Employing negative examples in region-based image retrieval

Author

Jing, Feng ; Li, Mingjing ; Zhang, Hong-Jiang ; Zhang, Bo

Author_Institution

State Key Lab of Intelligent Technol. & Syst., Beijing, China

Volume

3

fYear

2003

fDate

15-18 Dec. 2003

Firstpage

1600

Abstract

In this paper, the integration of negative examples into an efficient region-based image retrieval framework is investigated. The outputs of a support vector machine that separates positive images from negative ones are used to refine the current retrieval result. Considering the speciality of region-based representation, a kind of new kernel is proposed, which is the generalization of Gaussian kernel. Experimental results on a database of 10,000 general-purpose images demonstrate the effectiveness of employing negative examples and the superiority of the new kernel to Gaussian kernel.

Keywords

Gaussian processes; image representation; image retrieval; support vector machines; Gaussian kernel; image databases; image segmentation; negative examples; region-based image retrieval framework; support vector machine; Asia; Content based retrieval; Humans; Image retrieval; Intelligent systems; Kernel; Negative feedback; Space technology; Support vector machine classification; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Information, Communications and Signal Processing, 2003 and Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint Conference of the Fourth International Conference on

Print_ISBN

0-7803-8185-8

Type

conf

DOI

10.1109/ICICS.2003.1292737

Filename

1292737