Active BSVM learning for relevance feedback in content-based sketch retrieval

Authors:
Shuang Liang;Zhengxing Sun
Affiliations:
Nanjing University, Nanjing, P.R. China;Nanjing University, Nanjing, P.R. China
Venue:
SPPRA '08 Proceedings of the Fifth IASTED International Conference on Signal Processing, Pattern Recognition and Applications
Year:
2008

Citing 7
Cited 0

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Abstract

The availability of relevance feedback is held back by the problem of the imbalance and limited size of labeled training data, as well as the real-time requirement of online interaction demands. In this paper, we propose a relevance feedback algorithm called active biased SVM (BSVM) learning, in which biased classification and active learning are employed to address these difficulties. The algorithm is applied to content-based sketch retrieval (CBSR), and the experiments prove both the effectiveness and efficiency of the proposed approach.