A probabilistic template-based approach to discovering repetitive patterns in broadcast videos

Peng Wang, Zhi-Qiang Liu, Shi-Qiang Yang
2005 Proceedings of the 13th annual ACM international conference on Multimedia - MULTIMEDIA '05  
There are usually repetitive sub-segments in broadcast videos, which may be associated with high-level concepts or events, e.g., news footage, repeated scores in basketball. Unsupervised mining techniques provide generic solutions to discovering such temporal patterns in various video genres, which are currently the subject of great interests to researchers working on multimedia content analysis. In this paper, we propose a novel approach to automatically detecting repetitive patterns in a
more » ... stream. In this approach, a video stream is first transformed to a symbol sequence via the spectral clustering algorithm. After computing the transition probabilities of any two symbols in temporal evolution, we produce a set of probabilistic templates to characterize the patterns of potential interest. Finally, we verify each probabilistic template by measuring the similarities between the video subsegments and the template. Evaluations on various sports videos show promising results.
doi:10.1145/1101149.1101238 dblp:conf/mm/WangLY05 fatcat:lhri6pexzvh7jhjvbnbkcmth24