The kneed walker for human pose tracking

26th IEEE Conference on Computer Vision and Pattern Recognition, CVPR

Volumn , Issue , 2008, Pages

  Brubaker, Marcus A ^a   Fleet, David J ^a  

^a UNIVERSITY OF TORONTO   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

CYCLIC GAITS; DIFFERENT SLOPES; GENERATIVE MODELING; GROUND COLLISIONS; HUMAN LOCOMOTIONS; HUMAN POSE; HUMAN WALKING; JOINT LIMITS; KINEMATIC MODELLING; MEASUREMENT MODELS; ON DYNAMICS; OPTICAL-FLOW; PHYSICS-BASED MODELLING; UNDERLYING DYNAMICS; WALKING MOTIONS;

ARTIFICIAL INTELLIGENCE; BIOMECHANICS; BIPED LOCOMOTION; COMPUTER VISION; DYNAMICS; FEATURE EXTRACTION; IMAGE PROCESSING; KINEMATICS; OPTICAL FLOWS; PATTERN RECOGNITION; SPEED;

THREE DIMENSIONAL;

EID: 51949090604     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CVPR.2008.4587546     Document Type: Conference Paper

References (32)

1. A. Agarwal and B. Triggs. Recoving 3D human pose from monocular images. PAMI, 28(1):44-58, 2006.
2. A. Bissacco. Modeling and learning contact dynamics in human motion. CVPR, v. 1, pp. 421-428, 2005.
3. B. Brogliato, A. ten Dam, L. Paoli, F. Genot, and M. Abadie. Numerical simulation of finite dimensional multibody nonsmooth mechanical systems. Appl. Mech. Eng. Reviews, 55(2):107-150, 2002.
4. M. A. Brubaker, D. J. Fleet, and A. Hertzmann. Physics-based person tracking using simplified lower-body dynamics. CVPR, pp. 1-8, 2007.
5. S. Collins, A. Ruina, R. Tedrake, and M. Wisse. Efficient Bipedal Robots Based on Passive-Dynamic Walkers. Science, 307(5712):1082-1085, 2005.
6. J. Deutscher, A. Blake, and I. Reid. Articulated body motion capture by annealled particle filtering. CVPR, V. II, pp. 126-133, 2000.
7. A. Doucet, S. Godsill, and C. Andrieu. On sequential Monte Carlo sampling methods for Bayesian filtering. Stats. and Comp., 10(3):197-208, 2000.
8. A. Elgammal and C.-S. Lee. Inferring 3D body pose from silhouettes using activity manifold learning. CVPR, V. 2, pp. 681-688, 2004.
9. D. Fleet and Y. Weiss. Optical flow estimation. In Mathematical Models of Computer Vision: The Handbook, pp. 239-258, Springer, 2005.
10. A. Kong, J. S. Liu, and W. H. Wong. Sequential imputations and bayesian missing data problems. JASA, 89(425):278-288, 1994.
11. A. D. Kuo. A Simple Model of Bipedal Walking Predicts the Preferred Speed-Step Length Relationship. J. Biomech. Eng., 123(3):264-269, 2001.
12. A. D. Kuo. Energetics of Actively Powered Locomotion Using the Simplest Walking Model. J. Biomech. Eng., 124:113-120, 2002.
13. R. Li, T.-P. Tian, and S. Sclaroff. Simultaneous learning of non-linear manifold and dynamical models for high-dimensional time series. ICCV, 2007.
14. C. K. Liu, A. Hertzmann, and Z. Popović. Learning physics-based motion style with nonlinear inverse optimization. ACM Trans. Graphics, 24(3):1071-1081, 2005.
15. T. McGeer. Passive Walking with Knees. ICRA, V. 3, pp. 1640-1645, 1990.
16. T. McGeer. Dynamics and Control of Bipedal Locomotion. J. Theoretical Biol., 163:277-314, 1993.
17. D. Metaxas and D. Terzopoulos. Shape and nonrigid motion estimation through physics-based synthesis. PAMI, 15(6):580-591, 1993.
18. J. Nocedal and S. J. Wright. Numerical Optimization. Springer Series in Operations Res., 2nd ed., 2006.
19. M. Raibert. Legged Robots That Balance. MIT Press, Cambridge, 1986.
20. M. H. Raibert and J. K. Hodgins. Animation of dynamic legged locomotion. SIGGRAPH, pp. 349-358, 1991.
21. G. E. Robertson, G. Caldwell, J. Hamill, G. Kamen, and S. Whittlesey. Research Methods in Biomechanics. Human Kinetics, 2004.
22. L. Shampine. Conservation laws and the numerical solutions of ODEs, II. Comp. Math. Applic., 38:61-72, 1999.
23. L. Shampine, S. Thompson, J. A. Kierzenka, and G. D. Byrne. Non-negative solutions of ODEs. Appl. Math. Comp., 170:56-569, 2005.
24. H. Sidenbladh, M. Black, and D. J. Fleet. Stochastic Tracking of 3D Human Figures Using 2D Image Motion. ECCV, V. 2, pp. 702-718, 2000.
25. C. Sminchisescu and A. Jepson. Generative modeling for continuous non-linearly embedded visual inference. ICML, pp. 96-103, 2004.
26. 3E : Discriminative density propagation for visual tracking. PAMI, 29(11):2030-2044, 2007.
27. C. Sminchisescu and B. Triggs. Kinematic jump processes for monocular 3D human tracking. CVPR, pp 69-76, 2003
28. A. Thayananthan, R. Navaratnam, B. Stenger, P. Torr, and R. Cipolla. Multivariate relevance vector machines for tracking. ECCV 2006, V. 3, pp. 124-138. Springer, 2006.
29. R. Urtasun, D. J. Fleet, and P. Fua. 3D People Tracking with Gaussian Process Dynamical Models. CVPR, V 1, pp. 238-245, 2006.
30. R. Q. van der Linde and A. L. Schwab. Lecture Notes Multibody Dynamics B, wb1413. Lab. for Eng. Mech., Delft Univ. of Technology, 2002.
31. A. Witkin and M. Kass. Spacetime Constraints. SIGGRAPH, V. 22, pp. 159-168, 1988.
32. C. R. Wren and A. Pentland. Dynamic models of human motion. IEEE Face and Gesture, pp. 22-27, 1998.