Content-based Image Retrieval on the Web

NOVÁK, David, Michal BATKO and Pavel ZEZULA. Content-based Image Retrieval on the Web. In Proceedings of the Poster and Demonstration Paper Track of the 1st Future Internet Symposium (FIS 2008). Vienna: CEUR Workshop Proceedings. p. 1-3. ISBN 978-3-642-00984-6. 2008.

Basic information

• Original name: Content-based Image Retrieval on the Web
• Name in Czech: Hledání obrázků dle obsahu v prostředí webu
• Authors: NOVÁK, David (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: Vienna, Proceedings of the Poster and Demonstration Paper Track of the 1st Future Internet Symposium (FIS 2008), p. 1-3, 3 pp. 2008.
• Publisher: CEUR Workshop Proceedings

Other information

• Original language: English
• Type of outcome: Proceedings paper
• Field of Study: 10201 Computer sciences, information science, bioinformatics
• Country of publisher: Austria
• Confidentiality degree: is not subject to a state or trade secret
• Publication form: printed version "print"
• WWW: URL
• RIV identification code: RIV/00216224:14330/08:00024287
• Organization unit: Faculty of Informatics
• ISBN: 978-3-642-00984-6
• Keywords in English: similarity search; content-based search; image search; large-scale search; distributed data structures
• Tags: content-based search, DISA, distributed data structures, image search, large-scale search, similarity search
• Tags: International impact, Reviewed

Abstract

We present and demonstrate capabilities of Multi-Feature Indexing Network (MUFIN), http://mufin.fi.muni.cz/. To achieve an independence of the similarity abstraction and the ability to process large collections of data, MUFIN is based on two basic paradigms: (1) the metric space model of similarity, and (2) the concept of structured Peer-to-Peer networks. In the demonstration we will show an interactive image retrieval system which indexes 50 million images - it is one or two orders of magnitude more than any other system designed to this purpose can do. Further more, the scalability of the system grows with constant complexity, which is very important for future internet technologies. To demonstrate the extensibility of the metric-based MUFIN approach we will show another prototype application: a face-recognition and retrieval system.

Abstract (in Czech)

Tato práce prezentuje a demonstruje schopnosti systému Multi-Feature Indexing Network (MUFIN), http://mufin.fi.muni.cz/. K dosažení nezávislosti na konkrétní podobnostní abstraci a schopnosti zpracovávat velmi rozsáhlé kolekce dat využívá MUFIN dvou základních paradigmat: (1) metrický model podobnosti a (2) koncept strukturovaných Peer-to-Peer sítí. Při demonstraci systému ukážeme interaktivní systém pro vyhledávání v kolekci 50 milionů obrázků. Tato kolekce je o jeden nebo dva řády větší než v existujících podobných systémech. Navíc má systém prakticky konstantní škálovatelnost, což je velmi důležité pro budoucí internetové technologie. Pro demonstraci rozšiřitelnosti systému předvedeme jinou prototypní aplikaci: systém pro rozpoznávání a vyhledávání obličejů.

Links

• GD102/05/H050, research and development project: Name: Integrovaný přístup k výchově studentů DSP v oblasti paralelních a distribuovaných systémů

Investor: Czech Science Foundation, Integrated approach to education of PhD students in the area of parallel and distributed systems

• GP201/08/P507, research and development project: Name: Komplexní podobnostní dotazy nad rozsáhlými objemy dat

Investor: Czech Science Foundation, Complex similarity searching in very large data collections

• 1ET100300419, research and development project: Name: Inteligentní modely, algoritmy, metody a nástroje pro vytváření sémantického webu

Investor: Academy of Sciences of the Czech Republic, Intelligent Models, Algorithms, Methods and Tools for the Semantic Web (realization)