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Bibliography [1] Shai Avidan. Support vector tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence, 26(8):pp. 1064–1072, 2001. [2] Andrew Blake and Michael Isard. Active Contours. Springer-Verlag, 1998. [3] Vicent Caselles, Ron Kimmel, and Guillermo Sapiro. Geodesic active contours. International Journal of Computer Vision, 22(1):pp. 61–79, 1997. [4] Robert T. Collins, Alan J. Lipton, Takeo Kanade, Hironobu Fujiyoshi, David Duggins, Yanghai Tsin, David Tolliver, Nobuyoshi Enomoto, Os- amu Hasegawa, Peter Burt, and Lambert Wixson. A system for video surveillance and monitoring. Carnegie Mellon University, Pittsburgh, PA, Tech. Rep., CMU-RI-TR-00-12, 2000. [5] J M Ferryman, S Maybank, and A Worrall. Visual surveillance for moving vehicles. International Journal of Computer Vision, 37(2):pp. 187–197, 2000. [6] Christophe Fiorio and Jens Gustedt. Two linear time union-find strate- gies for image processing. Theoretical Computer Science, 154(2):pp. 165 – 181, 1996. [7] David A. Forsyth and Jean Ponce. Computer Vision: A Modern Ap- proach. Prentice Hall, 2002. [8] Gregory D. Hager and Peter N. Belhumeur. Efficient region tracking with parametric models of geometry and illumination. IEEE Transac- tions on Pattern Analysis and Machine Intelligence, 20(10):pp. 1025– 1039, 1998. [9] Weiming Hu, Tieniu Tan, LiangWang, and Steve Maybank. A survey on visual surveillance of object motion and behaviors. IEEE Transactions on Systems, Man, and Cybernetics, 34(3):pp. 334–352, 2004. [10] Peter J. Huber. Robust Statistics. Wiley, 1981. [11] Michael Isard and Andrew Blake. CONDENSATION—conditional den- sity propagation for visual tracking. International Journal of Computer Vision, 29(1):pp. 107–112, 1998. [12] Allan D. Jepson, David J. Fleet, and Michael J. Black. A layered motion representation with occlusion and compact spatial support. European Conference on Computer Vision, 1:pp. 692–706, 2002. [13] Allan D. Jepson, David J. Fleet, and Thomas F. El-Maraghi. Robust online appearance models for visual tracking. IEEE Conference on Com- puter Vision and Pattern Recognition, 1:pp. 415–422, 2001. [14] Rudolph Emil Kalman. A new approach to linear filtering and prediction problems. Transactions of the ASME–Journal of Basic Engineering, 82(Series D):pp. 35–45, 1960. [15] Jongwoo Lim, David Ross, Ruei Sung Lin, and Ming Hsuan Yang. In- cremental learning for visual tracking. Advances in Neural Information Processing Systems, 17:pp. 793–800, 2005. [16] D. Meyer, J. Denzier, and H. Niemann. Model based extraction of articulated objects in image sequences for gait analysis. In Proc. IEEE International Conference Image Processing, pages pp. 78–81, 1998. [17] Christopher Rasmussen and Gregory D. Hager. Probabilistic data asso- ciation methods for tracking complex visual objects. IEEE Transaction on Pattern Analysis and Machine Intelligence, 23(6):pp. 560–576, 2001. [18] C. Stauffer and W. Grimson. Adaptive background mixture models for real-time tracking. In Proc. IEEE Conf. Computer Vision and Pattern Recognition, 2:pp. 246–252, 1999. [19] Kenji Suzuki, Isao Horiba, and Noboru Sugie. Linear-time connected- component labeling based on sequential local operations. Computer Vi- sion and Image Understanding, 89:pp. 1–23, 2003. [20] Hai Tao, Harpreet S. Sawhney, and Rakesh Kumar. Object tracking with bayesian estimation of dynamic layer representations. IEEE Transac- tions on Pattern Analysis and Machine Intelligence, 24(1):pp. 75–89, 2002. [21] John Y. A. Wang and Edward H. Adelson. Representing moving im- ages with layers. IEEE Transactions on Image Processing Special Issue: Image Sequence Compression, 3(5):pp. 625–638, 1994. [22] Greg Welch and Gary Bishop. An introduction to the kalman filter. 2004. [23] Oliver Williams, Andrew Blake, and Roberto Cipolla. A sparse prob- abilistic learning algorithm for real-time tracking. IEEE International Conference on Computer Vision, 1:pp. 353–360, 2003. [24] Shaohua Zhou, Rama Chellappa, and Baback Moghaddam. Visual track- ing and recognition using appearance-adaptive models in particle filters. IEEE Transaction on Image Processing, 13(11):pp. 1491–1506, 2004. [25] Yue Zhou and Hai Tao. A background layer model for object tracking through occlusion. In Proceedings of IEEE International Conference on Computer Vision, pages pp. 1079–1085, 2003.
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