Sports video analysis and structuring
We propose a new method for structuring and analyzing sports video through clustering of video shots based on low-level visual content. The dominant scenes of a sports video are first automatically extracted by using the color features derived from its video shots. The video shots belonging to each dominant scene are then processed to identify interesting play events in the sports video. To reduce the influence of threshold selection on the results, different forms of shot color features, including shot color histogram and its principal component and subspace linear discriminant representations, are also examined. Experimental results on various kinds of sports videos, such as tennis, volleyball, basketball and football videos, are presented to demonstrate the effectiveness of the proposed method.