AAAI Publications, Twenty-Third International FLAIRS Conference

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Image Re-Ranking Based on Relevance Feedback Combining Internal and External Similarities
Ricardo Omar Chávez García, Manuel Montes, Luis Enrique Sucar

Last modified: 2010-05-06


We propose a novel method to re-order the list of images returned by an image retrieval system (IRS). The method combines the original order obtained by an IRS, the similarity between images obtained with textual features and a relevance feedback approach, all of them with the purpose of separating relevant from irrelevant images, and thus, obtaining a more appropriate order. Experiments were conducted with resources from Image CLEF 2008; the proposed method improves the order of the original list up to 42%.


Image Re-ranking; Internal Similarity; External Similarity; Markov Random Field;

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