Abstract
A large amount of digital video data is stored in local or network visual retrieval systems. The new technology advances in multimedia information processing as well as in network transmission have made video data publicly and relatively easy available. Users need the adequate tools to locate their desired video or video segments quickly and efficiently, for example in Internet video collections, TV shows archives, video-on-demand systems, personal video archives offered by many public Internet services, etc. Detection of scenes in TV videos is difficult because the diversity of effects used in video editing puts up a barrier to construct an appropriate model. The framework of automatic recognition and classification of scenes reporting the sport events in a given discipline in TV sports news have been proposed. Experimental results show good performance of the proposed scheme on detecting scenes on a given sport discipline in TV sports news. In the tests a special software called AVI – the Automatic Video Indexer has been used to detect shots and then scenes in tested TV news videos.
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Choroś, K., Pawlaczyk, P. (2010). Content-Based Scene Detection and Analysis Method for Automatic Classification of TV Sports News. In: Szczuka, M., Kryszkiewicz, M., Ramanna, S., Jensen, R., Hu, Q. (eds) Rough Sets and Current Trends in Computing. RSCTC 2010. Lecture Notes in Computer Science(), vol 6086. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13529-3_14
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DOI: https://doi.org/10.1007/978-3-642-13529-3_14
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