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» Statistically Driven Sparse Image Approximation
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MICCAI
2009
Springer
14 years 1 months ago
On the Manifold Structure of the Space of Brain Images
This paper investigates an approach to model the space of brain images through a low-dimensional manifold. A data driven method to learn a manifold from a collections of brain imag...
Samuel Gerber, Tolga Tasdizen, Sarang C. Joshi, Ro...
ECCV
2004
Springer
14 years 8 months ago
User Assisted Separation of Reflections from a Single Image Using a Sparsity Prior
When we take a picture through transparent glass the image we obtain is often a linear superposition of two images: the image of the scene beyond the glass plus the image of the sc...
Anat Levin, Yair Weiss
CORR
2011
Springer
210views Education» more  CORR 2011»
13 years 1 months ago
Statistical Compressed Sensing of Gaussian Mixture Models
A novel framework of compressed sensing, namely statistical compressed sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical distribu...
Guoshen Yu, Guillermo Sapiro
CVPR
2009
IEEE
15 years 1 months ago
Learning General Optical Flow Subspaces for Egomotion Estimation and Detection of Motion Anomalies
This paper deals with estimation of dense optical flow and ego-motion in a generalized imaging system by exploiting probabilistic linear subspace constraints on the flow. We dea...
Richard Roberts (Georgia Institute of Technology),...
CVPR
2010
IEEE
13 years 9 months ago
Ray Markov Random Fields for Image-Based 3D Modeling: Model and Efficient Inference
In this paper, we present an approach to multi-view image-based 3D reconstruction by statistically inversing the ray-tracing based image generation process. The proposed algorithm...
Shubao Liu, David Cooper