Recovery of 3D human posture from double views

The 3-D estimation of human motion captured by a video camera(s) is becoming a challenging scientific task. In this paper, two important problems are addressed: the acquisition of 3-D coordinates of human's body parts, and the key-frame-based human motion prediction. To the key frames, a fuzzy pattern matching method is adopted to detect and get 2-D image coordinates of the face in each image sequence. After stereo matching of the same feature point, we use a binocular imaging model to accomplish the acquisition of 3-D coordinates of the head. Out of the key frames, we use a Kalman estimator to predict the motion of human body parts. At the end of the paper, the experimental result and discussion are given.

[1]  Qian Chen,et al.  Face Detection From Color Images Using a Fuzzy Pattern Matching Method , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[2]  Aaron F. Bobick,et al.  Parametric Hidden Markov Models for Gesture Recognition , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[3]  Alex Pentland,et al.  Looking at People: Sensing for Ubiquitous and Wearable Computing , 2000, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  Alex Pentland,et al.  Invariant features for 3-D gesture recognition , 1996, Proceedings of the Second International Conference on Automatic Face and Gesture Recognition.

[5]  Jake K. Aggarwal,et al.  Nonrigid Motion Analysis: Articulated and Elastic Motion , 1998, Comput. Vis. Image Underst..