BUDÍKOVÁ, Petra, Michal BATKO, Jan BOTOREK and Pavel ZEZULA. Search-based image annotation: Extracting semantics from similar images. In Experimental IR Meets Multilinguality, Multimodality, and Interaction - 6th International Conference of the CLEF Association, CLEF 2015. Toulouse, France: Springer, 2015, p. 327-339. ISBN 978-3-319-24026-8. Available from: https://dx.doi.org/10.1007/978-3-319-24027-5_36.
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Basic information
Original name Search-based image annotation: Extracting semantics from similar images
Authors BUDÍKOVÁ, Petra (203 Czech Republic, guarantor, belonging to the institution), Michal BATKO (203 Czech Republic, belonging to the institution), Jan BOTOREK (203 Czech Republic, belonging to the institution) and Pavel ZEZULA (203 Czech Republic, belonging to the institution).
Edition Toulouse, France, Experimental IR Meets Multilinguality, Multimodality, and Interaction - 6th International Conference of the CLEF Association, CLEF 2015, p. 327-339, 13 pp. 2015.
Publisher Springer
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
Impact factor Impact factor: 0.402 in 2005
RIV identification code RIV/00216224:14330/15:00081488
Organization unit Faculty of Informatics
ISBN 978-3-319-24026-8
ISSN 0302-9743
Doi http://dx.doi.org/10.1007/978-3-319-24027-5_36
UT WoS 000364677800039
Keywords in English image annotation; similarity search; evaluation
Tags DISA, firank_B
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 28/4/2016 15:34.
Abstract
The importance of automatic image annotation as a tool for handling large amounts of image data has been recognized for several decades. However, working tools have long been limited to narrow-domain problems with a few target classes for which precise models could be trained. With the advance of similarity searching, it now becomes possible to employ a different approach: extracting information from large amounts of noisy web data. However, several issues need to be resolved, including the acquisition of a suitable knowledge base, choosing a suitable visual content descriptor, implementation of effective and efficient similarity search engine, and extraction of semantics from similar images. In this paper, we address these challenges and present a working annotation system based on the search-based paradigm, which achieved good results in the 2014 ImageCLEF Scalable Concept Image Annotation challenge.
Links
GBP103/12/G084, research and development projectName: Centrum pro multi-modální interpretaci dat velkého rozsahu
Investor: Czech Science Foundation
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