Abstract
Video broadcast series like news or magazine broadcasts usually expose a strong temporal structure, along with a characteristic audio-visual appearance. This results in frequent patterns occurring in the video signal. We propose an algorithm for the automatic detection of such patterns that exploits the video’s self-similarity induced by the patterns. The approach is applied to the problem of anchor shot detection, but can also be used for other related purposes. Tests on real-world video data show that it is possible with our method to detect anchor shots fully automatically with high reliability.
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Jacobs, A. (2006). Using Self-similarity Matrices for Structure Mining on News Video. In: Antoniou, G., Potamias, G., Spyropoulos, C., Plexousakis, D. (eds) Advances in Artificial Intelligence. SETN 2006. Lecture Notes in Computer Science(), vol 3955. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11752912_11
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DOI: https://doi.org/10.1007/11752912_11
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34117-8
Online ISBN: 978-3-540-34118-5
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