Gait tracking and recognition using person-dependent dynamic shape model

FGR 2006: Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition

Volumn 2006, Issue , 2006, Pages 553-559

  Lee, Chan Su ^a   Elgammal, Ahmed ^a  

^a RUTGERS UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL GEOMETRY; MATHEMATICAL MODELS; MATHEMATICAL TRANSFORMATIONS; NONLINEAR SYSTEMS; PARAMETER ESTIMATION; PATTERN RECOGNITION;

DYNAMIC SHAPE MODEL; GAIT TRACKING; NONLINEAR GENERATIVE MODEL;

GAIT ANALYSIS;

EID: 33750841451     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/FGR.2006.58     Document Type: Conference Paper

References (23)

1. A. Baumberg and D. Hogg. Generating spatiotemporal models from examples. Image and Vision Computing, 14(8):525-532, 1996.
2. C. BenAdbelkader, R. Cutler, and L. Davis. Motion-based recognition of people in eigengait space. In Proc. of FGR, pages 254-259, 2002.
3. T. F. Cootes, C. J. Taylor, D. H. Cooper, and J. Graham. Active shape models: Their training and applications. CVIU, 61(1):38-59, 1995.
4. D. Cunado, M. S. Nixon, and J. Carter. Automatic extraction and description of human gait models for recognition purposes. CVIU, 90:1-41, 2003.
5. J. Deutscher, A. Blake, and I. Reid. Articulated body motion capture by annealed particle filtering. In Proc. of CVPR, volume 2, pages 126-133, 2000.
6. A. Elgammal and C.-S. Lee. Inferring 3d body pose from silhouettes using activity manifold learning. In Proc. CVPR, volume 2, pages 681-688, 2004.
7. A. Elgammal and C.-S. Lee. Separating style and content on a nonlinear manifold. In Proc. CVPR, volume 1, pages 478-485, 2004.
8. P. Huang, C. Haris, and M. Nixon. Recogising humans by gait via parametric canonical space. Artificial Intelligence in Engineering, 13:359-366, 1999.
9. M. Isard and A. Blake. Condensation-conditional density propagation for visual tracking. Int.J. Computer Vision, 29(1):5-28, 1998.
10. A. Kale, A. Sundaresan, A. N. Rajagopalan, N. P. Cuntoor, A. K. Roy-Chowdhury, V. Kruger, and R. Chellappa. Identification of human using gait. IEEE Trans. Image Processing, 13(9):1163-1173, 2004.
11. C.-S. Lee and A. Elgammal. Gait style and gait content: Bilinear model for gait recogntion using gait re-sampling. In Proc. of FGR, pages 147-152, 2004.
12. C.-S. Lee and A. Elgammal. Style adaptive bayesian tracking using explicit manifold learning. In Proc. of British Machine Vision Conference, 2005.
13. L. Lee, G. Dalley, and K. Tieu. Learning pedestrian models for silhouette refinement. In Proc. of ICCV, pages 663-670, 2003.
14. Z. Liu and S. Sarkar. Simplest representation yet for gait recognition: Averaged silhouette. In Proc. ICPR, pages 211-214, 2004.
15. T. Poggio and F. Girosi. Networks for approximation and learning. Proceedings of the IEEE, 78(9):1481-1497, 1990.
16. S. Roweis and L. Saul. Nonlinear dimensionality reduction by locally linar embedding. Science, 290(5500):2323-2326, 2000.
17. B. Schlkopf and A. Smola. Learning with Kernels: Support Vector Machines, Regularization, Optimization and Beyond. MIT Press, 2002.
18. J. D. Shutler, M. G. Grant, M. S. Nixon, and J. N. Carter. On a large sequence-based human gait database. In Proc. Int. Conf. on Recent Advances in Soft Computing, pages 6671, 2002.
19. J. B. Tenenbaum and W. T. Freeman. Separating style and content with biliear models. Neural Computation, 12:12471283, 2000.
20. D. Tolliver and R. T. Collins. Gait shape estimation for identification. In Proc. AVBPA, pages 734-742, 2003.
21. K. Toyama and A. Blake. Probabilistic tracking in a metric space. In ICCV, pages 50-59, 2001.
22. L. Wang, T. Tan, H. Ning, and W. Hu. Silhouette analysisbased gait recognition for human identification. IEEE Trans. PAMI, 25(12): 1505-1518, 2003.
23. Q. Wang, G. Xu, and H. Ai. Learning object intrinsic structure for robust visual tracking. In CVPR, volume 2, pages 227-233, 2003.