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A two-step video subsequence identification based on bipartite graph matching

Subsequence identification consists in identifying real positions of a specific video clip in a video stream together with the operations that may be used to transform the former into a subsequence from the latter. In order to cope with this problem, we propose a two-step method. First, a clip filtering strategy based on the identification of dense segments is used, in order to decrease the number of video clip candidates. Then, for each dense segment, a graph matching approach is applied to identify video subsequences similar to the query video. Our main contribution is the use of a simple and efficient distance to solve subsequence identification problem along with the definition of a hit function that identifies precisely which operations were used in query transformation. Experimental results demonstrate good performance for our method (90% recall with 93% precision).