Computer vision has very wide application in human motion capture research. This paper proposes a new approach to do motion capture in video. It is composed of image sequence based tracking of human feature points and the reconstruction of the three-dimension(3D) motion skeleton. First, every part of the human body from top to bottom is tracked on the basis of a human model. The image difference and a morph-block similarity algorithm based on subpixels are used. Then camera calibration is done using the line correspondences between the 3D model and the image. Finally the 3D motion skeleton is established by use of the model knowledge. This approach does not aim at a given mode of human motion. Rather, it analyzes large scale motion from frame to frame in complex, variational background, and sets up a 3D motion skeleton in the perspective projection. The experiment results are presented at the end of the paper.
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