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Posture-invariant statistical shape analysis using Laplace operator

 
 
Affiliation:
Information and Communication Technologies; National Research Council Canada; Information and Communication Technologies
Language:
English
Type:
Article
Published in:
Computers & Graphics
Date:
2012
Pages :
410-416
NPArC #:
20494939
Keywords:
statistical shape analysis; posture-invariant shape processing; Laplace operator
Program(s):
3D Imaging, Modeling and Visualization; Imagerie 3D, modélisation et visualisation
Group(s):
Visual Information Technology; Technologie de l'information visuelle
Abstract:
Statistical shape analysis is a tool that allows to quantify the shape variability of a population of shapes. Traditional tools to perform statistical shape analysis compute variations that reflect both shape and posture changes simultaneously. In many applications, such as ergonomic design applications, we are only interested in shape variations. With traditional tools, it is not straightforward to separate shape and posture variations. To overcome this problem, we propose an approach to perform statistical shape analysis in a posture-invariant way. The approach is based on a local representation that is obtained using the Laplace operator.
 
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