Subsequence identification consists of 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. To cope with this problem, we propose a new approach, considering a bipartite graph matching to measure video clip similarity with a target video stream which has not been preprocessed. The main contributions of our work are the application of a simple and efficient distance to solve the subsequence identification problem along with the definition of a hit function that identifies precisely which operations were used in query transformation. Experimental results demonstrate that our method performances achieve 90% recall with 93% precision, though it is done without preprocessing of the target video.
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