View-based 3D object retrieval by bipartite graph matching

Yue Wen, Yue Gao, Richang Hong, Huanbo Luan, Qiong Liu, Jialie Shen, Rongrong Ji

Research output: Chapter in Book/Report/Conference proceedingConference Paper published in Proceedingspeer-review


Bipartite graph matching has been investigated in multiple view matching for 3D object retrieval. However, existing methods employ one-to-one vertex matching scheme while more than two views may share close semantic meanings in practice. In this work, we propose a bipartite graph matching method to measure the distance between two objects based on multiple views. In the proposed method, representative views are first selected by using view clustering for each object, and the corresponding weights are given based on the cluster results. A bipartite graph is constructed by using the two groups of representative views from two compared objects. To calculate the similarity between two objects, the bipartite graph is first partitioned to several subsets, and the views in the same sub-set are with high possibility to be with similar semantic meanings. The distances between two objects within individual subsets are then assembled through the graph to obtain the final similarity. Experimental results and comparison with the state-of-the-art methods demonstrate the effectiveness of the proposed algorithm.

Original languageEnglish
Title of host publicationMM 2012 - Proceedings of the 20th ACM International Conference on Multimedia
Place of PublicationNara, Japan
PublisherAssociation for Computing Machinery (ACM)
Number of pages4
ISBN (Print)9781450310895
Publication statusPublished - 26 Dec 2012
Externally publishedYes
Event20th ACM International Conference on Multimedia, MM 2012 - Nara, Japan
Duration: 29 Oct 20122 Nov 2012


Conference20th ACM International Conference on Multimedia, MM 2012


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