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

A novel approach is proposed to 3-D human motion estimation using regularization. First, a method of feature point tracking is developed based on alpha-beta 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.