Topological segmentation of discrete human body shapes in various postures based on geodesic distance
Topological segmentation of discrete human body shapes in various postures based on geodesic distance
复制标题
基于测地距离的离散人体形状各种姿势的拓扑分割
DOI：
10.1109/icpr.2004.1334486
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发表时间：
2004
期刊：
影响因子：
--
通讯作者：
N. Werghi
中科院分区：
文献类型：
--
作者：
Yijun Xiao;P. Siebert;N. Werghi
本文基于一种新的Morse函数，即测地线距离，扩展了以前的Reeb图方法，将全身扫描数据分割成不同姿势下的主要身体部位。由于测地距离的弯曲不变性，所得到的Reeb图在很大的姿态范围内都能保持稳定。因此，该方法能够分割姿态范围内的数据。测地距离的应用也带来了坐标系选择的独立性。我们给出了在真实人体3D扫描样本和模拟数据集上进行的一些实验，以证明该方法的有效性。
This paper extends our previous Reeb graph approach based on a new Morse function, namely geodesic distance, to segment whole body scan data into primary body parts in various postures. Because of the bending invariance of geodesic distance, the resulting Reeb graph can remain stable in a large range of postures. Consequently, the approach is capable of segmenting data within the posture range. The application of geodesic distance also brings the independence of coordinate frame selection. We present a number of experiments conducted on both real body 3D scan samples and simulated datasets to demonstrate the validity of the approach.