Search-based image annotation: Extracting semantics from
similar images

D 2015

Search-based image annotation: Extracting semantics from similar images

BUDÍKOVÁ, Petra, Michal BATKO, Jan BOTOREK and Pavel ZEZULA

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

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Confidentiality degree

není předmětem státního či obchodního tajemství

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

DOI

http://dx.doi.org/10.1007/978-3-319-24027-5_36

UT WoS

000364677800039

Keywords in English

image annotation; similarity search; evaluation

Abstract

V originále

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 project

Name: Centrum pro multi-modální interpretaci dat velkého rozsahu

Investor: Czech Science Foundation

Citovat

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.

@inproceedings{1331211,
   author = {Budíková, Petra and Batko, Michal and Botorek, Jan and Zezula, Pavel},
   address = {Toulouse, France},
   booktitle = {Experimental IR Meets Multilinguality, Multimodality, and Interaction - 6th International Conference of the CLEF Association, CLEF 2015},
   doi = {http://dx.doi.org/10.1007/978-3-319-24027-5_36},
   keywords = {image annotation; similarity search; evaluation},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Toulouse, France},
   isbn = {978-3-319-24026-8},
   pages = {327-339},
   publisher = {Springer},
   title = {Search-based image annotation: Extracting semantics from similar images},
   year = {2015}
}

TY  - JOUR
ID  - 1331211
AU  - Budíková, Petra - Batko, Michal - Botorek, Jan - Zezula, Pavel
PY  - 2015
TI  - Search-based image annotation: Extracting semantics from similar images
PB  - Springer
CY  - Toulouse, France
SN  - 9783319240268
KW  - image annotation
KW  - similarity search
KW  - evaluation
N2  - 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.
ER  -

BUDÍKOVÁ, Petra, Michal BATKO, Jan BOTOREK and Pavel ZEZULA. Search-based image annotation: Extracting semantics from similar images. In \textit{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.

Detailed Information on Publication Record