@INPROCEEDINGS{1012Glasberg2006,
	AUTHOR = {Ronald Glasberg and Cengiz Tas and Thomas Sikora},
	TITLE = {Recognizing Commercials in Real-Time using three Visual Descriptors and a Decision-Tree},
	BOOKTITLE = {IEEE 7th International Conference on Multimedia & Expo (ICME 2006)},
	YEAR = {2006},
	MONTH = jul,
	ADDRESS = {Toronto, Canada},
	PDF = {http://elvera.nue.tu-berlin.de/files/1012Glasberg2006.pdf},
	DOI = {10.1109/ICME.2006.262822},
	URL = {http://elvera.nue.tu-berlin.de/files/1012Glasberg2006.pdf},
	ABSTRACT = {We present a new approach for classifying mpeg-2 video sequences as "commercial" or "non-commercial" by analyzing specific color, texture and motion features of consecutive frames in real-time. This is part of the well-known video-genre-classification problem, where popular TV-broadcast genres like cartoon, commercial, music, news and sports are studied. Such applications have also been discussed in the context of MPEG-7. In our method the extracted features from three visual descriptors are logically combined using a decision tree to produce a reliable recognition. The results demonstrate a high identification rate based on a large collection of 200 representative video sequences (40 "commercials" and 4*40 "non-commercials") gathered from free digital TV-broadcasting in Germany.}
}