Recovering Articulated Motion with a Hierarchical Factorization Method

摘要

Recovering articulated human motion is an important task in many applications including surveillance and human-computer interaction. In this paper, a hierarchical factorization method is proposed for recovering articulated human motion (such as hand gesture) from a sequence of images captured under weak perspective projection. It is robust against missing feature points due to self-occlusion, and various observation noises. The accuracy of our algorithm is verified by experiments on synthetic data.