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CVPR
1997
IEEE
16 years 4 months ago
Learning Parameterized Models of Image Motion
A framework for learning parameterized models of optical flow from image sequences is presented. A class of motions is represented by a set of orthogonal basis flow fields that ar...
Michael J. Black, Yaser Yacoob, Allan D. Jepson, D...
108
Voted
ICIP
2010
IEEE
15 years 18 days ago
3D augmented Markov random field for object recognition
In this paper, we propose to use 3D information to augment the Markov random field (MRF) model for object recognition. Conventional MRF for image-based object recognition usually ...
Wei Yu, Ahmed Bilal Ashraf, Yao-Jen Chang, Congcon...
147
Voted
JMLR
2010
145views more  JMLR 2010»
14 years 9 months ago
Parallelizable Sampling of Markov Random Fields
Markov Random Fields (MRFs) are an important class of probabilistic models which are used for density estimation, classification, denoising, and for constructing Deep Belief Netwo...
James Martens, Ilya Sutskever
118
Voted
ICASSP
2008
IEEE
15 years 9 months ago
Optical flow robust estimation in a hybrid multi-resolution MRF framework
We propose in this paper a robust multi-resolution technique to estimate dense velocity field from image sequences. It couples a Gaussian pyramidal down-sampling decomposition to...
Cyril Cassisa, Véronique Prinet, Liang Shao...
135
Voted
ICIP
1999
IEEE
16 years 4 months ago
Road and Lane Edge Detection with Multisensor Fusion Methods
This paper treats automated detection of road and lane boundaries by fusing information from forwardlooking optical and active W-band radar imaging sensors mounted on a motor vehi...
Bing Ma, Sridhar Lakshmanan, Alfred O. Hero III