Semantics-based highlight extraction of soccer program using DBN

This paper proposes a novel semantics-based content analysis system for reliable media highlight extraction using dynamic Bayesian network (DBN). It extracts the low-level evidences and then converts the input video to high-level semantic meaning. Specific domains contain rich spatial and temporal transitional structures that help the transformation process. We introduce a robust audio-visual low-level evidence extraction scheme, and develop the so-called temporal intervening network to improve the performance of our system. In experiments, we show that our system can detect soccer events such as goal event, corner kick event, penalty kick event, and card event effectively.