基于内部球的三维模型逼近与聚类

3D Model Approximation and Clustering Based on Inner Spheres

为了实现物体间的快速碰撞检测,提出一种三维模型球体逼近表示方法.首先在三维模型体素化基础上构建了模型内部球逼近,以改进内部球数目和球体连续性效果;接着通过基于测地距离的改进计算对内部球进行聚类,得到有意义的分类结果,可用于模型内部球的层次结构树构造和模型语义分割等.实验结果表明,该方法是可行和有效的.

To realize the fast collision detection between objects, a sphere approximation representation for 3D models is proposed in this paper. It firstly presents a novel 3D model approximation method with inner spheres based on three-dimensional model voxelization. It also reduces the number of inner spheres and enhances the sphere connectivity. Then this approach improves the inner sphere clustering based on the geodesic distance. It obtains meaningful clustering results which can be applied in many applications such as the structure construction of hierarchical inner sphere-trees and the semantic segmentation of 3D models. Experimental results demonstrate the feasibility and effectiveness of this method.