ENTROPY FEATURES TRAINED SUPPORT VECTOR MACHINE BASED LOGO DETECTION METHOD FOR REPLAY DETECTION AND EXTRACTION FROM SPORTS VIDEOS
Keywords:
Logo-based Detection, Support Vector Machine (SVM Learning (ML), Sports Replay Detection, Video SummarizationAbstract
In many sports, the majority of highlights are confined to relatively short durations of intense action. In some sense these segments capture the essence of a game and summarize the moments of important action. Automatic detection of these highlights could provide an important browsing mechanism in a video library of sports games. These replays often correspond to highlights in a game and can be used as indices of a sports video. The proposed mechanism employs support vector machine (SVM) for detection of logos that are flashed at beginning and end of every reply action. The algorithm is composed of logos detection and replay segment extraction. First SVM is trained with features of all possible logos normally used in various sports videos. Then the SVM is used for detection of logos that sandwich replay segment further that segment is automatically extracted to produce replay clip. The SVM classifier is trained with histogram features of logos is utilized. Experiments conducted on IPL and Soccer videos demonstrate the effectiveness of this method. Moreover, algorithm can be easily applied to other sports videos where replay is sandwiched by pair of logos.
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Copyright (c) 2020 Vilas Naik, Raghavendra Havin (Author)
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