Optical flow estimation with p-harmonic regularization

In this paper, an alternative efficient energy functional is proposed for estimating optical flow. The problem of optical flow estimation is posed as one of solving for the minimum configurations of its two components in an L1 total variation framework augmented with a p-harmonic energy functional....

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Published in2010 IEEE International Conference on Image Processing pp. 1969 - 1972
Main Authors Jiading Gai, Stevenson, Robert L
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.09.2010
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Abstract In this paper, an alternative efficient energy functional is proposed for estimating optical flow. The problem of optical flow estimation is posed as one of solving for the minimum configurations of its two components in an L1 total variation framework augmented with a p-harmonic energy functional. A novel smooth term based on a p-harmonic map energy is added as a regularization constraint in the optical flow computation. The p-harmonic smooth term deals with the regularization of the angle of directional data, while preserving the magnitude. The proposed algorithm is based on separating the optical flow vector into its magnitude and angle, and then processing each one of these components iteratively, in a closed-loop manner. Experiments show that the proposed algorithm outperforms a recently published, top performing L1 total variation method, which shows the capability of the new regularization term in improving the optical flow estimation performance.
AbstractList In this paper, an alternative efficient energy functional is proposed for estimating optical flow. The problem of optical flow estimation is posed as one of solving for the minimum configurations of its two components in an L1 total variation framework augmented with a p-harmonic energy functional. A novel smooth term based on a p-harmonic map energy is added as a regularization constraint in the optical flow computation. The p-harmonic smooth term deals with the regularization of the angle of directional data, while preserving the magnitude. The proposed algorithm is based on separating the optical flow vector into its magnitude and angle, and then processing each one of these components iteratively, in a closed-loop manner. Experiments show that the proposed algorithm outperforms a recently published, top performing L1 total variation method, which shows the capability of the new regularization term in improving the optical flow estimation performance.
Author Jiading Gai
Stevenson, Robert L
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Snippet In this paper, an alternative efficient energy functional is proposed for estimating optical flow. The problem of optical flow estimation is posed as one of...
SourceID ieee
SourceType Publisher
StartPage 1969
SubjectTerms Adaptive optics
Approximation methods
Estimation
Integrated optics
Minimization
Nonlinear optics
Optical flow
Optical imaging
p-harmonic energy
regularization
total variation
Title Optical flow estimation with p-harmonic regularization
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