Shot retrieval based on fuzzy evolutionary aiNet and hybrid features


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LI, Xiang-Hui, Yong-Zhao ZHAN, Jia KE, Hong-Wei ZHENG, 2011. Shot retrieval based on fuzzy evolutionary aiNet and hybrid features. In: Computers in Human Behavior. 27(5), pp. 1571-1578. ISSN 0747-5632. Available under: doi: 10.1016/j.chb.2010.11.002

@article{Li2011retri-16627, title={Shot retrieval based on fuzzy evolutionary aiNet and hybrid features}, year={2011}, doi={10.1016/j.chb.2010.11.002}, number={5}, volume={27}, issn={0747-5632}, journal={Computers in Human Behavior}, pages={1571--1578}, author={Li, Xiang-Hui and Zhan, Yong-Zhao and Ke, Jia and Zheng, Hong-Wei} }

<rdf:RDF xmlns:dcterms="" xmlns:dc="" xmlns:rdf="" xmlns:bibo="" xmlns:dspace="" xmlns:foaf="" xmlns:void="" xmlns:xsd="" > <rdf:Description rdf:about=""> <dc:creator>Zhan, Yong-Zhao</dc:creator> <dc:creator>Ke, Jia</dc:creator> <dcterms:available rdf:datatype="">2012-09-30T22:25:05Z</dcterms:available> <dspace:isPartOfCollection rdf:resource=""/> <dcterms:bibliographicCitation>Computers in Human Behavior ; 27 (2011), 5. - S. 1571-1578</dcterms:bibliographicCitation> <dc:date rdf:datatype="">2011-11-08T17:12:49Z</dc:date> <dc:creator>Zheng, Hong-Wei</dc:creator> <dc:contributor>Li, Xiang-Hui</dc:contributor> <dcterms:isPartOf rdf:resource=""/> <dcterms:rights rdf:resource=""/> <dcterms:abstract xml:lang="eng">As the multimedia data increasing exponentially, how to get the video data we need efficiently become so important and urgent. In this paper, a novel method for shot retrieval is proposed, which is based on fuzzy evolutionary aiNet and hybrid features. To begin with, the fuzzy evolutionary aiNet algorithm proposed in this paper is utilized to extract key-frames in a video sequence. Meanwhile, to represent a key-frame, hybrid features of color feature, texture feature and spatial structure feature are extracted. Then, the features of key-frames in the same shot are taken as an ensemble and mapped to high dimension space by non-linear mapping, and the result obeys Gaussian distribution. Finally, shot similarity is measured by the probabilistic distance between distributions of the key-frame feature ensembles for two shots, and similar shots are retrieved effectively by using this method. Experimental results show the validity of this proposed method.</dcterms:abstract> <bibo:uri rdf:resource=""/> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dc:creator>Li, Xiang-Hui</dc:creator> <dc:contributor>Ke, Jia</dc:contributor> <dcterms:hasPart rdf:resource=""/> <dc:rights>terms-of-use</dc:rights> <dcterms:issued>2011</dcterms:issued> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dcterms:title>Shot retrieval based on fuzzy evolutionary aiNet and hybrid features</dcterms:title> <dc:language>eng</dc:language> <dc:contributor>Zhan, Yong-Zhao</dc:contributor> <dspace:hasBitstream rdf:resource=""/> <dc:contributor>Zheng, Hong-Wei</dc:contributor> </rdf:Description> </rdf:RDF>

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