Abstract
Video copy detection should be capable of identifying video copies subject to alterations e.g. in video contrast or frame rates. We propose a video copy detection scheme that allows for adaptable detection of videos that are altered temporally (e.g. frame rate change) and/or visually (e.g. change in contrast). Our query processing combines filtering and indexing structures for efficient multistep computation of video copies under this model. We show that our model successfully identifies altered video copies and does so more reliably than existing models.
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Assent, I., Kremer, H. (2009). Robust Adaptable Video Copy Detection. In: Mamoulis, N., Seidl, T., Pedersen, T.B., Torp, K., Assent, I. (eds) Advances in Spatial and Temporal Databases. SSTD 2009. Lecture Notes in Computer Science, vol 5644. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02982-0_25
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DOI: https://doi.org/10.1007/978-3-642-02982-0_25
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