: Diep, Nhon;

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Related Applications:
Application Number Filed Patent Pub. Date  Title
US2003000248348 2003-01-11       


       
Parent Case: CROSS REFERENCE TO RELATED APPLICATIONS
    This application is a continuation-in-part of the co-pending application for Object Tracking Using Adaptive Block-Size Matching along Object Boundary and Frame-Skipping When Object Motion is Low, U.S. Ser. No. 10/248,348, filed Jan. 11, 2003.

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First Claim:
Show all 20 claims
    1. An object tracker comprising:

a backward motion estimator, receiving a base object location in a base frame, for generating backward motion vectors representing displacements from regions in a current frame to best-matching regions in the base frame;

an object-location generator that generates a current object location for the current frame by including regions from the current frame that match best-matching regions in the base frame that are within the base object location and including sub-regions in the current frame matching best-matching sub-regions that are within the base object location;

a forward motion estimator, receiving the current object location in the current frame, for generating forward motion vectors representing displacements to best-matching regions in a second frame from the current frame;

an occlusion detector, receiving the forward motion vectors, the occlusion detector comprising:

a forward difference generator that finds a suspect covered region in the current frame and within the current object location, the suspect covered region not having a best-matching region in the second frame;

an object clusterer that divides regions in the current object location into a plurality of object clusters by minimizing variance of backward motion vectors of regions within an object cluster, each object cluster being represented by a centroid motion vector;

a motion-similarity comparator that compares an average motion vector for the suspect covered region to the centroid motion vector for each object cluster and signals an occlusion when a minimum difference between the average motion vector and the centroid motion vectors is less than an occlusion threshold; and

an occlusion remover that receives the current object location and removes the suspect covered region when the motion-similarity comparator signals the occlusion,

whereby suspect covered regions are removed as occluded regions when the motion-similarity comparator signals the occlusion.



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Forward References: Show 4 U.S. patent(s) that reference this one

       
U.S. References: Go to Result Set: All U.S. references   |  Forward references (4)   |   Backward references (18)   |   Citation Link

Buy
PDF
Patent  Pub.Date  Inventor Assignee   Title
Buy PDF- 11pp US5635986  1997-06 Kim  Daewoo Electronics Co., Ltd Method for encoding a contour of an object in a video signal by using a contour motion estimation technique
Buy PDF- 12pp US5936671  1999-08 Van Beek et al.  Sharp Laboratories of America, Inc. Object-based video processing using forward-tracking 2-D mesh layers
Buy PDF- 75pp US5940538  1999-08 Spiegel et al.   Apparatus and methods for object border tracking
Buy PDF- 68pp US6075875  2000-06 Gu  Microsoft Corporation Segmentation of image features using hierarchical analysis of multi-valued image data and weighted averaging of segmentation results
Buy PDF- 8pp US6137913  2000-10 Kwak et al.  Electronics and Telecommunications Research Institute Method for segmenting moving picture objects by contour tracking
Buy PDF- 23pp US6169573  2001-01 Sampath-Kumar et al.  HOTV, Inc. Hypervideo system and method with object tracking in a compressed digital video environment
Buy PDF- 15pp US6192156  2001-02 Moorby  Synapix, Inc. Feature tracking using a dense feature array
Buy PDF- 10pp US6236680  2001-05 Chun et al.  Samsung Electronics Electronics Co., Ltd. Encoding and decoding system of motion image containing arbitrary object
Buy PDF- 33pp US6298170  2001-10 Morita  Fujitsu Limited Image tracking apparatus for tracking an image within a local region to continuously track a moving object
Buy PDF- 8pp US6337917  2002-01 Onural et al.   Rule-based moving object segmentation
Buy PDF- 23pp US6389168  2002-05 Altunbasak et al.  Hewlett-Packard Company Object-based parsing and indexing of compressed video streams
Buy PDF- 33pp US6393054  2002-05 Altunbasak  Hewlett-Packard Company System and method for automatically detecting shot boundary and key frame from a compressed video data
Buy PDF- 16pp US6400846  2002-06 Lin et al.  Mitsubishi Electric Research Laboratories, Inc. Method for ordering image spaces to search for object surfaces
Buy PDF- 21pp US6424370  2002-07 Courtney  Texas Instruments Incorporated Motion based event detection system and method
Buy PDF- 31pp US6466624  2002-10 Fogg  Pixonics, LLC Video decoder with bit stream based enhancements
Buy PDF- 136pp US20040090523A1  2004-05 Kondo et al.   Image processing apparatus and method and image pickup apparatus
Buy PDF- 25pp US20040091047A1  2004-05 Paniconi et al.   Method and apparatus for nonlinear multiple motion model and moving boundary extraction
Buy PDF- 22pp US20050213660A1  2005-09 Paniconi et al.   Method and apparatus for nonlinear multiple motion model and moving boundary extraction
       
Foreign References: None

Other References:
  • D. Schonfeld and D. Lelescu,“VORTEX: Video retrieval and tracking from compressed multimedia databases-multiple object tracking from MPEG-2 bitstream.”
  • Journal of Visual Communications and Image Representation, Special Issue on Multimedia Database Management, vol. 11, pp. 154-182, 2000 (50pp).
  • Eickeler et al., “Content-Based Indexing of Images and Video using face Detection and Recognition Methods”.
  • IEEE Int. Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2001 (4pp).


  • Continuity Data:
    Application Number Filed Notes

    US2002000249577   is a continuation in part of
    US2003000248348  2003-01-11   (pending) [presumed granted]
         US7095786 issued 2006-08-22   Object tracking using adaptive block-size matching along object boundary and frame-skipping when object motion is low


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