Video based human motion capture

Xiaoming Liu, Yueting Zhuang, Yi Wu, Yunhe Pan

Abstract: Proposes a new approach to capture human motion in video. This approach does not aim at a given human motion mode, but instead analyzes large-scale motion from frame to frame in a complex variational background and sets up a 3D motion skeleton under perspective projection. This approach is composed of two steps. First, we track every part of a human body from top to bottom on the basis of a human model. Then we perform a camera calibration using the line correspondences between the 3D model and the image, and establish the 3D motion skeleton by using the human model knowledge. The experimental results are presented at the end of the paper.