Publication details
Content
-based Image Retrieval on the Web
| Basic information | |
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| Original title: | Content -based Image Retrieval on the Web |
| Authors: | David Novák, Michal Batko, Pavel Zezula |
| Further information | |
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| Citation: | NOVÁK, David - BATKO, Michal - ZEZULA, Pavel. 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, 2008. ISBN 978 -3 -642 -00984 -6, pp. 1 -3. 28.9.2008, Vienna, Austria. |
| Original language: | English |
| Field: | Informatika |
| WWW: | http://sunsite.informatik.rwth -aachen.de/Publications/CEUR -WS/Vol -399/paper09.pdf |
| Type: | Article in Proceedings |
| Keywords: | similarity search; content -based search; image search; large -scale search; distributed data structures |
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.
Related projects:
- Integrated approach to education of PhD students in the area of parallel and distributed systems
- Intelligent Models, Algorithms, Methods and Tools for the Semantic Web (realization)
- Complex similarity searching in very large data collections










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