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Spatio-temporal weighting in local patches for direct estimation of camera motion in video stabilization

机译:在本地补丁中时空加权以直接估计视频稳定中的摄像机运动

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摘要

This paper presents a robust video stabilization method by solving a novel formulation for the camera motion estimation. We introduce spatio-temporal weighting on local patches in optimization formulation, which enables one-step direct estimation without outlier elimination adopted in most existing methods. The spatio-temporal weighting represents the reliability of a local region in estimation of camera motion. The weighting emphasizes regions which have the similar motion to the camera motion, such as backgrounds, and reduces the influence of unimportant regions, such as moving objects. In this paper, we develop a formula to determine the spatio-temporal weights considering the age, edges, saliency, and distribution information of local patches. The proposed scheme reduces the computational load by eliminating the integration part of local motions and decreases accumulation of fitting errors in the existing two-step estimation methods. Through numerical experiments on several unstable videos, we verify that the proposed method gives better performance in camera motion estimation and stabilization of jittering video sequences.
机译:本文提出了一种鲁棒的视频稳定方法,通过解决摄像机运动估计的新公式。我们在优化公式中引入了对局部补丁的时空加权,这使得一步一步直接估算而大多数现有方法都没有采用离群值消除。时空加权表示摄像机运动估计中局部区域的可靠性。加权强调具有与摄像机运动类似的运动的区域(例如背景),并减少不重要区域的影响(例如运动的对象)。在本文中,我们开发了一个公式来确定时空权重,其中考虑了年龄,边缘,显着性和局部斑块的分布信息。所提出的方案通过消除局部运动的积分部分来减轻计算负担,并减少了现有的两步估计方法中拟合误差的累积。通过对几个不稳定视频的数值实验,我们验证了该方法在摄像机运动估计和抖动视频序列稳定方面具有更好的性能。

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