DocumentCode :
3439486
Title :
Topological segmentation of discrete human body shapes in various postures based on geodesic distance
Author :
Xiao, Yijun ; Siebert, Paul ; Werghi, Naoufel
Author_Institution :
Dept. of Comput. Sci., Glasgow Univ., UK
Volume :
3
fYear :
2004
fDate :
23-26 Aug. 2004
Firstpage :
131
Abstract :
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.
Keywords :
differential geometry; graph theory; pattern recognition; Morse function; Reeb graph; discrete human body shapes; geodesic distance; human body postures; real body 3D scan; topological segmentation; Area measurement; Biological system modeling; Clouds; Commercialization; Educational institutions; Geophysics computing; Humans; Information technology; Shape; Time measurement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on
ISSN :
1051-4651
Print_ISBN :
0-7695-2128-2
Type :
conf
DOI :
10.1109/ICPR.2004.1334486
Filename :
1334486
Link To Document :
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