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» MRF Solutions for Probabilistic Optical Flow Formulations
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ICIP
2009
IEEE
13 years 4 months ago
Optical flow and depth from motion for omnidirectional images using a TV-L1 variational framework on graphs
This paper deals with the problem of efficiently computing the optical flow of image sequences acquired by omnidirectional (nearly full field of view) cameras. We formulate the pr...
Luigi Bagnato, Pascal Frossard, Pierre Vandergheyn...
ECCV
2008
Springer
14 years 8 months ago
Learning Optical Flow
Assumptions of brightness constancy and spatial smoothness underlie most optical flow estimation methods. In contrast to standard heuristic formulations, we learn a statistical mod...
Deqing Sun, Stefan Roth, J. P. Lewis, Michael J. B...
ICML
2008
IEEE
14 years 7 months ago
On partial optimality in multi-label MRFs
We consider the problem of optimizing multilabel MRFs, which is in general NP-hard and ubiquitous in low-level computer vision. One approach for its solution is to formulate it as...
Pushmeet Kohli, Alexander Shekhovtsov, Carsten Rot...
CVPR
2010
IEEE
13 years 12 months ago
Secrets of Optical Flow Estimation and Their Principles
The accuracy of optical flow estimation algorithms has been improving steadily as evidenced by results on the Middlebury optical flow benchmark. The typical formulation, however...
Deqing Sun, Stefan Roth, Michael Black
CVPR
2011
IEEE
12 years 10 months ago
Connecting Non-Quadratic Variational Models and MRFs
Spatially-discrete Markov random fields (MRFs) and spatially-continuous variational approaches are ubiquitous in low-level vision, including image restoration, segmentation, opti...
Kevin Schelten, Stefan Roth