| Summary: | 碩士 === 國立中央大學 === 資訊工程研究所 === 98 === This research presents a system of analyzing video content in the MPEG compressed videos for classifying the highlights in baseball videos. The system makes use of the transition e ects inserted preceding and following the slow motion replays by the broadcaster, which demonstrate highlights of the game. First, we examine the characteristics of the tran-
sition e ects via the camera changes and the video content analysis to construct the transition e ect template, which can help to locate all the appearances of transition e ects. Next, we search the pitching views which appear before the transition e ects and construct the pitching view model for this game. Finally, after we locate the highlight candidates, we will apply HMM (Hidden Markov Model) to analyze and classify the content to ensure that the extracted highlights match our de nitions of high-level highlight semantics. Because the system is based on MPEG
compressed video data streams, it can save a large amount of computational complexity. The experimental results show the feasibility of the potential solution.
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