DocumentCode
1956298
Title
A Solution to Efficient Viewpoint Space Partition in 3D Object Recognition
Author
Yu, Xiao ; Ma, Huimin ; You, Shaodi ; Yuan, Ze
Author_Institution
Dept. of Electron. Eng., Tsinghua Univ., Beijing, China
fYear
2009
fDate
20-23 Sept. 2009
Firstpage
565
Lastpage
570
Abstract
Viewpoint Space Partition based on Aspect Graph is one of the core techniques of 3D object recognition. Projection images obtained from critical viewpoint following this approach can efficiently provide topological information of an object. Computational complexity has been a huge challenge for obtaining the representation viewpoints used in 3D recognition. In this paper, we discuss inefficiency of calculation due to redundant nonexistent visual events; propose a systematic criterion for edge selection involved in EEE events. Pruning algorithm based on concave-convex property is demonstrated. We further introduce intersect relation into our pruning algorithm. These two methods not only enable the calculation of EEE events, but also can be implemented before viewpoint calculation, hence realizes view-independent pruning algorithm. Finally, analysis on simple representative models supports the effectiveness of our methods. Further investigations on Princeton Models, including airplane, automobile, etc, show a two orders of magnitude reduction in the number of EEE events on average.
Keywords
computational complexity; computational geometry; edge detection; graph theory; object recognition; 3D object recognition; EEE events; Princeton models; aspect graph; computational complexity; concave convex property; edge selection; magnitude reduction; projection images; pruning algorithm; viewpoint space partition; Airplanes; Automobiles; Computational complexity; Equations; Gaussian processes; Graphics; Object recognition; Partitioning algorithms; Shape; Topology; concave and convex property; object recognition; viewpoint space partition;
fLanguage
English
Publisher
ieee
Conference_Titel
Image and Graphics, 2009. ICIG '09. Fifth International Conference on
Conference_Location
Xi´an, Shanxi
Print_ISBN
978-1-4244-5237-8
Type
conf
DOI
10.1109/ICIG.2009.65
Filename
5437945
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