Local Diffusion Map Signature for Symmetry-aware Non-rigid Shape Correspondence

M. Wang, Yi Fang
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引用次数: 2

Abstract

Identifying accurate correspondences information among different shapes is of great importance in shape analysis such as shape registration, segmentation and retrieval. This paper aims to develop a paradigm to address the challenging issues posed by shape structural variation and symmetry ambiguity. Specifically, the proposed research developed a novel shape signature based on local diffusion map on 3D surface, which is used to identify the shape correspondence through graph matching process. The developed shape signature, named local diffusion map signature (LDMS), is obtained by projecting heat diffusion distribution on 3D surface into 2D images along the surface normal direction with orientation determined by gradients of heat diffusion field. The local diffusion map signature is able to capture the concise geometric essence that is deformation-insensitive and symmetry-aware. Experimental results on 3D shape correspondence demonstrate the superior performance of our proposed method over other state-of-the-art techniques in identifying correspondences for non-rigid shapes with symmetry ambiguity.
对称感知非刚性形状对应的局部扩散映射签名
在形状配准、分割和检索等形状分析中,准确识别不同形状之间的对应信息具有重要意义。本文旨在建立一种范式来解决形状结构变化和对称模糊所带来的挑战性问题。具体而言,本研究提出了一种基于三维表面局部扩散图的形状特征,通过图匹配过程识别形状对应关系。将三维表面上的热扩散分布沿表面法线方向投影到二维图像上,由热扩散场的梯度决定其方向,得到的形状特征称为局部扩散图特征(LDMS)。局部扩散图签名能够捕捉到形变不敏感和对称敏感的简洁几何本质。三维形状对应的实验结果表明,我们提出的方法在识别具有对称模糊的非刚性形状对应方面优于其他最先进的技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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