A semantic segmentation algorithm of 3D model

This paper presents a semantic segmentation algorithm under the guidance of skeleton of 3D humanoid model. The algorithm is in two phase: (1) extract the skeleton of humanoid model; (2) identify the feature points of the extracted skeleton and segment the model according the key point employ the short-cut rule of cross section. Due to the complexity of calculating the general potential field, general potential field skeleton extraction algorithm is time consuming. In skeleton extraction stage a curve-skeleton extraction algorithm combining distance transform and potential field is used for less complexity computation. The algorithm is simply and easily operated and can segment the humanoid 3d model semantically.