@INPROCEEDINGS{0743Glasberg2005,
	AUTHOR = {Ronald Glasberg and Amjad Samour and Khalid Elazouzi and Thomas Sikora},
	TITLE = {Cartoon-Recognition using Video & Audio-Descriptors},
	BOOKTITLE = {EUSIPCO},
	YEAR = {2005},
	MONTH = sep,
	ADDRESS = {Antalya, Turkey},
	PDF = {http://elvera.nue.tu-berlin.de/files/0743Glasberg2005.pdf},
	URL = {http://elvera.nue.tu-berlin.de/files/0743Glasberg2005.pdf},
	ABSTRACT = {We present a new approach for classifying mpeg-2 video sequences as ‘cartoon’ or ‘non-cartoon’ by analyzing specific video and audio 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 [12]. In our method the extracted features from the visual descriptors are non-linearly combined using a multilayered perceptron and then considered together with the output of the audio-descriptor to produce a reliable recognition. The results demonstrate a high identification rate based on a large collection of 100 representative video sequences (20 cartoons and 4*20 non-cartoons) gathered from free digital TV-broadcasting.}
}