Applied Sciences (Jan 2020)

Optical Flow-Based Fast Motion Parameters Estimation for Affine Motion Compensation

  • Antoine Chauvet,
  • Yoshihiro Sugaya,
  • Tomo Miyazaki,
  • Shinichiro Omachi

DOI
https://doi.org/10.3390/app10020729
Journal volume & issue
Vol. 10, no. 2
p. 729

Abstract

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This study proposes a lightweight solution to estimate affine parameters in affine motion compensation. Most of the current approaches start with an initial approximation based on the standard motion estimation, which only estimates the translation parameters. From there, iterative methods are used to find the best parameters, but they require a significant amount of time. The proposed method aims to speed up the process in two ways, first, skip evaluating affine prediction when it is likely to bring no encoding efficiency benefit, and second, by estimating better initial values for the iteration process. We use the optical flow between the reference picture and the current picture to estimate quickly the best encoding mode and get a better initial estimation. We achieve a reduction in encoding time over the reference of half when compared to the state of the art, with a loss in efficiency below 1%.

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