@INPROCEEDINGS{1182Glasberg2008,
	AUTHOR = {Ronald Glasberg and Sebastian Schmiedeke and Hüseyin Oguz and Pascal Kelm and Thomas Sikora},
	TITLE = {Real-Time Detection of Sport in MPEG-2 Sequences using High-Level AV-Descriptors and SVM},
	BOOKTITLE = {Third International Conference on Digital Information Management, ICDIM November 13-16, 2008, London, UK},
	YEAR = {2008},
	MONTH = nov,
	EDITOR = {IEE, Richard Chbeir},
	PUBLISHER = {IEEE},
	ORGANIZATION = {IEEE},
	ADDRESS = {London, UK},
	NOTE = {oral presentation   ;   eingereicht   ;   ISBN 978-1-4244-2917-2   ;   TACD//-ICDIM-08},
	PDF = {http://elvera.nue.tu-berlin.de/files/1182Glasberg2008.pdf},
	URL = {http://elvera.nue.tu-berlin.de/files/1182Glasberg2008.pdf},
	ABSTRACT = {We present a new approach for classifying mpeg-2 video sequences as ‘sport’ or ‘non-sport’ by analyzing new high-level audiovisual 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 video, news and sports are studied. Such applications have also been discussed in the context of MPEG-7 [1]. In our method the extracted features are logically combined by a support vector machine [2] to produce a reliable detection. The results demonstrate a high identification rate of 98.5% based on a large balanced database of 100 representative video sequences gathered from free digital TV-broadcasting and world wide web.}
}