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Content-based image retrieval with relevance feedback using random walks

7 years 9 months ago
Content-based image retrieval with relevance feedback using random walks
In this paper we propose a novel approach to content-based image retrieval with relevance feedback, which is based on the random walker algorithm introduced in the context of interactive image segmentation. The idea is to treat the relevant and non-relevant images labeled by the user at every feedback round as “seed” nodes for the random walker problem. The ranking score for each unlabeled image is computed as the probability that a random walker starting from that image will reach a relevant seed before encountering a non-relevant one. Our method is easy to implement, parameter-free and scales well to large datasets. Extensive experiments on different real datasets with several image similarity measures show the superiority of our method over different recent approaches.
Samuel Rota Bulò, Massimo Rabbi, Marcello P
Added 17 Sep 2011
Updated 17 Sep 2011
Type Journal
Year 2011
Where PR
Authors Samuel Rota Bulò, Massimo Rabbi, Marcello Pelillo
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