Abstract
Detection of commercials in TV videos is difficult because the diversity of them puts up a high barrier to construct an appropriate model. In this work, we try to deal with this problem through a top-down approach. We take account of the domain knowledge of commercial production and extract features that describe the characteristics of commercials. According to the clues from speech-music discrimination, video scene detection, and caption detection, a multi-modal commercial detection scheme is proposed. Experimental results show good performance of the proposed scheme on detecting commercials in news and talk show programs.
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Chen, JC., Yeh, JH., Chu, WT., Kuo, JH., Wu, JL. (2005). Improvement of Commercial Boundary Detection Using Audiovisual Features. In: Ho, YS., Kim, H.J. (eds) Advances in Multimedia Information Processing - PCM 2005. PCM 2005. Lecture Notes in Computer Science, vol 3767. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11581772_68
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DOI: https://doi.org/10.1007/11581772_68
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-30027-4
Online ISBN: 978-3-540-32130-9
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