@inproceedings{0eb1765f47754e7092b24a53bce22032,
title = "Improvement of commercial boundary detection using audiovisual features",
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.",
author = "Chen, \{Jun Cheng\} and Yeh, \{Jen Hao\} and Chu, \{Wei Ta\} and Kuo, \{Jin Hau\} and Wu, \{Ja Ling\}",
year = "2005",
doi = "10.1007/11581772\_68",
language = "English",
isbn = "3540300279",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "776--786",
booktitle = "Advances in Mulitmedia Information Processing - PCM 2005 - 6th Pacific Rim Conference on Multimedia, Proceedings",
note = "6th Pacific Rim Conference on Multimedia - Advances in Mulitmedia Information Processing - PCM 2005 ; Conference date: 13-11-2005 Through 16-11-2005",
}