Domain Transfer SVM for video concept detection

Lixin Duan, I.W. Tsang, Dong Xu, S.J. Maybank
2009 2009 IEEE Conference on Computer Vision and Pattern Recognition  
Cross-domain learning methods have shown promising results by leveraging labeled patterns from auxiliary domains to learn a robust classifier for target domain, which has a limited number of labeled samples. To cope with the tremendous change of feature distribution between different domains in video concept detection, we propose a new cross-domain kernel learning method. Our method, referred to as Domain Transfer SVM (DTSVM), simultaneously learns a kernel function and a robust SVM classifier
more » ... y minimizing the both structural risk functional of SVM and distribution mismatch of labeled and unlabeled samples between the auxiliary and target domains. Comprehensive experiments on the challenging TRECVID corpus demonstrate that DTSVM outperforms existing crossdomain learning and multiple kernel learning methods.
doi:10.1109/cvprw.2009.5206747 fatcat:4af3gq6rgnfwdoh3ajjopbyqba