Image analysis – Applications – Target tracking or detecting
Reexamination Certificate
2006-02-14
2006-02-14
Couso, Jose L. (Department: 2621)
Image analysis
Applications
Target tracking or detecting
Reexamination Certificate
active
06999599
ABSTRACT:
A system and method for object tracking using probabilistic mode-based multi-hypothesis tracking (MHT) provides for robust and computationally efficient tracking of moving objects such as heads and faces in complex environments. A mode-based multi-hypothesis tracker uses modes that are local maximums which are refined from initial samples in a parametric state space. Because the modes are highly representative, the mode-based multi-hypothesis tracker effectively models non-linear probabilistic distributions using a small number of hypotheses. Real-time tracking performance is achieved by using a parametric causal contour model to refine initial contours to nearby modes. In addition, one common drawback of conventional MHT schemes, i.e., producing only maximum likelihood estimates instead of a desired posterior probability distribution, is addressed by introducing an importance sampling framework into MHT, and estimating the posterior probability distribution from the importance function.
REFERENCES:
patent: 5926568 (1999-07-01), Chaney et al.
patent: 5999651 (1999-12-01), Chang et al.
patent: 6542621 (2003-04-01), Brill et al.
patent: 6741756 (2004-05-01), Toyama et al.
patent: 6826292 (2004-11-01), Tao et al.
Yong Rui, “Parametric Contour Tracking Using Unscented Kalman Filter”, Image Processing. 2002. Proceedings. 2002 International Conference on vol. 3, Jun. 24-28, 2002 pp.:613-616 vol. 3, p. 613-616.
Nathan Peterfreund, “Robust Tracking of Position and Velocity With Kalman Snakes”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 21, No. 6, Jun. 1999, p. 564-569.
A. Amini, T. Weymouth, R. Jain, “Using dynamic programming for solving variational problems in vision,”IEEE Trans. PAMI, vol. 12, No. 9, pp. 855-867, 1990.
S. Birchfield, “Ellipitical Head Tracking Using Intensity Gradients and Color Histograms”,Proc. CVPR, 1998. pp. 232-237.
T. Cham, J. M. Rehg, “Multiple hypothesis approach to figure tracking,”Proc. IEEE CVPR, vol. 2, p 239-245, 1999.
K. Choo and D. Fleet, “People tracking using hybrid Monte Carlo filtering”,Proc. IEEE ICCV, Vancouver, Canada, 2001.
J. Deutscher, A. Blake, I. Reid, “Articulated body motion capture by annealed particle filtering,”Proc. CVPR, 2000.
M. Isard, A. Blake, “Condensation—conditional density propagation for visual tracking”,Int. J. Computer Vision, 29, 1, 5-28 (1998).
M. Isard, A. Blake, Icondensation: Unifying low-level and high-level tracking in a stochastic framework,Proc. 5thEuropean Conf. Computer Vision, 1998, pp. 893-908.
M. Kass, A. Witkin, D. Terzopoulos, “Snakes: Active contour models”,Int. J. Comput. Vision, vol. 1, No. 4, pp. 321-331, 1987.
R. Merwe, A. Doucet, N. Freitas, and E. Wan, “The unscented particle filter”,Technical Report CUED/F-INFENG/TR 380, Cambridge University Engieering Department, Aug. 2000.
N. Peterfreund, “Robust tracking of position and velocity with Kalman snakes”,IEEE Trans.PAMI, vol. 21, No. 6, 1999, pp. 564-569.
D.B. Reid, “An algorithm for tracking mulitple targets”,IEEE Trans. On Automatic Control, vol. 24, No. 6, pp. 843-854, 1979.
K. Toyama, G. D. Hager, “Keeping your eye on the ball: Tracking occluding contours of unfamiliar objects without distraction,”IEEE Inter. Conf. on Intelligent Robots and Systems, pp 354-359, 1995.
J. Vermaak, and A. Blake, “Nonlinear filtering for speaker tracking in noisy and reverberant environments,”Proc. of IEEE ICASSP, 2000.
C.J.C Burges, J.C. Platt, and S. Jana, “Distortion Discriminant Analysis for Audio Fingerprinting”, IEEE Transactions on Speech and Audio Processing, vol. 11, No. 3, 2003.
Chen Yunqiang
Rui Yong
Couso Jose L.
Lu Tom Y.
Lyon & Harr LLP
Watson Mark A.
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