| Summary: | 碩士 === 國立中央大學 === 資訊工程研究所 === 97 === This paper presents a practical highlight extraction and classification schemes for baseball videos. The approach relies on precise detections of transition effects inserted at the beginning and the end of the replays in the game, which demonstrate the game highlights. It is worth noting that the complexity of the highlight extraction procedure should be limited since it is an auxiliary function of a digital video recorder. Therefore, in the proposed system, the features of MPEG compressed videos are used for subsequent processing to archive efficiency. The properties of transition effects are exploited so that the effects can be accurately retrieved for locating the video segments of replays. Next, the pitching view, which is the starting point of every play in baseball games, will be extracted via Support Vector Machine (SVM). The contents of the play can then be analyzed and classified to determine their types or exciting levels. We classify the extracted highlight segments by using Hidden Markov model (HMM). Experimental results show that the accuracy is good enough to achieve the practical highlight extraction for baseball videos.
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