Multimodal Ranking for Image Search on Community Databases

  • Searching for relevant images given a query term is an important task in nowadays large-scale community databases. The image ranking approach presented in this work represents an image collection as a graph that is built using a multimodal similarity measure based on visual features and user tags. We perform a random walk on this graph to find the most common images. Further we discuss several scalability issues of the proposed approach and show how in this framework queries can be answered fast. Experimental results validate the effectiveness of the presented algorithm.

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Author:Fabian Richter, Stefan RombergGND, Eva HörsterGND, Rainer LienhartGND
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Series (Serial Number):Reports / Technische Berichte der Fakultät für Angewandte Informatik der Universität Augsburg (2011-07)
Publishing Institution:Universität Augsburg
Release Date:2011/03/24
Tag:image ranking; image retrieval; PageRank; graph
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Maschinelles Lernen und Maschinelles Sehen
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):Deutsches Urheberrecht