AutoHighlight : Automatic Highlights Detection and Segmentation in Soccer Matches

More and more football fans prefer to watch football highlights because it takes too much time to watch the entire football game. At the same time, many TV stations and sports companies need to store and retrieve fragments of different events in football matches. The traditional way is to analyze and cut the football match manually. This method is time consuming and the process largely depends on personal choice, which results in unsecured accuracy. Therefore, it's necessary to develop a fast and accurate system for automatic summarization and analysis of football matches video. Automatic event detection and segmentation in football matches is about detecting specific event and extracting the related moments for football viewers and companies. This paper presents a deep learning based event detection and segmentation system for emphasizing specific events during football matches. The proposed system use live text of football matches as auxiliary information to segment the important event segmentation. We firstly use the deep learning model to tag each live text. Second, we merge successive live texts with the same label. Then we go to the football match to segment corresponding segmentation to the merged live text. Finally, if necessary, we run pure video based event detection model to these segmentation for finer grained segmentation. Experiments on real football matches show encouraging results. The proposed system greatly improves the accuracy and speed of segmentation.