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A similarity measure between videos using alignment, graphical and speech features

By D. Fuentes, R. Bardeli, J.A. Ortega and L. Gonzalez-Abril

Abstract

A novel video similarity measure is proposed by using visual features, alignment distances and speech transcripts. First, video files are represented by a sequence of segments each of which contains colour histograms, starting time, and a set of phonemes. After, textual, alignment and visual features are extracted of these segments. The following step, bipartite matching and statistical features are applied to find correspondences between segments. Finally, a similarity is calculated between videos. Experiments have been carried out and promising results have been obtained

Topics: information retrieval, content segmentation, bipartite matching
Year: 2012
DOI identifier: 10.1016/j.eswa.2012.02.169
OAI identifier: oai:fraunhofer.de:N-206235
Provided by: Fraunhofer-ePrints
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