DocumentCode :
2899182
Title :
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
Link To Document :
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