Event Mining and Indexing in Basketball Video

The video program has been produced by TV programs that were mass growing. How to recognize and to make sure the important events for indexing in video content management issues are become more and more important. In this paper, we developed a shot ontology description based for the basketball video. Shot ontology is inferred by shot manipulations those included: shot detection, shot type classification, score board detection and motion statistics. This video content management system provided event feature manipulations at multiple levels: signal, structural, or semantic in order to meet user preferences while striking the overall utility of the video. The experiment results showed that our proposed methodologies could correctly detect interested events, long shots, and close-up shots and also achieved the purpose of video indexing and weaving for what user preferences.