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