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3-D human motion estimation using regularization with 2-D feature point tracking

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3 Author(s)
Ya-Ming Wang ; Res. Center for Comput. Vision & Pattern Recognition, Zhejiang Inst. of Sci. & Technol., Hangzhou, China ; Li Cao ; Wen-Qing Huang

A novel approach is proposed to 3-D human motion estimation using regularization. First, a method of feature point tracking is developed based on α-β filter and genetic algorithm. The outliers and occluded points can be solved by this method. Then, in order to deal with the ill-posed estimation problem, a regularization approach is proposed, which is based on the results of 2-D feature point tracking and the motion smoothness between consecutive estimation groups. Thus, the ill-posed problem is converted to a well-posed one. Experimental results also demonstrate the feasibility of the proposed approach.

Published in:

Machine Learning and Cybernetics, 2003 International Conference on  (Volume:5 )

Date of Conference:

2-5 Nov. 2003