Structure in soccer videos: Detecting and classifying highlights for automatic summarization

We propose an automatic framework to detect and classify highlights directly from soccer videos. Sports videos are amongst the most important events for TV transmissions and journalism, however for the purpose of archiving, reuse for sports analysts and coaches, and of main interest to the audience, the considered highlights of the match should be annotated and saved separately. This procedure is done manually by many assistants watching the match from a video. In this paper we develop an automatic framework to perform such a summarization of a soccer video using object-based features. The highlights of a soccer match are defined as shots towards any of the two goal areas, i.e. plays that have already passed the midfield area. Novel algorithms are presented to perform shot classification as long distance shot and others, highlights detection based on object-based features segmentation, and highlights classification for complete summarization of the event. Experiments are reported for complete soccer matches transmitted by TV stations in Brazil, testing for different illumination (day and night), different stadium fields, teams and TV broadcasters.