Abstract
In order to monitor video streams in real-time or search large collections of video documents, several solutions based on near-duplicate video detection have been proposed in the literature. We present in this paper an architecture based on signature-based index structures coupling visual and temporal features and on an N-gram matching and scoring framework. The techniques we cover are robust and insensitive to general video editing and/or degradation, making it ideal for re-broadcasted video search. Through the use of signature-based indexing and N-gram matching and scoring, we identify corresponding query and index contents accurately in order to detect near-duplicate videos, even when these contents constitute only a small section of the videos being compared. Experiments are carried out on large quantities of video data collected from the TRECVID 02, 03 and 04 collections and real-world video broadcasts recorded from two German TV stations. An empirical comparison over two state-of-the-art dynamic programming techniques is encouraging and demonstrates the advantage and feasibility of our method.
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Tahayna, B., Belkhatir, M. (2008). An Efficient Method for Near-Duplicate Video Detection. In: Huang, YM.R., et al. Advances in Multimedia Information Processing - PCM 2008. PCM 2008. Lecture Notes in Computer Science, vol 5353. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-89796-5_39
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DOI: https://doi.org/10.1007/978-3-540-89796-5_39
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