DocumentCode :
3410150
Title :
Convex shape decomposition
Author :
Liu, Hairong ; Liu, Wenyu ; Latecki, Longin Jan
Author_Institution :
Huazhong Univ. of Sci. & Technol., Huazhong, China
fYear :
2010
fDate :
13-18 June 2010
Firstpage :
97
Lastpage :
104
Abstract :
In this paper, we propose a new shape decomposition method, called convex shape decomposition. We formalize the convex decomposition problem as an integer linear programming problem, and obtain approximate optimal solution by minimizing the total cost of decomposition under some concavity constraints. Our method is based on Morse theory and combines information from multiple Morse functions. The obtained decomposition provides a compact representation, both geometrical and topological, of original object. Our experiments show that such representation is very useful in many applications.
Keywords :
approximation theory; image segmentation; integer programming; linear programming; shape recognition; Morse theory; concavity constraints; convex shape decomposition; image segmentation; integer linear programming problem; Cost function; Data mining; Image edge detection; Image processing; Image segmentation; Integer linear programming; Motion detection; Q measurement; Shape; Topology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on
Conference_Location :
San Francisco, CA
ISSN :
1063-6919
Print_ISBN :
978-1-4244-6984-0
Type :
conf
DOI :
10.1109/CVPR.2010.5540225
Filename :
5540225
Link To Document :
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