基于泊松形状信号的网格模型部件分割算法

为了将网格模型分割成若干个有意义的部件,提出了一种基于网格模型结构信号的分割算法.通过构造网格模型对应的体素模型,基于体素模型求解泊松方程得出每个体素对应的泊松形状信号;根据网格模型顶点与体素模型的对应关系,计算出网格模型中每个三角面片对应的泊松形状信号;采用Mean-Shift算法将每个三角面片对应的泊松形状信号进行聚类;最后基于泊松形状信号值,提取网格模型主要部件,并精化分块结果边界,从而达到网格模型部件分割的目的.实验表明,该算法能对具有部件结构特征的实体模型有较好的分割效果、鲁棒、速度快,与物体各个部件刚体变换无关.

Part segmentation algorithm for triangular mesh based on Poisson shape signature

A novel algorithm based on structure signature was proposed to segment triangular meshes into several meaningful part components.The corresponding volume for the input mesh was constructed and the Poisson solver with Dirichlet boundary condition was used to get each voxel's shape signature.The Poisson shape signature of each face in the mesh model was obtained based on the mapping relation between mesh vertices and voxels.The mean-shift algorithm could cluster the Poisson shape signature of each face.Based on the Poisson shape signature,the core part component was extracted,and the boundary between part components was refined.The experimental results show that the presented mesh segmentation algorithm can work well for the triangular meshes with part component structure,and is independent of the part rigid-transform.It is robust and efficient.