A Graph-Based Matching Algorithm on Sub-Sequence of Near Duplicated Video

Abstract

As to solving the effectiveness and efficiency problem in the process of detecting the near duplicated video, we the thesis proposes a graph-based matching algorithm on sub-sequence of near duplicated video. The method will built similarity researching results based on the features of key frames feature into the query matching diagram, and then the near duplicated video detection is converted into a problem of searching the longest path in the matching results graph. As for its main advantage, firstly, it can find the best matching sequence in many cluttered matching results, which can effectively exclude a lot of noises brought by certain false “high similarity” matching, thus to some extent it can compensate the deficiencies of the underlying characterization force. Secondly, because it fully understands and uses the timing characteristics of the video sequences, the positioning accuracy of near duplicated video is with a high degree. Finally, multiple discrete paths existing in the matching results graphs are automatically detected, thus the situation where two video segments may exist several near duplicated videos can be detected once time. Experimental results show that the graph-based matching algorithm on video sub sequence improve the detection accuracy, at the same time improve the detection efficiency, which achieved good practice effect.