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Enhancing Exemplar SVMs using Part Level Transfer Regularization

Enhancing Exemplar SVMs using Part Level Transfer Regularization

This video was recorded at British Machine Vision Conference (BMVC), Surrey 2012. Exemplar SVMs (E-SVMs, Malisiewicz et al, ICCV 2011), where a SVM is trained with only a single positive sample, have found applications in the areas of object detection and Content-Based Image Retrieval (CBIR), amongst others. In this paper we introduce a method of part based transfer regularization that boosts the performance of E-SVMs, with a negligible additional cost. This Enhanced E-SVM (EE-SVM) improves the generalization ability of E-SVMs by softly forcing it to be constructed from existing classifier parts cropped from previously learned classifiers. In CBIR applications, where the aim is to retrieve instances of the same object class in a similar pose, the EE-SVM is able to tolerate increased levels... Show More

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