Evaluation Platform for Content-based Image Retrieval Systems

D 2011

Evaluation Platform for Content-based Image Retrieval Systems

BUDÍKOVÁ, Petra, Michal BATKO and Pavel ZEZULA

Basic information

Original name

Evaluation Platform for Content-based Image Retrieval Systems

Name in Czech

Evaluační platforma pro obrazové vyhledávací systémy založené na obsahu

Authors

BUDÍKOVÁ, Petra (203 Czech Republic, guarantor, belonging to the institution), Michal BATKO (203 Czech Republic, belonging to the institution) and Pavel ZEZULA (203 Czech Republic, belonging to the institution)

Edition

Berlin, International Conference on Theory and Practice of Digital Libraries 2011, LNCS 6966, p. 130-142, 12 pp. 2011

Publisher

Springer

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

10201 Computer sciences, information science, bioinformatics

Country of publisher

Germany

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

RIV identification code

RIV/00216224:14330/11:00049925

Organization unit

Faculty of Informatics

ISBN

978-3-642-24468-1

UT WoS

000306258000015

Keywords in English

large-scale image dataset; visual and textual annotation; ground truth; collaboration service

Abstract

V originále

In all subelds of information retrieval, test datasets and ground truth data are important tools for testing and comparison of new search methods. This is also reflected by the image retrieval community where several benchmarking activities have been created in past years using different test data. However, the number of available test collections is still rather small and the existing ones are often limited in size or accessible only to the participants of benchmarking competitions. In this work, we present a new freely-available large-scale dataset for evaluation of content-based image retrieval systems. The dataset consists of 20 million high-quality images with ve visual descriptors and rich and systematic textual annotations, a set of 100 test query objects and a semi-automatically collected ground truth data veried by users. Furthermore, we provide services that enable exploitation and collaborative expansion of the ground truth.

Links

GAP103/10/0886, research and development project

Name: Vizuální vyhledávání obrázků na Webu (Acronym: VisualWeb)

Investor: Czech Science Foundation, Content-based Image Retrieval on the Web Scale

VF20102014004, research and development project

Name: Multimediální analýza (Acronym: Multimediální analýza)

Investor: Ministry of the Interior of the CR

Citovat

BUDÍKOVÁ, Petra, Michal BATKO and Pavel ZEZULA. Evaluation Platform for Content-based Image Retrieval Systems. In International Conference on Theory and Practice of Digital Libraries 2011, LNCS 6966. Berlin: Springer, 2011, p. 130-142, 12 pp. ISBN 978-3-642-24468-1.

@inproceedings{948299,
   author = {Budíková, Petra and Batko, Michal and Zezula, Pavel},
   address = {Berlin},
   booktitle = {International Conference on Theory and Practice of Digital Libraries 2011, LNCS 6966},
   keywords = {large-scale image dataset; visual and textual annotation; ground truth; collaboration service},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Berlin},
   isbn = {978-3-642-24468-1},
   pages = {130-142},
   publisher = {Springer},
   title = {Evaluation Platform for Content-based Image Retrieval Systems},
   year = {2011}
}

TY  - JOUR
ID  - 948299
AU  - Budíková, Petra - Batko, Michal - Zezula, Pavel
PY  - 2011
TI  - Evaluation Platform for Content-based Image Retrieval Systems
PB  - Springer
CY  - Berlin
SN  - 9783642244681
KW  - large-scale image dataset
KW  - visual and textual annotation
KW  - ground truth
KW  - collaboration service
N2  - In all subelds of information retrieval, test datasets and ground truth data are important tools for testing and comparison of new search methods. This is also reflected by the image retrieval community where several benchmarking activities have been created in past years using different test data. However, the number of available test collections is still rather small and the existing ones are often limited in size or accessible only to the participants of benchmarking competitions. In this work, we present a new freely-available large-scale dataset for evaluation of content-based image retrieval systems. The dataset consists of 20 million high-quality images with ve visual descriptors and rich and systematic textual annotations, a set of 100 test query objects and a semi-automatically collected ground truth data veried by users. Furthermore, we provide services that enable exploitation and collaborative expansion of the ground truth.
ER  -

BUDÍKOVÁ, Petra, Michal BATKO and Pavel ZEZULA. Evaluation Platform for Content-based Image Retrieval Systems. In \textit{International Conference on Theory and Practice of Digital Libraries 2011, LNCS 6966}. Berlin: Springer, 2011, p.~130-142, 12 pp. ISBN~978-3-642-24468-1.

Detailed Information on Publication Record