A similarity measure between videos using alignment, graphical and speech features
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 feature...
| Authors: | , , , |
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| Format: | article |
| Status: | Published version |
| Publication Date: | 2012 |
| Country: | España |
| Institution: | Universidad de Sevilla (US) |
| Repository: | idUS. Depósito de Investigación de la Universidad de Sevilla |
| OAI Identifier: | oai:idus.us.es:11441/142692 |
| Online Access: | https://hdl.handle.net/11441/142692 https://doi.org/10.1016/j.eswa.2012.02.169 |
| Access Level: | Open access |
| Keyword: | Information retrieval Content segmentation Bipartite matching |
| Summary: | 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. |
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