Results 1 - 10 of 182,651

Performance of optical flow techniques

by J. L. Barron, D. J. Fleet, S. S. Beauchemin - INTERNATIONAL JOURNAL OF COMPUTER VISION , 1994
"... While different optical flow techniques continue to appear, there has been a lack of quantitative evaluation of existing methods. For a common set of real and synthetic image sequences, we report the results of a number of regularly cited optical flow techniques, including instances of differential, ..."
Abstract - Cited by 1325 (32 self) - Add to MetaCart
While different optical flow techniques continue to appear, there has been a lack of quantitative evaluation of existing methods. For a common set of real and synthetic image sequences, we report the results of a number of regularly cited optical flow techniques, including instances of differential

Determining Optical Flow

by Berthold K. P. Horn, Brian G. Schunck - ARTIFICIAL INTELLIGENCE , 1981
"... Optical flow cannot be computed locally, since only one independent measurement is available from the image sequence at a point, while the flow velocity has two components. A second constraint is needed. A method for finding the optical flow pattern is presented which assumes that the apparent veloc ..."
Abstract - Cited by 2404 (9 self) - Add to MetaCart
Optical flow cannot be computed locally, since only one independent measurement is available from the image sequence at a point, while the flow velocity has two components. A second constraint is needed. A method for finding the optical flow pattern is presented which assumes that the apparent

High Accuracy Optical Flow Estimation Based on a Theory for Warping

by Thomas Brox, Andrés Bruhn, Nils Papenberg, Joachim Weickert , 2004
"... We study an energy functional for computing optical flow that combines three assumptions: a brightness constancy assumption, a gradient constancy assumption, and a discontinuity-preserving spatio-temporal smoothness constraint. ..."
Abstract - Cited by 509 (45 self) - Add to MetaCart
We study an energy functional for computing optical flow that combines three assumptions: a brightness constancy assumption, a gradient constancy assumption, and a discontinuity-preserving spatio-temporal smoothness constraint.

The Computation of Optical Flow

by S.S. Beauchemin, J.L. Barron , 1995
"... Two-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-ordered images allow the estimation of projected two-dimensional image motion as either instantaneous image velocities or discrete image dis ..."
Abstract - Cited by 295 (10 self) - Add to MetaCart
displacements. These are usually called the optical flow field or the image velocity field. Provided that optical flow is a reliable approximation to two-dimensional image motion, it may then be used to recover the three-dimensional motion of the visual sensor (to within a scale factor) and the three

A database and evaluation methodology for optical flow

by Simon Baker, Daniel Scharstein, J. P. Lewis, Stefan Roth, Michael J. Black, Richard Szeliski - In Proceedings of the IEEE International Conference on Computer Vision , 2007
"... The quantitative evaluation of optical flow algorithms by Barron et al. (1994) led to significant advances in performance. The challenges for optical flow algorithms today go beyond the datasets and evaluation methods proposed in that paper. Instead, they center on problems associated with complex n ..."
Abstract - Cited by 407 (22 self) - Add to MetaCart
The quantitative evaluation of optical flow algorithms by Barron et al. (1994) led to significant advances in performance. The challenges for optical flow algorithms today go beyond the datasets and evaluation methods proposed in that paper. Instead, they center on problems associated with complex

Probability Distributions of Optical Flow

by Eero P. Simoncelli, Edward H. Adelson, David J. Heeger - PROC. CONF. COMP. VISION AND PATT. RECOGNITION , 1991
"... Gradient methods are widely used in the computation of optical flow. We discuss extensions of these methods which compute probability distributions of optical flow. The use of distributions allows representation of the uncertainties inherent in the optical flow computation, facilitating the combinat ..."
Abstract - Cited by 214 (14 self) - Add to MetaCart
Gradient methods are widely used in the computation of optical flow. We discuss extensions of these methods which compute probability distributions of optical flow. The use of distributions allows representation of the uncertainties inherent in the optical flow computation, facilitating

Optic flow

by Part I
"... Optic flow measurement is an early vision processing step in computer vision, which is used in a wide variety of applications, ranging from three dimensional scene analysis to video compression and experimental physics. The term optical flow was first used by the psychologist James Jerome Gibson in ..."
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Optic flow measurement is an early vision processing step in computer vision, which is used in a wide variety of applications, ranging from three dimensional scene analysis to video compression and experimental physics. The term optical flow was first used by the psychologist James Jerome Gibson

Optic flow

by Henning Zimmer, Andrés Bruhn, Joachim Weickert, Levi Valgaerts, Agustín Salgado, Bodo Rosenhahn, Hans-peter Seidel - in harmony. IJCV 93 , 2011
"... Abstract. We introduce the concept of complementarity between data and smoothness term in modern variational optic flow methods. First we design a sophisticated data term that incorporates HSV colour representation with higher order constancy assumptions, completely separate robust penalisation, and ..."
Abstract - Cited by 19 (4 self) - Add to MetaCart
Abstract. We introduce the concept of complementarity between data and smoothness term in modern variational optic flow methods. First we design a sophisticated data term that incorporates HSV colour representation with higher order constancy assumptions, completely separate robust penalisation

On the Spatial Statistics of Optical Flow

by Stefan Roth, Michael J. Black - In ICCV , 2005
"... We 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. A detailed analysis of optical flow ..."
Abstract - Cited by 102 (8 self) - Add to MetaCart
We 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. A detailed analysis of optical flow

Secrets of Optical Flow Estimation and Their Principles

by Deqing Sun, Stefan Roth, Michael J. Black , 2010
"... 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, has changed little since the work of Horn and Schunck. We attempt to uncover what has made recent advances possible throu ..."
Abstract - Cited by 195 (10 self) - Add to MetaCart
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, has changed little since the work of Horn and Schunck. We attempt to uncover what has made recent advances possible
Results 1 - 10 of 182,651