Artículos de revistas
Image re-ranking and rank aggregation based on similarity of ranked lists
Registro en:
Pattern Recognition. Elsevier Sci Ltd, v. 46, n. 8, n. 2350, n. 2360, 2013.
0031-3203
WOS:000317944800024
10.1016/j.patcog.2013.01.004
Autor
Pedronette, DCG
Torres, RD
Institución
Resumen
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) In Content-based Image Retrieval (CBIR) systems, ranking accurately collection images is of great relevance. Users are interested in the returned images placed at the first positions, which usually are the most relevant ones. Collection images are ranked in increasing order of their distance to the query pattern (e.g., query image) defined by users. Therefore, the effectiveness of these systems is very dependent on the accuracy of the distance function adopted. In this paper, we present a novel context-based approach for redefining distances and later re-ranking images aiming to improve the effectiveness of CBIR systems. In our approach, distances among images are redefined based on the similarity of their ranked lists. Conducted experiments involving shape, color, and texture descriptors demonstrate the effectiveness of our method. (C) 2013 Elsevier Ltd. All rights reserved. 46 8 2350 2360 AMD Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) FAEPEX Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) DGA/UNICAMP Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)