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The superpixel extraction algorithm is becoming increasingly significant for pattern recognition applications. Different superpixel generation methods have different properties and lead to various over-segmentation results. In this paper, we treat the over-segmentation as an image decomposition problem, and propose a novel discriminative sparse coding (DSC)(More)
A non-rigid and precise image registration algorithm based on finite element method (FEM) is presented. The algorithm require to model image as the free-form deformation elastic material, construct the physical model and generate meshes from image datasets. Its characteristic is achieved through a finite-element based scheme and thus control the mesh(More)
In this paper, we propose a hierarchical probabilistic model for scene classification. This model infers the local–class–shared and local–class-specific latent topics respectively. Our approach consists of first learning the latent topics from the BoW representation and subsequently, training SVM on the distribution of the latent topics. This approach is(More)
In this paper, we exploit an algorithm for detecting the individual objects from multiple images in a weakly supervised manner. Specifically, we treat the object co-detection as a jointly dictionary learning and objects localization problem. Thus a novel low-rank and sparse representation dictionary learning algorithm is proposed. It aims to learn a compact(More)