Abstract
Near-duplicate video clip(NDVC) detection is a special issue of content-based video search. Identifying the videos derived from the same original source is the primary task of this research. In NDVC detection, an important step is to define an effective similarity measure that captures both frame and sequence information inherent to the video clips. To address this, in this paper, we propose a new similarity measure, named as Video Edit Distance(VED), that adopts a complementary information compensation scheme based on the visual features and sequence context of videos. Visual features contain the discriminative information of each video, and sequence context captures the feature variation of it. To reduce the computation cost of inter-video comparison by VED, we extract key frames from video sequences and map each key frame into one single symbol. Various techniques are proposed to compensate the information loss in the measurement. Experimental results demonstrate that the proposed measure is highly effective.
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Zhou, X., Zhou, X., Shen, H.T. (2007). A New Similarity Measure for Near Duplicate Video Clip Detection. In: Dong, G., Lin, X., Wang, W., Yang, Y., Yu, J.X. (eds) Advances in Data and Web Management. APWeb WAIM 2007 2007. Lecture Notes in Computer Science, vol 4505. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72524-4_21
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DOI: https://doi.org/10.1007/978-3-540-72524-4_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-72483-4
Online ISBN: 978-3-540-72524-4
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