Event detection in basketball video using multiple modalities

Semantic sports video analysis has attracted more and more attention recently. In this paper, we present a basketball event detection method by using multiple modalities. Instead of using low-level features, the proposed method is built upon visual and auditory mid-level features i.e. semantic shot classes and audio keywords. Promising event detection results have been achieved. By heuristically mapping semantic shot classes and by aligning audio keywords with semantic shot classes, we have been able to detect nine basketball events. Experimental results have shown our proposed method is effective for basketball event detection.