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 in | 2010 IEEE International Conference on Image Processing pp. 1969 - 1972 |
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Main Authors | , |
Format | Conference Proceeding |
Language | English |
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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. |
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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 |
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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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