A topological approach for segmenting human body shape

Yijun Xiao, N. Werghi, P. Siebert
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引用次数: 20

Abstract

Segmentation of a 3D human body, is a very challenging problem in applications exploiting human scan data. To tackle this problem, the paper proposes a topological approach based on the discrete Reeb graph (DRG) which is an extension of the classical Reeb graph to handle unorganized clouds of 3D points. The essence of the approach concerns detecting critical nodes in the DRG, thereby permitting the extraction of branches that represent parts of the body. Because the human body shape representation is built upon global topological features that are preserved so long as the whole structure of the human body does not change, our approach is quite robust against noise, holes, irregular sampling, frame change and posture variation. Experimental results performed on real scan data demonstrate the validity of our method.
人体形状分割的拓扑方法
在利用人体扫描数据的应用中,三维人体的分割是一个非常具有挑战性的问题。为了解决这一问题,本文提出了一种基于离散Reeb图(DRG)的拓扑方法,该方法是经典Reeb图的扩展,用于处理三维点的无组织云。该方法的本质是检测DRG中的关键节点,从而允许提取代表身体部分的分支。由于人体形状表征是建立在全局拓扑特征的基础上的,只要人体的整体结构不变,我们的方法对噪声、孔洞、不规则采样、帧变化和姿势变化都具有很强的鲁棒性。在实际扫描数据上的实验结果证明了该方法的有效性。
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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