Image analysis – Applications – Target tracking or detecting
Reexamination Certificate
2007-01-09
2007-01-09
Dang, Duy M. (Department: 2624)
Image analysis
Applications
Target tracking or detecting
C382S173000, C348S169000
Reexamination Certificate
active
11171448
ABSTRACT:
A semantic object tracking method tracks general semantic objects with multiple non-rigid motion, disconnected components and multiple colors throughout a vector image sequence. The method accurately tracks these general semantic objects by spatially segmenting image regions from a current frame and then classifying these regions as to which semantic object they originated from in the previous frame. To classify each region, the method performs a region based motion estimation between each spatially segmented region and the previous frame to compute the position of a predicted region in the previous frame. The method then classifies each region in the current frame as being part of a semantic object based on which semantic object in the previous frame contains the most overlapping points of the predicted region. Using this method, each region in the current image is tracked to one semantic object from the previous frame, with no gaps or overlaps. The method propagates few or no errors because it projects regions into a frame where the semantic object boundaries are previously computed rather than trying to project and adjust a boundary in a frame where the object's boundary is unknown.
REFERENCES:
patent: 4783833 (1988-11-01), Kawabata et al.
patent: 5034986 (1991-07-01), Karmann et al.
patent: 5103305 (1992-04-01), Watanabe
patent: 5103306 (1992-04-01), Weiman et al.
patent: 5117287 (1992-05-01), Koike et al.
patent: 5136659 (1992-08-01), Kaneko et al.
patent: 5148497 (1992-09-01), Pentland et al.
patent: 5175808 (1992-12-01), Sayre
patent: 5214504 (1993-05-01), Toriu et al.
patent: 5258836 (1993-11-01), Murata
patent: 5259040 (1993-11-01), Hanna
patent: 5274453 (1993-12-01), Maeda
patent: 5295201 (1994-03-01), Yokohama
patent: 5329311 (1994-07-01), Ward et al.
patent: 5376971 (1994-12-01), Kadono et al.
patent: 5471535 (1995-11-01), Ikezawa et al.
patent: 5524068 (1996-06-01), Kacandes et al.
patent: 5546129 (1996-08-01), Lee
patent: 5557684 (1996-09-01), Wang et al.
patent: 5572258 (1996-11-01), Yokoyama
patent: 5577131 (1996-11-01), Oddou
patent: 5581308 (1996-12-01), Lee
patent: 5598215 (1997-01-01), Watanabe
patent: 5598216 (1997-01-01), Lee
patent: 5612743 (1997-03-01), Lee
patent: 5619281 (1997-04-01), Jung
patent: 5627591 (1997-05-01), Lee
patent: 5654771 (1997-08-01), Tekalp et al.
patent: 5666434 (1997-09-01), Nishikawa et al.
patent: 5668608 (1997-09-01), Lee
patent: 5673339 (1997-09-01), Lee
patent: 5684509 (1997-11-01), Hatanaka et al.
patent: 5684886 (1997-11-01), Kamada et al.
patent: 5692063 (1997-11-01), Lee et al.
patent: 5694487 (1997-12-01), Lee
patent: 5706417 (1998-01-01), Adelson
patent: 5717463 (1998-02-01), Brailean et al.
patent: 5731836 (1998-03-01), Lee
patent: 5731849 (1998-03-01), Kondo et al.
patent: 5734737 (1998-03-01), Chang et al.
patent: 5748789 (1998-05-01), Lee et al.
patent: 5761326 (1998-06-01), Brady et al.
patent: 5761341 (1998-06-01), Go
patent: 5764805 (1998-06-01), Martucci et al.
patent: 5764814 (1998-06-01), Chen et al.
patent: 5778098 (1998-07-01), Lee et al.
patent: 5784175 (1998-07-01), Lee
patent: 5802220 (1998-09-01), Black et al.
patent: 5809161 (1998-09-01), Auty et al.
patent: 5864630 (1999-01-01), Cosatto et al.
patent: 5923365 (1999-07-01), Tamir et al.
patent: 5946043 (1999-08-01), Lee et al.
patent: 5946419 (1999-08-01), Chen et al.
patent: 5978497 (1999-11-01), Lee et al.
patent: 5982909 (1999-11-01), Erdem et al.
patent: 6005493 (1999-12-01), Taniguchi et al.
patent: 6005625 (1999-12-01), Yokoyama
patent: 6011596 (2000-01-01), Burl et al.
patent: 6026182 (2000-02-01), Lee et al.
patent: 6037988 (2000-03-01), Gu et al.
patent: 6075875 (2000-06-01), Gu
patent: 6097854 (2000-08-01), Szeliski et al.
patent: 6400831 (2002-06-01), Lee et al.
patent: 6711278 (2004-03-01), Gu et al.
patent: 474307 (1992-03-01), None
patent: 579319 (1994-01-01), None
patent: 614318 (1994-09-01), None
patent: 625853 (1994-11-01), None
patent: WO 91/11782 (1991-08-01), None
patent: WO 97/05746 (1997-02-01), None
Adiv, “Determining Three-Dimensional Motion and Structure From Optical Flow Generated By Several Moving Objects,”IEEE Trans. on PAMI, vol. 7, pp. 384-401 (1985).
Aggarwal et al., “Corresponding Processes in Dynamic Scene Analysis,”Proc. IEEE, vol. 69, No. 5, pp. 562-572 (1981).
Ayer et al., “Segmentation of Moving Objects by Robust Motion Parameter Estimation Over Multiple Frames,”Proc. 3 European Conference on Computer Vision, Stockholm, Sweden, pp. 316-327 (1994).
Black, “Combining Intensity and Motion for Incremental Segmentation and Tracking Over Long Image Sequences,” ECCV'92, pp. 485-493, Santa Margherita, Italy (May 1992).
Bonnaud et al., “Multiple Occluding Object Tracking Using a Non-Redundant Boundary-Based Representation,” ICIP 97, pp. 426-429 (Oct. 1997).
Bouthemy et al., “Motion Segmentation and Qualitative Dynamic Scene Analysis from An Image Sequence,”Intl. Journal of Computer Vision, vol. 10, No. 2, pp. 157-182 (1993).
Brady et al., “Computationally Efficient Estimation of Polynomial Model-based Motion,”Proceedings of Picture Coding Symposium 1996, Melbourn(Mar. 1996).
Brady et al., “Object Detection and Tracking Using an Em-Based Motion Estimation and Segmentation Framework,” ICIP'96, vol. 1, pp. 925-928, Lausanne, Switzerland (Sep. 1996).
Burt et al., “Segmentation and Estimation of Image Region Properties Through Cooperative Hierarchical Computation,”IEEE Transactions on Systems, Man, and Cybernetics, vol. SMC-11, No. 12, pp. 802-809 (Dec. 1981).
Canny, “A Computational Approach to Edge Detection,”IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. PAMI-8, No. 6, pp. 679-698 (Nov. 1986).
Chang et al., “Next Generation Content Representation, Creation, and Searching for New-Media Applications in Education,”Proc. IEEE, vol. 86, No. 5, pp. 884-904 (1998).
Chang et al., “Transform Coding of Arbitrarily-Shaped Image Segments,”Proceedings of the ACM Multimedia 93, pp. 83-90 (Aug. 1, 1993).
Chen et al., “A Block Transform Coder for Arbitrarily Shaped Image Segments,” ICIP-94, vol. I/III, pp. 85-89 (Nov. 13, 1994).
Chen et al., “Image Segmentation as an Estimation Problem,”Computer Graphics and Image Processing, vol. 12, pp. 153-172 (1980).
Cover et al., “Nearest Neighbor Pattern Classification,”IEEE Transactions on Information Theory, vol. IT-13, pp. 21-27 (1967).
Crisman, “Color Region Tracking for Vehicle Guidance,”Active Vision, Blake and Yuille ed., MIT Press, Cambridge, pp. 107-120 (1992).
Curwen et al., “Dynamic Contours: Real-time Active Splines,”Active Vision, Blake and Yuille ed., MIT Press, Cambridge, pp. 39-58 (1992).
Deriche et al., “Tracking Line Segments,” ECCV'90, pp. 259-268 (1990).
Dickmanns, “Expectation-based Dynamic Scene Understanding,”Active Vision, Blake and Yuille ed., MIT Press, Cambridge, pp. 303-335 (1992).
Diehl, “Object-Oriented Motion Estimation and Segmentation In Image Sequences,”Signal Processing Image Communication, vol. 3, No. 1, pp. 23-56 (1991).
Fogg, “Image and Video Compression,”SPIE-The International Society for Optical Engineering Proceedings, vol. 2186 (1994).
Foley et al., “Computer Graphics Principles and Practice,” Addison-Wesley Publishing Company, Inc., pp. 835-851 (1990).
Franke et al., “Constrained Iterative Restoration Techniques: A Powerful Tool in Region Oriented Texture Coding,”Signal Processing IV: Theories and Applications, pp. 1145-1148 (Sep. 1988).
Goh et al., “Model-Based Multi-Resolution Motion Estimation in Noisy Images,”CVGIP: Image Understanding, vol. 59, No. 3, pp. 307-319 (1994).
Gordon, “On the Tracking of Featureless Objects with Occlusion,”IEEE Workshop on Visual Motion, Irving, pp. 13-20 (1989).
Gu, “3D Contour Image Coding Based on Morphological Filters and Motion Estimation,” ICAS
Gu Chuang
Lee Ming-Chieh
Dang Duy M.
Klarquist & Sparkman, LLP
Microsoft Corporation
LandOfFree
Tracking semantic objects in vector image sequences does not yet have a rating. At this time, there are no reviews or comments for this patent.
If you have personal experience with Tracking semantic objects in vector image sequences, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Tracking semantic objects in vector image sequences will most certainly appreciate the feedback.
Profile ID: LFUS-PAI-O-3825813