Human body segmentation in static images by models with shape as guidance.

In this paper, a hierarchical method for human body segmentation in static images is proposed. Based on the face detection, a torso model is developed to locate the torso to provide the foreground seeds for torso segmentation with graph cuts. Similarly, an upper leg model is designed for lower body segmentation based on the segmented torso. Besides, a general method which combines shape information into graph cuts is presented, which can make the segmentation more accurate. The main contributions of this paper include two models and a new method of integrating shape information into graph cuts. Experiments on our collected real world images show that our method can accurately recover human body from static images with a variety of individuals, poses, backgrounds and clothing. (c) 2017 Elsevier B.V. All rights reserved.