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Cartoon-Recognition using Visual-Descriptors and a Multilayer-Perceptron
Citation key 0748Glasberg2005
Author Ronald Glasberg and Khalid Elazouzi and Thomas Sikora
Title of Book WIAMIS
Year 2005
Address Montreux
Month apr
Abstract sequences as ‘cartoon’ or ‘non-cartoon’ by analyzing specific color, texture and motion features of consecutive frames in real-time. This is part of the well-known videogenre-classification problem, where popular TVbroadcast 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 nonlinear weighted with a sigmoid-function and afterwards combined using a multilayered perceptron to produce a reliable recognition. The results demonstrate a high identification rate based on a large collection of 200 representative video sequences (40 cartoons and 4*40 non-cartoons) gathered from free digital TV-broadcasting in Germany.
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