Results 231 to 240 of about 445,901 (262)
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2008
Assumptions of brightness constancy and spatial smoothness underlie most optical flow estimation methods. In contrast to standard heuristic formulations, we learn a statistical model of both brightness constancy error and the spatial properties of optical flow using image sequences with associated ground truth flow fields.
Deqing Sun +3 more
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Assumptions of brightness constancy and spatial smoothness underlie most optical flow estimation methods. In contrast to standard heuristic formulations, we learn a statistical model of both brightness constancy error and the spatial properties of optical flow using image sequences with associated ground truth flow fields.
Deqing Sun +3 more
openaire +1 more source
Optical flow and deformable objects
Proceedings of IEEE International Conference on Computer Vision, 2002When a plane undergoes a deformation that can be represented by a planar linear vector field, the projected vector field on the image plane of an optical device is at most quadratic. This 2D motion field has one singular point, with eigenvalues identical to those of the singular point describing the deformation.
GIACHETTI, Andrea, Torre, Vincent
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On the Spatial Statistics of Optical Flow
International Journal of Computer Vision, 2005We develop a method for learning the spatial statistics of optical flow fields from a novel training database. Training flow fields are constructed using range images of natural scenes and 3D camera motions recovered from handheld and car-mounted video sequences.
Stefan Roth 0001, Michael J. Black
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On the information in optical flows
Computer Vision, Graphics, and Image Processing, 1983Abstract This paper outlines the structure of optical flows and their relation to relative depth, local surface orientation, relative motion, and the source of optokinetic information, the retinal velocities. Some possibilities and limitations of optical flows as a source of information about the three-dimensional environment are also discussed.
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Optical flow and scene flow estimation: A survey
Pattern Recognition, 2021Xuezhi Xiang, Mingliang Zhai, Ning Lv
exaly
A Lightweight Optical Flow CNN —Revisiting Data Fidelity and Regularization
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021Chen Change Loy, Tak-Wai Hui
exaly