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高斯曲率约束的MRG骨架提取优化算法

Gaussian Curvature Constrained Skeleton Extraction Method Based on MRG

  • 摘要: 三维模型的骨架保持了模型的拓扑特性,并被广泛应用于模型相似性比较、计算机动画及压缩等领域.根据多分辨率Reeb图的原理,提出了一种基于离散高斯曲率约束的骨架提取优化算法.通过计算网格顶点的离散高斯曲率判断曲面局部凸凹特性,以获取模型表面的双曲极值点作为约束点;并依据约束点及其邻域的μ函数值产生的分裂线进行区域细分,获得子连通区域、确定关节点、形成优化的骨架结构.实验结果表明,该算法有效地突出了模型的拓扑分支特征以及模型表面的细节,提高了骨架提取的精度和效率.

     

    Abstract: Skeleton representation of 3D models has been widely used for shape similarity comparison,character animation and data compression. This paper presents an optimized skeleton extraction approach by using discrete Gaussian curvature to refine the multi-resolution Reeb graph generation. It first calculates the Gaussian curvature of each vertex which clarifies the convex and concave feature of the local surface. By taking the concave point as constrained points,sub-splitting-lines are generated according to their μ values. A local subdivision method is then adopted to get the sub-regions and the new nodes. The skeleton is finally formed by connecting all the nodes. This optimized skeleton keeps the topological and local features of 3D model very well. A series of experiments demonstrated its efficiency.

     

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