Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/73060
Type: Artigo
Title: Using contextual spaces for image re-ranking and rank aggregation
Author: Pedronette, Daniel Carlos Guimarães
Torres, Ricardo da Silva
Calumby, Rodrigo Tripodi
Abstract: This article presents two novel re-ranking approaches that take into account contextual information defined by the K-Nearest Neighbours (KNN) of a query image for improving the effectiveness of CBIR systems. The main contributions of this article are the definition of the concept of contextual spaces for encoding contextual information of images; the definition of two new re-ranking algorithms that exploit contextual information encoded in contextual spaces; and the evaluation of the proposed algorithms in several CBIR tasks related to the combination of image descriptors; combination of visual and textual descriptors; and combination of post-processing (re-ranking) methods. We conducted a large evaluation protocol involving visual descriptors (considering shape, color, and texture) and textual descriptors, various datasets, and comparisons with other post-processing methods. Experimental results demonstrate the effectiveness of our approaches.
This article presents two novel re-ranking approaches that take into account contextual information defined by the K-Nearest Neighbours (KNN) of a query image for improving the effectiveness of CBIR systems. The main contributions of this article are the
Subject: Recuperação de imagens baseada em conteúdo
Re-ranqueamento
Sistemas de recuperação da informação
Processamento de imagens
Reconhecimento de padrões
Country: Estados Unidos
Editor: Springer
Citation: Multimedia Tools And Applications. Springer, v. 69, n. 3, n. 689, n. 716, 2014.
Rights: Aberto
Identifier DOI: 10.1007/s11042-012-1115-z
Address: https://link.springer.com/article/10.1007/s11042-012-1115-z
Date Issue: 2014
Appears in Collections:IC - Artigos e Outros Documentos

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