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» Optimal recovery approach to image interpolation
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ICCV
2009
IEEE
15 years 14 days ago
Bayesian selection of scaling laws for motion modeling in images
Based on scaling laws describing the statistical structure of turbulent motion across scales, we propose a multiscale and non-parametric regularizer for optic-flow estimation. R...
Patrick H´eas, Etienne M´emin, Dominique Heitz, ...
TIP
2010
160views more  TIP 2010»
13 years 2 months ago
Development and Optimization of Regularized Tomographic Reconstruction Algorithms Utilizing Equally-Sloped Tomography
We develop two new algorithms for tomographic reconstruction which incorporate the technique of equally-sloped tomography (EST) and allow for the optimized and flexible implementat...
Yu Mao, Benjamin P. Fahimian, Stanley Osher, Jianw...
SIGGRAPH
1999
ACM
13 years 11 months ago
Creating Generative Models from Range Images
We describe a new approach for creating concise high-level generative models from range images or other approximate representations of real objects. Using data from a variety of a...
Ravi Ramamoorthi, James Arvo
ICPR
2002
IEEE
14 years 13 days ago
Motion Prediction Using VC-Generalization Bounds
This paper describes a novel application of Statistical Learning Theory (SLT) for motion prediction. SLT provides analytical VC-generalization bounds for model selection; these bo...
Harry Wechsler, Zoran Duric, Fayin Li, Vladimir Ch...
ICCV
2009
IEEE
1735views Computer Vision» more  ICCV 2009»
15 years 14 days ago
Coded Aperture Pairs for Depth From Defocus
The classical approach to depth from defocus uses two images taken with circular apertures of different sizes. We show in this paper that the use of a circular aperture severely...
Changyin Zhou, Stephen Lin, Shree Nayar