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X. Yang, X. Bai, L. J. Latecki and Z. Tu, “Improving Shape Retrieval by Learning Graph Transduction,” ECCV, 2008.

has been cited by the following article:

• TITLE: A Retrieval Matching Method Based Case Learning for 3D Model

  AUTHORS: Zhi Liu, Qihua Chen, Caihong Xu

  KEYWORDS: Case Learning-Based; Retrieval Matching; Similarity Matching

  JOURNAL NAME: Journal of Software Engineering and Applications, Vol.5 No.7, June 15, 2012

  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.