MUFIN at ImageCLEF 2011: Success or Failure?

BUDÍKOVÁ, Petra, Michal BATKO and Pavel ZEZULA. MUFIN at ImageCLEF 2011: Success or Failure?. Online. In CLEF 2011 Labs and Workshop, Notebook Papers; CEUR Workshop Proceedings Vol. 1177. Amsterdam: CLEF, 2011, p. 1-12. ISSN 1613-0073.

Basic 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

• Original language: English
• Type of outcome: Proceedings paper
• Field of Study: 10201 Computer sciences, information science, bioinformatics
• Country of publisher: Netherlands
• Confidentiality degree: is not subject to a state or trade secret
• Publication form: electronic version available online
• WWW: URL
• RIV identification code: RIV/00216224:14330/11:00050011
• Organization unit: Faculty of Informatics
• ISSN: 1613-0073
• Keywords in English: image annotation; content-based image retrieval; ImageCLEF Photo Annotation Task
• Tags: DISA
• Tags: International impact, Reviewed

Abstract

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: 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