时间一致的高帧率上采样与运动稀疏化

Dominic Rüfenacht, D. Taubman
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引用次数: 8

摘要

本文继续我们的工作,在闭塞感知时间帧插值(TFI),采用分段平滑运动与尖锐的运动边界。在这项工作中,我们提出了一种三角形网格稀疏化算法,该算法可以权衡计算复杂性和重建质量。此外,我们还提出了一种在两帧参考帧之间被解除遮挡的区域中创建背景运动层的方法,该方法用于在两帧参考帧之间插值的帧之间获得时间一致的插值。在大型数据集上的实验结果表明,所提出的网格稀疏化能够将处理时间缩短75%,PSNR小幅下降0.02 dB。提出的TFI方案在插值帧的质量方面优于各种最先进的TFI方法,同时具有最低的处理时间。对具有挑战性的合成序列的进一步实验突出了传统上困难区域的时间一致性。
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Temporally consistent high frame-rate upsampling with motion sparsification
This paper continues our work on occlusion-aware temporal frame interpolation (TFI) that employs piecewise-smooth motion with sharp motion boundaries. In this work, we propose a triangular mesh sparsification algorithm, which allows to trade off computational complexity with reconstruction quality. Furthermore, we propose a method to create a background motion layer in regions that get disoccluded between the two reference frames, which is used to get temporally consistent interpolations among frames interpolated between the two reference frames. Experimental results on a large data set show the proposed mesh sparsification is able to reduce the processing time by 75%, with a minor drop in PSNR of 0.02 dB. The proposed TFI scheme outperforms various state-of-the-art TFI methods in terms of quality of the interpolated frames, while having the lowest processing times. Further experiments on challenging synthetic sequences highlight the temporal consistency in traditionally difficult regions of disocclusion.
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