@INPROCEEDINGS{1180Glasberg2008,
	AUTHOR = {Ronald Glasberg and Sebastian Schmiedeke and Pascal Kelm and Thomas Sikora},
	TITLE = {An automatic system for real-time video-genres detection using high-level-descriptors and a set of classifiers},
	BOOKTITLE = {12th Annual IEEE International Symposium on Consumer Electronics, ISCE 2008, Algarve, Portugal},
	YEAR = {2008},
	MONTH = apr,
	EDITOR = {The International Symposium on Consumer Electronics (ISCE), Antonio Navarro},
	PUBLISHER = {IEEE Press},
	PAGES = {1--4},
	ORGANIZATION = {IEEE},
	ADDRESS = {Algarve, Portugal},
	NOTE = {oral presentation; eingereicht; ISBN 978-1-4244-2422-1},
	PDF = {http://elvera.nue.tu-berlin.de/files/1180Glasberg2008.pdf},
	DOI = {10.1109/ISCE.2008.4559449},
	ABSTRACT = {We present a new approach for classifying mpeg-2 video sequences as ‘cartoon’, ‘commercial’, ‘music’, ‘news’ or ‘sport’ by analyzing specific, high-level audio-visual features of consecutive frames in real-time. This is part of the well-known video-genre-classification problem, where popular TV-broadcast genres are studied. Such applications have also been discussed in the context of MPEG-7 [1]. In our method the extracted features are logically combined using a set of classifiers to produce a reliable recognition. The results demonstrate a high identification rate based on a large representative collection of 100 video sequences (20 sequences per genre) gathered from free digital TV-broadcasting in Europe.}
}