A background layer model for object tracking through occlusion

Proceedings of the IEEE International Conference on Computer Vision

Volumn 2, Issue , 2003, Pages 1079-1085

  Zhou, Yue ^a   Tao, Hai ^a  

^a University of California Santa Cruz   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; COMPUTATIONAL COMPLEXITY; IMAGE SEGMENTATION; MARKOV PROCESSES; MATHEMATICAL MODELS; MOTION ESTIMATION; PARAMETER ESTIMATION;

MOTION LAYER PARAMETERS; OBJECT TRACKING METHOD;

OBJECT RECOGNITION;

EID: 0344983291     PISSN: 15505499     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (12)

1. J. R. Bergen, P. Anandan, K. K. Hanna, and R. Hingorani, Hiearchical model-based motion estimation, in Proc. of 2nd European Conference on Computer Vision, pp. 237-252, 1992.
2. M.J. Black, D.J. Fleet., and Y. Yacoob A framework for modeling appearance change in image sequences. IEEE International Conference on Computer Vision, Mumbai, India, January 1998, pp. 660-667.
3. Black, M. J. and Fleet, D. J., Probabilistic detection and tracking of motion boundaries, Int. J. of Computer Vision, 38(3):231-245, July 2000.
4. Allan D. Jepson, David J. Fleet, Michael J. Black A Layered Motion representation with occlusion and compact spatial support. ECCV (1) 2002: 692-706.
5. Allan D. Jepson, David J. Fleet and Thomas F. El-Maraghi, Robust online appearance models for visual tracking IEEE Conference on Computer Vision and and Pattern Recognition, Kauai, 2001, Vol. I, pp. 415-422.
6. N. Jojic, N. Petrovic, B. Frey, and T. S. Huang, Transformed hidden Markov models: estimating mixture models of images and inferring spatial transformations in video sequences, in Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, pp.(II) 26-33, 2000.
7. N. Jojic and B.J. Frey Learning flexible sprites in video layers. In Computer Vision and Pattern Recognition, pages I:199-206, 2001.
8. L.R. Rabiner. A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE, 77(2): 257-285, 1989.
9. H. Tao, H. Sawhney and R. Kumar, "Object tracking with Bayesian estimation of dynamic layer representations", IEEE Transactions On Pattern Analysis And Machine Intelligence. Jan. 2002.
10. N. Vasconcelos and A. Lippman, Emprical Bayesian EM-based motion segmentation, in Proc. of IEEE Conference on Computer Vision and Pattern Recognition, pp. 527-532, 1997.
11. J. Y. A. Wang and Edward H. Adelson, Layered representation for motion analysis, in Proc. of IEEE conference on Computer Vision and Pattern Recognition, pp. 361-366, 1993.
12. Y. Weiss and E. H. Adelson, A unified mixture framework for motion segmentation: incorporating spatial coherence and estimating the number of models, in Proc. of IEEE conference on Computer Vision and Pattern Recognition, pp. 321-326, 1996.