Abstract
In this paper we present a novel algorithm for anchor shot detection (ASD). ASD is a fundamental step for segmenting news video into stories that is among key issues for achieving efficient treatment of news-based digital libraries. The proposed algorithm creates a set of audio/video templates of anchorperson shots in an unsupervised way, then classifies shots by comparing them to the templates. Audio similarity is evaluated by means of a new index and helps to achieve better performance than a pure video approach. The method has been tested on a wide database and compared with other state-of-the-art algorithms, demonstrating its effectiveness with respect to them. © Springer-Verlag Berlin Heidelberg 2006.
Cite
CITATION STYLE
D’Anna, L., Marrazzo, G., Percannella, G., Sansone, C., & Vento, M. (2006). A multi-stage approach for anchor shot detection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4109 LNCS, pp. 773–782). Springer Verlag. https://doi.org/10.1007/11815921_85
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