Extracting representative motion flows for effective video retrieval |
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Authors: | Zhe Zhao Bin Cui Gao Cong Zi Huang Heng Tao Shen |
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Affiliation: | (1) State Key Laboratory of Software Development Environment & Department of Computer Science, Peking University, Beijing, China;(2) Nanyang Technological University, Nanyang, Singapore;(3) The University of Queensland, Queensland, Australia |
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Abstract: | In this paper, we propose a novel motion-based video retrieval approach to find desired videos from video databases through
trajectory matching. The main component of our approach is to extract representative motion features from the video, which
could be broken down to the following three steps. First, we extract the motion vectors from each frame of videos and utilize
Harris corner points to compensate the effect of the camera motion. Second, we find interesting motion flows from frames using
sliding window mechanism and a clustering algorithm. Third, we merge the generated motion flows and select representative
ones to capture the motion features of videos. Furthermore, we design a symbolic based trajectory matching method for effective
video retrieval. The experimental results show that our algorithm is capable to effectively extract motion flows with high
accuracy and outperforms existing approaches for video retrieval. |
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Keywords: | |
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