HOMOLA, Tomáš, Vlastislav DOHNAL and Pavel ZEZULA. Sub-image Searching Through Intersection of Local Descriptors. In 3rd International Conference on Similarity Search and Applications (SISAP 2010). New York: ACM Press, 2010, p. 127-128. ISBN 978-1-4503-0420-7.
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Basic information
Original name Sub-image Searching Through Intersection of Local Descriptors
Authors HOMOLA, Tomáš (203 Czech Republic, belonging to the institution), Vlastislav DOHNAL (203 Czech Republic, guarantor, belonging to the institution) and Pavel ZEZULA (203 Czech Republic, belonging to the institution).
Edition New York, 3rd International Conference on Similarity Search and Applications (SISAP 2010), p. 127-128, 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/00216224:14330/10:00044856
Organization unit Faculty of Informatics
ISBN 978-1-4503-0420-7
Keywords in English sub image retrieval
Tags DISA
Tags International impact, Reviewed
Changed by Changed by: doc. RNDr. Vlastislav Dohnal, Ph.D., učo 2952. Changed: 17/1/2013 10:26.
Abstract
The complexity of search in current business intelligence systems, academic research, or even the home audiovisual databases grows up rapidly. Users require searching by the content of their data. For example, the user sees a cathedral while watching a movie and by taking a snapshot, his or her private collection of holiday photos can be searched for images containing that cathedral. In practice, it is not sufficient to store data and search in it by exact match but rather by means of similarity, i.e. retrieving data items similar to a query item. Similarity searching is especially requested in multimedia databases, digital right management systems, computer aided diagnosis, but also in natural sciences and psychology. In these fields, theoretical primal background for querying by similarity is already defined. In this demonstration, we focus on similarity searching from the perspective of identifying and locating an object depicted in a query image in a collection of images.
Links
GAP103/10/0886, research and development projectName: Vizuální vyhledávání obrázků na Webu (Acronym: VisualWeb)
Investor: Czech Science Foundation, Content-based Image Retrieval on the Web Scale
GA201/09/0683, research and development projectName: Vyhledávání v rozsáhlých multimediálních databázích
Investor: Czech Science Foundation, Similarity Searching in Very Large Multimedia Databases
MUNI/A/0922/2009, interní kód MUName: Aplikovaný výzkum Fakulty informatiky (Acronym: AVFI)
Investor: Masaryk University, Category A
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