Motion retrieval based on graph matching and revised Kuhn-Munkres algorithm

In this paper, we propose a content-based motion retrieval algorithm, where many-to-many matching method, weighted graph matching, is employed for comparison between two motions. In this work, each motion is represented by a set of sequence frames. Representative frames are first selected from the motions and the corresponding initial weights are provided. The weighted graph is built with these selected frames, and a revised KM (Kuhn-Munkres) algorithm is used to solve maximum matching problem of weighted graph. The 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.