Human Body Segmentation Based on Shape Model and Level Set

Abstract

Human body segmentation is important for object tracking and recognition. When there are multiple human bodies, because of inter-occlusion, human body precise segmentation is difficult. A segmentation method based on prior shape model and level set is proposed. Human coarse shape models are constructed with position, scale and posture. For each human body, its corresponding human shape model is obtained by model matching by which position is obtained roughly after model matching, and object precise contour is obtained through curve evolution by multiphase level set with initial contour obtained from shape model. The proposed method could segment human object precisely.