基于表面及切向属性的点模型骨架提取方法

Skeleton Extraction Approach Based on the Attributes of Surface and Tangency for Point Models

针对目前在离散点云模型以及低分辨率模型上提取骨架算法存在的局限性,提出一种基于表面及切向属性(attributesofsurfaceandtangency,AST)的新方法.首先给出两个属性定义及其计算方式.然后基于上述属性通过表面光滑收缩和骨架吸引的双重作用达到模型的几何收缩,连接迭代收缩完成后得到的中心点,从而得到模型的骨架.实验表明:该方法得到的骨架能较好地表达原始模型的几何特征和拓扑结构,在缺少连接信息和低分辨率的情况下也能获得较好的骨架提取效果.

For the limitations of skeleton extraction on discrete point models and low-resolution models, this paper presents a novel skeleton extraction approach for point models based on the attributes of surface and tangency. Firstly, the definition and the calculating method of the two attributes are given. And then, geometry contraction is done by surface smooth contraction and skeleton attraction. Finally, the center points after iteration contraction are connected, and the skeleton of the model is obtained. Experiment results show that the skeleton extracted from this approach could express the geometry and topology of original model better. Even if the model lacks connection information and in low-resolution, the approach could also get good skeleton.