Recent results on stereo indicate that an accurate segmentation is crucial for obtaining faithful depth maps. Variational methods have successfully been applied to both image segm...
In this paper, we propose a novel metric learning method based on regularized moving least squares. Unlike most previous metric learning methods which learn a global Mahalanobis d...
A novel adaptive and patch-based approach is proposed for image regularization and representation. The method is unsupervised and based on a pointwise selection of small image patc...
Abstract. We introduce a new type of local feature basedon the phaseand amplitude responsesof complex-valuedsteerable filters. The designof this local feature is motivated by a des...
Traditional similarity or distance measurements usually become meaningless when the dimensions of the datasets increase, which has detrimental effects on clustering performance. I...