ZAVŘEL, Vojtěch, Michal BATKO and Pavel ZEZULA. Visual Video Retrieval System Using MPEG-7 Descriptors. In 3rd International Conference on Similarity Search and Applications. New York: ACM Press, 2010, p. 125-126. ISBN 978-1-4503-0420-7.
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Basic information
Original name Visual Video Retrieval System Using MPEG-7 Descriptors
Name in Czech Systém pro vyhledávání videí na základě visuální podobnosti definované pomocí MPEG-7 deskriptorů
Authors ZAVŘEL, Vojtěch (203 Czech Republic, guarantor, belonging to the institution), Michal BATKO (203 Czech Republic, belonging to the institution) and Pavel ZEZULA (203 Czech Republic).
Edition New York, 3rd International Conference on Similarity Search and Applications, p. 125-126, 2 pp. 2010.
Publisher ACM Press
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Turkey
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
RIV identification code RIV/00216224:14330/10:00044843
Organization unit Faculty of Informatics
ISBN 978-1-4503-0420-7
Keywords in English video retrieval system; content-based searching; metric space; Multi-feature Indexing Network
Tags DISA
Tags International impact, Reviewed
Changed by Changed by: RNDr. Michal Batko, Ph.D., učo 2907. Changed: 3/4/2013 16:26.
Abstract
Visual Video Retrieval System allows users search according visual similarity in a collection of indexed videos. The system is build upon Multi Feature Indexing Network. Only the visual part of multimedia video (represented by keyframes) is indexed. User is able to search by example or use iterative search.
Links
GA201/09/0683, research and development projectName: Vyhledávání v rozsáhlých multimediálních databázích
Investor: Czech Science Foundation, Similarity Searching in Very Large Multimedia Databases
GP201/08/P507, research and development projectName: Komplexní podobnostní dotazy nad rozsáhlými objemy dat
Investor: Czech Science Foundation, Complex similarity searching in very large data collections
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