Posture Constraints for Bayesian Human Motion Tracking
One of the most used techniques for full-body human tracking consists of estimating the probability of the parameters of a human body model over time by means of a particle filter. However, given the high-dimensionality of the models to be tracked, the number of required particles to properly populate the space of solutions makes the problem computationally very expensive. To overcome this, we present an efficient scheme which makes use of an action-specific model of human postures to guide the prediction step of the particle filter, so only feasible human postures are considered. As a result, the prediction step of this model-based tracking approach samples from a first order motion model only those postures which are accepted by our action-specific model. In this manner, particles are propagated to locations in the search space with most a posteriori information avoiding particle wastage. We show that this scheme improves the efficiency and accuracy of the overall tracking approach.
KeywordsAction Model Human Motion Human Posture Prediction Step Tracking Approach
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- 1.Chai, J., Hodgins, J.K.: Performance animation from low-dimensional control signals. SIGGRAPH 2005, ACM Trans. Graph. 24(3), 686–696 (2005)Google Scholar
- 4.Gonzàlez, J.: Human Sequence Evaluation: the Key-frame Approach. PhD thesis, Universitat Autònoma de Barcelona (2004)Google Scholar
- 6.Horprasert, T., Harwood, D., Davis, L.S.: A robust background subtraction and shadow detection. In: Proc. Asian. Conf. on Comp. Vision (January 2000)Google Scholar
- 8.Ning, H., Tan, T., Wang, L., Hu, W.: Kinematics-based tracking of human walking in monocular video sequences. IVC 22, 429–441 (2004)Google Scholar
- 12.Stadler, W.: Analytical Robotics and Mechatronics. McGraw-Hill, NY, USA (1995)Google Scholar
- 13.Urtasun, R., Fleet, D.J., Hertzmann, A., Fua, P.: Priors for people tracking from small training sets. In: IEEE International Conference on Computer Vision (ICCV 2005), vol. 1, pp. 403–410 (2005)Google Scholar
- 14.Wachter, S., Nagel, H.H.: Tracking persons in monocular image sequences. CVIU 74(3), 174–192 (1999)Google Scholar