Human Body Detection Using Multi-Scale Shape Contexts

In this paper, we propose a prototype-based human detection approach using shape information. Multi-scale shape contexts descriptor is utilized to model the shapes in the procedure of human body detection. As a partial shape presentation, it is capable of modeling shapes and measuring their similarity at different scale. The multi-scale shape contexts help human detection own robustness to the variations result from noise, illumination, movement, and clutter in image. The approach consists of two steps: An edge detector is firstly performed to acquire the edges; the multi-scale shape contexts are then applied to find human body in the edges based on the similarities between the edges and a predefined human body prototype. Experimental results demonstrate the advantage of the proposed approach.