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CVPR
2009
IEEE
1081views Computer Vision» more  CVPR 2009»
15 years 2 months ago
Learning Real-Time MRF Inference for Image Denoising
Many computer vision problems can be formulated in a Bayesian framework with Markov Random Field (MRF) or Conditional Random Field (CRF) priors. Usually, the model assumes that ...
Adrian Barbu (Florida State University)
PAMI
2010
249views more  PAMI 2010»
13 years 6 months ago
Fast Keypoint Recognition Using Random Ferns
While feature point recognition is a key component of modern approaches to object detection, existing approaches require computationally expensive patch preprocessing to handle pe...
Mustafa Özuysal, Michael Calonder, Vincent Le...
JMLR
2011
167views more  JMLR 2011»
13 years 2 months ago
Logistic Stick-Breaking Process
A logistic stick-breaking process (LSBP) is proposed for non-parametric clustering of general spatially- or temporally-dependent data, imposing the belief that proximate data are ...
Lu Ren, Lan Du, Lawrence Carin, David B. Dunson
HAPTICS
2006
IEEE
14 years 1 months ago
Measuring Fingertip Forces by Imaging the Fingernail
This paper presents an external camera method for measuring fingertip forces by imaging the fingernail and surrounding skin. This method is an alternative to the photoplethysmog...
Yu Sun, Young-Seok Kim, John M. Hollerbach, Thenku...
ICASSP
2011
IEEE
12 years 11 months ago
Denoising of image patches via sparse representations with learned statistical dependencies
We address the problem of denoising for image patches. The approach taken is based on Bayesian modeling of sparse representations, which takes into account dependencies between th...
Tomer Faktor, Yonina C. Eldar, Michael Elad