Detailed Information on Publication Record
2011
MUFIN at ImageCLEF 2011: Success or Failure?
BUDÍKOVÁ, Petra, Michal BATKO and Pavel ZEZULABasic information
Original name
MUFIN at ImageCLEF 2011: Success or Failure?
Name in Czech
MUFIN na soutěži ImageCLEF 2011: Úspěch nebo selhání?
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
Amsterdam, CLEF 2011 Labs and Workshop, Notebook Papers; CEUR Workshop Proceedings Vol. 1177, p. 1-12, 12 pp. 2011
Publisher
CLEF
Other information
Language
English
Type of outcome
Stať ve sborníku
Field of Study
10201 Computer sciences, information science, bioinformatics
Country of publisher
Netherlands
Confidentiality degree
není předmětem státního či obchodního tajemství
Publication form
electronic version available online
References:
RIV identification code
RIV/00216224:14330/11:00050011
Organization unit
Faculty of Informatics
ISSN
Keywords in English
image annotation; content-based image retrieval; ImageCLEF Photo Annotation Task;
Tags
Tags
International impact, Reviewed
Změněno: 5/5/2016 16:02, RNDr. Pavel Šmerk, Ph.D.
Abstract
V originále
In all fields of research it is important to discuss and compare various methods that are being proposed to solve given problems. In image retrieval, the ImageCLEF competitions provide such comparison platform. We have participated in the Photo Annotation Task of the ImageCLEF 2011 competition with a system based on the MUFIN Annotation Tool. Our approach is, in contrast to typical classifier solutions, based on a general annotation system for web images that provides general keywords for arbitrary image. However, the free-text annotation needs to be transformed into the 99 concepts given by the competition task. The transformation process is described in detail in the first part of this paper. In the second part, we discuss the results achieved by our solution. Even though the free-text annotation approach was not as successful as the classifier-based approaches, the results are competitive especially for the concepts involving real-world objects. On the other hand, our approach does not require training and is scalable to any number of concepts.
Links
GAP103/10/0886, research and development project |
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VF20102014004, research and development project |
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