Semantic event extraction from basketball games using multi-modal analysis

In this paper, we present a novel multi-modal framework for se-mantic event extraction from basketball games based on web-casting text and broadcast video. We propose novel approaches to text analysis for event detection and semantics extraction, video analysis for event structure modeling and event moment detection, and text/video alignment for event boundary detection in the video. Compared with existing approaches to event detection in sports video which rely heavily on low-level features directly extracted from video itself, our approach aims to bridge the semantic gap between low-level features and high-level events and facilitates personalization of the sports video. Promising results are reported on real-world video clips by using text analysis, video analysis and text/video alignment. 1