Distance scaling of higher order motion parameters in an extension of HEVC

Heithausen, Cordula; Blaser, Max; Wien, Mathias

doi:10.1109/pcs.2016.7906343

Cited by 2 publications

(1 citation statement)

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“…The first limitation is not all blocks are going to use affine prediction, so it may be often necessary to code them without a prediction, but even in the case where a neighbor uses affine prediction, it may use a different reference picture, and scaling the motion parameters is challenging, as simply multiplying every value by the distance ratio does not work. Reference [11] tackles this problem by allowing motion scaling to work on affine parameters. They propose decomposing the transform into separate transforms, for example a rotation and a zoom operation, and scale each matrix appropriately, then combine them again to get the new parameters.…”

Section: Motion Parameter Prediction and Entropy Codingmentioning

confidence: 99%

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

et al. 2020

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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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Section: Motion Parameter Prediction and Entropy Codingmentioning

confidence: 99%