An unsupervised shot classification system for news video story detection

Automatic classification of shots extracted by news video plays an important role in the context of news video segmentation, which is an essential step towards effective indexing of broadcasters' digital databases. In this paper, we propose a system for news video story detection based on an unsupervised shot classification system. Since it is always possible to find a case in which the assumptions of a single shot classification technique fail, in our system shot classification is performed by means of a multi-expert approach. In order to assess the performance of the proposed system, we built up a database significantly wider than those typically used in the field. Experimental results demonstrate the effectiveness of the proposed approach both in terms of shot classification and of news story detection capability.