Shape matching in pose reconstruction using shape context

Recovery of 3D body pose is a fundamental problem for human motion analysis in many applications. This paper introduces a new silhouette-based framework for inferring human pose from monocular uncalibrated camera and pays more attention on how to retrieving 3D body pose by matching 2D silhouette based on shape context. Finally we retrieve a group of 2D silhouettes from one human motion which has two different viewpoints. By many experiments, the rate of 2D silhouette matching we got is been proved more accurate than that generated by using other methods we have known in this field. To accelerate the matching process of calculating shape context, we use PCA (principal components analysis) to reduce the computation of complexity. In the paper we use trampoline and box sport as examples of complex human motion, to demonstrate the effectiveness of our approach and compare the results with those obtained with Hu moments methods