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» Modelling perception using image processing algorithms
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NIPS
2008
15 years 4 months ago
Efficient Sampling for Gaussian Process Inference using Control Variables
Sampling functions in Gaussian process (GP) models is challenging because of the highly correlated posterior distribution. We describe an efficient Markov chain Monte Carlo algori...
Michalis Titsias, Neil D. Lawrence, Magnus Rattray
SIAMIS
2010
395views more  SIAMIS 2010»
15 years 1 months ago
A Geometric Approach to Joint 2D Region-Based Segmentation and 3D Pose Estimation Using a 3D Shape Prior
Abstract. In this work, we present an approach to jointly segment a rigid object in a two-dimensional (2D) image and estimate its three-dimensional (3D) pose, using the knowledge o...
Samuel Dambreville, Romeil Sandhu, Anthony J. Yezz...
CVPR
2007
IEEE
16 years 5 months ago
Variable Bandwidth Image Denoising Using Image-based Noise Models
This paper introduces a variational formulation for image denoising based on a quadratic function over kernels of variable bandwidth. These kernels are scale adaptive and reflect ...
Noura Azzabou, Nikos Paragios, Frederic Guichard, ...
ICDAR
2009
IEEE
15 years 9 months ago
Enhanced Text Extraction from Arabic Degraded Document Images Using EM Algorithm
This paper presents a new enhanced text extraction algorithm from degraded document images on the basis of the probabilistic models. The observed document image is considered as a...
Wafa Boussellaa, Aymen Bougacha, Abderrazak Zahour...
PAMI
2008
243views more  PAMI 2008»
15 years 2 months ago
Shape from Defocus via Diffusion
Defocus can be modeled as a diffusion process and represented mathematically using the heat equation, where image blur corresponds to the diffusion of heat. This analogy can be ext...
Paolo Favaro, Stefano Soatto, Martin Burger, Stanl...