Abstract
In this paper, we propose a novel 3D object retrieval with features collaboration and bipartite graph matching strategies. We explored the essential characters of 3D object in a view-based retrieval framework, which extracts complement descriptors from both the contour and the interior region of 3D object effectively. Specifically, a greedy bipartite graph matching algorithm is employed. With the bipartite graph matching and feature concatenation, significant performance improvement is achieved in the 3D object retrieval task. The proposed method is evaluated by the third party on the data set comprising more than 500 3D objects and achieves the best performance for SHREC’15 challenge.
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