Outdoor human motion capture using inverse kinematics and von mises-fisher sampling

Proceedings of the IEEE International Conference on Computer Vision

Volumn , Issue , 2011, Pages 1243-1250

  Pons Moll, Gerard ^a   Baak, Andreas ^b   Gall, Juergen ^c   Leal Taixé, Laura ^a   Müller, Meinard ^b   Seidel, Hans Peter ^b   Rosenhahn, Bodo ^a  

^a LEIBNIZ UNIVERSITY HANNOVER   (Germany)

^b SAARLAND UNIVERSITY   (Germany)

^c ETH ZURICH   (Switzerland)

Author keywords

[No Author keywords available]

Indexed keywords

ARBITRARY ORIENTATION; BACKGROUND CLUTTER; DYNAMIC MOTIONS; EFFICIENT SAMPLING; HIGH DIMENSIONALITY; HUMAN MOTION CAPTURE; HUMAN MOTIONS; INERTIAL SENSOR; KINEMATIC CONSTRAINTS; MULTI-VIEW IMAGE; OPTIMIZATION SCHEME; ORIENTATION CONSTRAINT; OUTDOOR ENVIRONMENT; SENSOR NOISE; STATE SPACE; VISUAL CUES; VON MISES-FISHER DISTRIBUTION; VON MISES-FISHER SAMPLING;

IMAGE PROCESSING;

INVERSE KINEMATICS;

EID: 84863407129     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCV.2011.6126375     Document Type: Conference Paper

References (35)

1. P. Azad, T. Asfour, and R. Dillmann. Robust real-time stereo-based markerless human motion capture. In Proc. 8th IEEE-RAS Int. Conf. Humanoid Robots, 2008.
2. A. Baak, B. Rosenhahn, M. Müller, and H.-P. Seidel. Stabilizing motion tracking using retrieved motion priors. In ICCV, 2009.
3. A. O. Balan, L. Sigal, M. J. Black, J. E. Davis, and H.W. Haussecker. Detailed human shape and pose from images. In CVPR, 2007.
4. C. Bregler, J. Malik, and K. Pullen. Twist based acquisition and tracking of animal and human kinematics. IJCV, 56(3):179-194, 2004.
5. J. Chen, M. Kim, Y. Wang, and Q. Ji. Switching gaussian process dynamic models for simultaneous composite motion tracking and recognition. In CVPR, pages 2655-2662. IEEE, 2009.
6. J. Deutscher and I. Reid. Articulated body motion capture by stochastic search. IJCV, 61(2):185-205, 2005.
7. R. Fisher. Dispersion on a sphere. Proceedings of the Royal Society of London. Mathematical and Physical Sciences, 1953.
8. M. Fontmarty, F. Lerasle, and P. Danes. Data fusion within a modified annealed particle filter dedicated to human motion capture. In IRS, 2007.
9. J. Gall, B. Rosenhahn, T. Brox, and H.-P. Seidel. Optimization and filtering for human motion capture. IJCV, 87:75-92, 2010.
10. J. Gall, A. Yao, and L. Van Gool. 2D action recognition serves 3D human pose estimation. In ECCV, pages 425-438, 2010.
11. V. Ganapathi, C. Plagemann, S. Thrun, and D. Koller. Real time motion capture using a time-of-flight camera. In CVPR, 2010.
12. D. Gavrila and L. Davis. 3D model based tracking of humans in action: A multiview approach. In CVPR, 1996.
13. N. Hasler, B. Rosenhahn, T. Thormählen, M. Wand, J. Gall, and H.- P. Seidel. Markerless motion capture with unsynchronized moving cameras. In CVPR, pages 224-231, 2009.
14. S. Hauberg, J. Lapuyade, M. Engell-Norregard, K. Erleben, and K. Steenstrup Pedersen. Three dimensional monocular human motion analysis in end-effector space. In EMMCVPR, 2009.
15. H. Kjellstromm, D. Kragic, and M. J. Black. Tracking people interacting with objects. In CVPR, pages 747-754, 2010.
16. C. Lee and A. Elgammal. Coupled visual and kinematic manifold models for tracking. IJCV, 2010.
17. M. W. Lee and I. Cohen. Proposal maps driven mcmc for estimating human body pose in static images. In CVPR, volume 2, 2004.
18. N. Lehment, D. Arsic, M. Kaiser, and G. Rigoll. Automated pose estimation in 3D point clouds applying annealing particle filters and inverse kinematics on a gpu. In CVPR Workshop, 2010.
19. T. Moeslund, A. Hilton, V. Krueger, and L. Sigal, editors. Visual Analysis of Humans: Looking at People. Springer, 2011.
20. R. Murray, Z. Li, and S. Sastry. A Mathematical Introduction to Robotic Manipulation. CRC Press, Baton Rouge, 1994.
21. B. Paden. Kinematics and control of robot manipulators. PhD thesis, 1985.
22. G. Pons-Moll, A. Baak, T. Helten, M. Müller, H.-P. Seidel, and B. Rosenhahn. Multisensor-fusion for 3D full-body human motion capture. In CVPR, pages 663-670, 2010.
23. G. Pons-Moll, L. Leal-Taixé, T. Truong, and B. Rosenhahn. Efficient and robust shape matching for model based human motion capture. In DAGM, 2011.
24. G. Pons-Moll and B. Rosenhahn. Visual Analysis of Humans: Looking at People, chapter Model Based Pose Estimation. Springer, 2011.
25. M. Salzmann and R. Urtasun. Combining discriminative and generative methods for 3d deformable surface and articulated pose reconstruction. In CVPR, June 2010.
26. G. Shakhnarovich, P. Viola, and T. Darrell. Fast pose estimation with parameter-sensitive hashing. In ICCV, pages 750-757, 2003.
27. H. Sidenbladh, M. Black, and D. Fleet. Stochastic tracking of 3D human figures using 2D image motion. In ECCV, 2000.
28. L. Sigal, L. Balan, and M. Black. Combined discriminative and generative articulated pose and non-rigid shape estimation. In NIPS, pages 1337-1344, 2008.
29. C. Sminchisescu and B. Triggs. Kinematic jump processes for monocular 3d human tracking. In CVPR, 2003.
30. Y. Tao, H. Hu, and H. Zhou. Integration of vision and inertial sensors for 3D arm motion tracking in home-based rehabilitation. IJRR, 26(6):607, 2007.
31. X. M. Technologies. http://www.xsens.com/.
32. R. Urtasun, D. J. Fleet, and P. Fua. 3D people tracking with gaussian process dynamical models. In CVPR, 2006.
33. P. Wang and J. M. Rehg. A modular approach to the analysis and evaluation of particle filters for figure tracking. In CVPR, 2006.
34. A. Wood. Simulation of the von mises-fisher distribution. Communications in Statistics - Simulation and Computation, 1994.
35. F. Zhang, E. R. Hancock, C. Goodlett, and G. Gerig. Probabilistic white matter fiber tracking using particle filtering and von misesfisher sampling. Medical Image Analysis, 13(1):5-18, 2009.