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A Retrieval Matching Method Based Case Learning for 3D Model
College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China
College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China
College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China
- 1 College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China
- 2 College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China
- 3 College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China
Journal of Software Engineering and Applications·Volume 05 (2012)·Pages 467–471·Published 27 July 2012·DOI10.4236/jsea.2012.57053
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Abstract
The similarity metric in traditional content based 3D model retrieval method mainly refers the distance metric algorithm used in 2D image retrieval. But this method will limit the matching breadth. This paper proposes a new retrieval matching method based on case learning to enlarge the retrieval matching scope. In this method, the shortest path in Graph theory is used to analyze the similarity how the nodes on the path between query model and matched model effect. Then, the label propagation method and k nearest-neighbor method based on case learning is studied and used to improve the retrieval efficiency based on the existing feature extraction.
KeywordsCase Learning-BasedRetrieval MatchingSimilarity Matching
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