Skeleton-based human segmentation in still images

In this paper we propose a skeleton-based model for human segmentation in static images. Our approach explores edge information, orientation coherence and anthropometric-estimated parameters to generate a graph, and the desired contour is a path with maximal cost. Experimental results show that the proposed technique works well in non trivial images.