earticle

영어

Many soccer fans prefer to watch a summary of football games as watching a whole soccer match needs a lot of time. Traditionally, soccer videos were analyzed manually, however this costs valuable time. Therefore, it is necessary to have a tool for doing the video anal- ysis and summarization job automatically. Automatic soccer video summarization is about extracting important events from soccer matches in order to produce general summaries for the most important moments in which soccer viewers may be interested. This paper presents a machine learning (ML) based event detection and summarization system for em- phasizing important events during soccer matches. The proposed system rstly segments the whole video stream into small video shots, then it classies the resulted shots into dierent shot-type classes. Afterwards, the system applies two machine learning algorithms, namely; support vector machine (SVM) and articial neural network (ANN), for emphasizing impor- tant segments with logo appearance with addition to detecting the caption region providing information about the score of the game. Subsequently, the system detects vertical goal posts and goal net. Finally, the most important events during the match are highlighted in the resulted soccer video summary. Experiments on real soccer videos demonstrate encourag- ing results. The proposed approach greatly reduces workload and enhances the accuracy of summarizing soccer video matches with reference to both recall and precision performance measurement criteria.