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The computation of optical flow
ACM Computing Surveys, 1995Two-dimensional image motion is the projection of the three-dimensional motion of objects, relative to a visual sensor, onto its image plane. Sequences of time-orderedimages allow the estimation of projected two-dimensional image motion as either instantaneous image velocities or discrete image displacements.
Steven S. Beauchemin, John L. Barron
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Robust Optical Flow Integration
IEEE Transactions on Image Processing, 2015We analyze the problem of how to correctly construct dense point trajectories from optical flow fields. First, we show that simple Euler integration is unavoidably inaccurate, no matter how good is the optical flow estimator. Then, an inverse integration scheme is analyzed which is more robust to bias and input noise and shows better stability ...
Tomás Crivelli +4 more
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Optic Flow and Autonomous Navigation
Perception, 1995Many animals, especially insects, compute and use optic flow to control their motion direction and to avoid obstacles. Recent advances in computer vision have shown that an adequate optic flow can be computed from image sequences. Therefore studying whether artificial systems, such as robots, can use optic flow for similar purposes is of particular ...
CAMPANI M, GIACHETTI A, TORRE V
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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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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
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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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Optical flow and scene flow estimation: A survey
Pattern Recognition, 2021Mingliang Zhai, Xuezhi Xiang, Ning Lv
exaly