Improvement of Commercial Boundary Detection Using Audiovisual Features

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.