We show how to use unlabeled data and a deep belief net (DBN) to learn a good covariance kernel for a Gaussian process. We first learn a deep generative model of the unlabeled da...
—To construct 3D virtual scenes from two-dimensional images with depth information, image warping techniques could be used. In this paper, a novel approach of cylindrical depth i...
We present a pose estimation method for rigid
objects from single range images. Using 3D models of the
objects, many pose hypotheses are compared in a data-parallel
version of t...
In Kyu Park, Marcel Germann, Michael D. Breitenste...
In this paper, using hypergraph theory, we introduce an image model called Adaptive Image Neighborhood Hypergraph (AINH). From this model we propose a combinatorial definition of ...
This paper presents an effective target representation based on multiple colour histograms computed on semi-overlapping image areas. This solution introduces spatial information i...