Abstract
In this paper, we propose a content-based motion retrieval (CBMR) algorithm, where many-to-many matching method, weighted graph matching, is employed for comparison between two motions. Our novel points can be described as: (1) A selection approach of representative frames (RF) is presented, in this work, each motion is represented by a set of sequence frames, representative frames are first selected from the motions based on Fuzzy clustering and the corresponding initial weights are provided. (2) The RF-based weighted graph model (RF-WGM) is constructed, and a revised KM (Kuhn–Munkres) algorithm is used to solve maximum matching problem of weighted graph. The RF-WGM matching result is used to measure the similarity between two motions. Experimental results and comparison with existing methods show the effectiveness of the proposed algorithm.
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Acknowledgments
This work was supported by NSFC (No. 60972095, 61271362), Shanxi Province Natural Science Foundation (No. 2012JM8028) and Shanxi Province Education Department Specialized Research Foundation (No. 12JK0510, 12JK0727).
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Communicated by M.J. Watts.
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Xiao, Q., Wang, Y. & Wang, H. Motion retrieval using weighted graph matching. Soft Comput 19, 133–144 (2015). https://doi.org/10.1007/s00500-014-1237-5
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DOI: https://doi.org/10.1007/s00500-014-1237-5