Image retrieval based on bag of images


Autoria(s): Zhang, Jun; Ye, Lei
Contribuinte(s)

[Unknown]

Data(s)

01/01/2009

Resumo

Conventional relevance feedback schemes may not be suitable to all practical applications of content-based image retrieval (CBIR), since most ordinary users would like to complete their search in a single interaction, especially on the web search. In this paper, we explore a new approach to improve the retrieval performance based on a new concept, bag of images, rather than relevance feedback. We consider that image collection comprises of image bags instead of independent individual images. Each image bag includes some relevant images with the same perceptual meaning. A theoretical case study demonstrates that image retrieval can benefit from the new concept. A number of experimental results show that the CBIR scheme based on bag of images can improve the retrieval performance dramatically.<br />

Identificador

http://hdl.handle.net/10536/DRO/DU:30039521

Idioma(s)

eng

Publicador

IEEE

Relação

http://dro.deakin.edu.au/eserv/DU:30039521/zhang-imageretrieval-2009.pdf

http://www.icip2009.org/default.asp

http://dx.doi.org/10.1109/ICIP.2009.5413602

Direitos

2009, IEEE

Palavras-Chave #content-based image retrieval #similarity measure #bag of images #information retrieval
Tipo

Conference Paper