Class-specific metrics for multidimensional data projection applied to CBIR


Autoria(s): Jóia Filho, Paulo; Gomez-Nieto, Erick Mauricio; Casaca, Wallace Correa de Oliveira; Botelho, Glenda Michele; Paiva Neto, Afonso; Nonato, Luis Gustavo
Contribuinte(s)

UNIVERSIDADE DE SÃO PAULO

Data(s)

14/10/2013

14/10/2013

2012

Resumo

Content-based image retrieval is still a challenging issue due to the inherent complexity of images and choice of the most discriminant descriptors. Recent developments in the field have introduced multidimensional projections to burst accuracy in the retrieval process, but many issues such as introduction of pattern recognition tasks and deeper user intervention to assist the process of choosing the most discriminant features still remain unaddressed. In this paper, we present a novel framework to CBIR that combines pattern recognition tasks, class-specific metrics, and multidimensional projection to devise an effective and interactive image retrieval system. User interaction plays an essential role in the computation of the final multidimensional projection from which image retrieval will be attained. Results have shown that the proposed approach outperforms existing methods, turning out to be a very attractive alternative for managing image data sets.

FAPESP

CAPES-Brazil

Identificador

The Visual Computer, Heidelberg, v. 28, n. 10, Special Issue, supl. 1, Part 2, p. 1027-1037, oct, 2012

0178-2789

http://www.producao.usp.br/handle/BDPI/35015

10.1007/s00371-012-0730-z

http://dx.doi.org/10.1007/s00371-012-0730-z

Idioma(s)

eng

Publicador

Springer-Verlag

Heidelberg

Relação

The Visual Computer

Direitos

closedAccess

Copyright Springer-Verlag

Palavras-Chave #MULTIDIMENSIONAL PROJECTION #CONTENT-BASED IMAGE RETRIEVAL #NONLINEAR DIMENSIONALITY REDUCTION #IMAGE RETRIEVAL #FEATURES #COMPUTAÇÃO GRÁFICA #PROCESSAMENTO DE IMAGENS #GEOMETRIA COMPUTACIONAL #COMPUTER SCIENCE, SOFTWARE ENGINEERING
Tipo

article

original article

publishedVersion