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» Modelling perception using image processing algorithms
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NIPS
2007
15 years 5 months ago
Using Deep Belief Nets to Learn Covariance Kernels for Gaussian Processes
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...
Ruslan Salakhutdinov, Geoffrey E. Hinton
IJVR
2007
202views more  IJVR 2007»
15 years 4 months ago
Full Solid Angle Panoramic Viewing by Depth Image Warping on Field Programmable Gate Array
—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...
Xiaoying Li, Baoquan Liu, Enhua Wu

Publication
241views
15 years 5 months ago
Fast and Automatic Object Pose Estimation for Range Images on the GPU
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...
CAIP
2001
Springer
166views Image Analysis» more  CAIP 2001»
15 years 9 months ago
Application of Adaptive Hypergraph Model to Impulsive Noise Detection
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 ...
Soufiane Rital, Alain Bretto, Driss Aboutajdine, H...
ICIP
2005
IEEE
16 years 6 months ago
Multi-part target representation for color tracking
This paper presents an effective target representation based on multiple colour histograms computed on semi-overlapping image areas. This solution introduces spatial information i...
Emilio Maggio, Andrea Cavallaro