Spatio-Temporal 2D Model Framework for Human Motion Analysis with a Monocular Static Camera

Abstract. We use a common static background subtraction algorithm to perform foreground detection and propose a model-based approach associating the body pose and the 2D silhouette to jointly segment and recover the pose of the subject observed in the scene. To cope with viewpoint and out-of plane rotation, local spatio-temporal models corresponding to several views and steps of the same action are trained, concatenated and sorted in a global framework. Temporal and spatial constraints are then considered to select the most probable models at each time step. The experiments carried out on indoor and outdoor sequences have demonstrated the ability of this approach to adequately segment walking pedestrians and estimate their poses independently of the direction of motion.

Keywords. Monocular Human Pose Analysis, Segmentation, Model Based, Torus Manifold.