Human-computer interaction

Abstract

SUMMARYThis paper presents a method for markerless human motion capture using a single camera. It uses tree-based filtering to efficiently propagate a probability distribution over poses of a 3D body model. The pose vectors and associated shapes are arranged in a tree, which is constructed by hierarchical pairwise clustering, in order to efficiently evaluate the likelihood in each frame. A new likelihood function based on silhouette matching is proposed that improves the pose estimation of thinner body parts, i.e. the limbs. The dynamic model takes self-occlusion into account by increasing the variance of occluded body-parts, thus allowing for recovery when the body part reappears. We present two applications of our method that work in real-time on a Cell Broadband Engine TM : a computer game and a virtual clothing application. key words: video motion capture, tree-based filtering, silhouette matching, Cell Broadband Engine TM