17 December 1998 Choosing efficient feature sets for video classification
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In this paper, we address the problem of choosing appropriate features to describe the content of still pictures or video sequences, including audio. As the computational analysis of these features is often time- consuming, it is useful to identify a minimal set allowing for an automatic classification of some class or genre. Further, it can be shown that deleting the coherence of the features characterizing some class, is not suitable to guarantee an optimal classification result. The central question of the paper is thus, which features should be selected, and how they should be weighted to optimize a classification problem.
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Stephan Fischer, Ralf Steinmetz, "Choosing efficient feature sets for video classification", Proc. SPIE 3656, Storage and Retrieval for Image and Video Databases VII, (17 December 1998); doi: 10.1117/12.333840; https://doi.org/10.1117/12.333840

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