Benchmarking graph-based clustering algorithms
Image and Vision Computing
A graph-based clustering method and its applications
BVAI'07 Proceedings of the 2nd international conference on Advances in brain, vision and artificial intelligence
Automatic indexing of news videos through text classification techniques
ICAPR'05 Proceedings of the Third international conference on Pattern Recognition and Image Analysis - Volume Part II
Combining audio-based and video-based shot classification systems for news videos segmentation
MCS'05 Proceedings of the 6th international conference on Multiple Classifier Systems
Anchor shot detection with diverse style backgrounds based on spatial-temporal slice analysis
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
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Automatic classification of shots extracted by news videos plays an important role in the context of news video segmentation, which is an essential step towards effective indexing of broadcasters’ digital databases. In spite of the efforts reported by the researchers involved in this field, no techniques providing fully satisfactory performance have been presented until now. In this paper, we propose a multi-expert approach for unsupervised shot classification. The proposed multi-expert system (MES) combines three algorithms that are model-free and do not require a specific training phase. In order to assess the performance of the MES, 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.