Computer graphics processing and selective visual display system – Computer graphics processing – Three-dimension
Reexamination Certificate
2006-09-26
2006-09-26
Nguyen, Kimbinh T. (Department: 2671)
Computer graphics processing and selective visual display system
Computer graphics processing
Three-dimension
C345S683000, C715S716000, C715S723000, C382S159000, C382S173000
Reexamination Certificate
active
07113185
ABSTRACT:
A simplified general model and an associated estimation algorithm is provided for modeling visual data such as a video sequence. Specifically, images or frames in a video sequence are represented as collections of flat moving objects that change their appearance and shape over time, and can occlude each other over time. A statistical generative model is defined for generating such visual data where parameters such as appearance bit maps and noise, shape bit-maps and variability in shape, etc., are known. Further, when unknown, these parameters are estimated from visual data without prior pre-processing by using a maximization algorithm. By parameter estimation and inference in the model, visual data is segmented into components which facilitates sophisticated applications in video or image editing, such as, for example, object removal or insertion, tracking and visual surveillance, video browsing, photo organization, video compositing, etc.
REFERENCES:
patent: 5892847 (1999-04-01), Johnson
patent: 6668080 (2003-12-01), Torr et al.
Schodl et al. “Controlled Animation of Video Sprites”, ACM, piblished Jul. 2002, pp. 121-127 and 196.
John Y. A. Wang and Edward H. Adelson, “Representing Moving Images with Layers.” M.I.T. Media Laboratory Perceptual Computing Section Technical Report No. 279 (Replaces TR-228 ) Appears in the IEEE Transactions on Image Processing Special Issue: Image Sequence Compression, vol. 3, No. 5, pp. 625-638, Sep. 1994. Revised: May, 1994.
Philip H.S. Torr, Richard Szeliski, P. Anandan, “An Integrated Bayesian Approach to Layer Extraction from Image Sequences” IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 23, No. 3; Mar. 2001, pp. 297-303.
A. Jepson and M. Black. “Mixture models for optical flow computation.” Technical Report RBCVTR -93-44, University of Toronto, 1993.
Michael J. Black David J. Fleet, “Probabilistic Detection and Tracking of Motion Discontinuities” Int. Conf. on Computer Vision (ICCV'99), Corfu, Greece, Sep. 1999.
Hai Tao, Harpreet S. Sawhney, and Rakesh Kumar, “Dynamic layer representation and its applications to tracking,” inProc. IEEE conf. on Computer Vision and Pattern Recognition(CVPR2000), vol. 2, pp. 134-141, Jun. 2000.
Frey Brendan J.
Jojic Nebojsa
Lyon & Harr LLP
Nguyen Kimbinh T.
Watson Mark
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