Joint labelling and segmentation for 3D scanned human body

In this paper, we present an approach to perform 3D human body labelling and segmentation jointly. Given a 3D mesh of scanned human body with texture, our approach segments it into 5 parts: head, torso, arms, legs and feet automatically. We assume that the faces on the same part of human body share similar color features and are constrained by geometry. According to this assumption, we formulate the labelling and segmentation of 3D Mesh as an energy function optimization problem. In this energy function, a data term models the color information and a smooth term models the geometry constraint. Then a GraphCut algorithm is applied to solve the optimization problem. The experiment results show good performance of our method.