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ICCV
2009
IEEE
15 years 3 months ago
Large Displacement Optical Flow Computation without Warping
We propose an algorithm for large displacement opti- cal flow estimation which does not require the commonly used coarse-to-fine warping strategy. It is based on a quadratic rel...
Frank Steinbrucker, Thomas Pock, Daniel Cremers
ICCV
2009
IEEE
15 years 3 months ago
Structure- and Motion-adaptive Regularization for High Accuracy Optic Flow
The accurate estimation of motion in image sequences is of central importance to numerous computer vision applications. Most competitive algorithms compute flow fields by minimi...
Andreas Wedel, Daniel Cremers, Thomas Pock, Horst ...
CVPR
2009
IEEE
15 years 6 months ago
Large Displacement Optical Flow
The literature currently provides two ways to establish point correspondences between images with moving objects. On one side, there are energy minimization methods that yield v...
Thomas Brox (University of California, Berkeley), ...
ICIP
2010
IEEE
13 years 8 months ago
Randomized motion estimation
Motion estimation is known to be a non-convex optimization problem. This non-convexity comes from several ambiguities in motion estimation such as the aperture problem, or fast mo...
Sylvain Boltz, Frank Nielsen
ICCV
1999
IEEE
15 years 23 days ago
Optimal Filters for Gradient-based Motion Estimation
Gradient based approaches for motion estimation (Optical-Flow) estimate the motion of an image sequence based on local changes in the image intensities. In order to best evaluate ...
Michael Elad, Patrick C. Teo, Yacov Hel-Or