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Real-Time Detection of Sport in MPEG-2 Sequences using High-Level AV-Descriptors and SVM
Citation key 1182Glasberg2008
Author Ronald Glasberg and Sebastian Schmiedeke and Hüseyin Oguz and Pascal Kelm and Thomas Sikora
Title of Book Third International Conference on Digital Information Management, ICDIM November 13-16, 2008, London, UK
Year 2008
Address London, UK
Month nov
Note oral presentation ; eingereicht ; ISBN 978-1-4244-2917-2 ; TACD//-ICDIM-08
Editor IEE, Richard Chbeir
Publisher IEEE
Organization IEEE
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.
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