|Author(s)||Ronald Glasberg, Khalid Elazouzi, Thomas Sikora|
|Title||Cartoon-Recognition using Visual-Descriptors and a Multilayer-Perceptron|
|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 . 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.