Multimodal ranking for image search on community databases

Fabian Richter, Stefan Romberg, Eva Hörster, Rainer Lienhart
2010 Proceedings of the international conference on Multimedia information retrieval - MIR '10  
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
more » ... . Experimental results validate the effectiveness of the presented algorithm.
doi:10.1145/1743384.1743402 dblp:conf/mir/RichterRHL10 fatcat:ylplqntbq5go7nm25wrcfvi35i