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| Conference/Proceedings | Proc. of the 7th International Conference on Advanced Communication Technology (ICACT) |
| Start date | 21.02.2005 |
| End date | 23.02.2005 |
| Pages | 1121 - 1124 |
| Author(s) | Ronald Glasberg, Khalid Elazouzi, Thomas Sikora |
| Title | Video-genre-classification: recognizing cartoons in real-time using visual-descriptors and a multilayer-percetpron |
| Abstract | We present a new approach for classifying MPEG-2 video sequences as ‘cartoon’ or ‘non-cartoon’ by analyzing pecific color, texture and motion features of consecutive frames in real-time. This is part of the well-known ideo-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. 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 100 representative video sequences (20 cartoons and 4*20 non-cartoons) gathered from free digital TV-broadcasting. |
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