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. © Springer-Verlag Berlin Heidelberg 2005.
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CITATION STYLE
Chen, J. C., Yeh, J. H., Chu, W. T., Kuo, J. H., & Wu, J. L. (2005). Improvement of commercial boundary detection using audiovisual features. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3767 LNCS, pp. 776–786). https://doi.org/10.1007/11581772_68
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