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Robust motion estimation for night-shooting videos using dual-accumulated constraint warping

机译:使用双累积约束扭曲对夜拍视频进行鲁棒的运动估计

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This paper introduces a novel concept of dual-accumulated constraint projection warping, as a robust and efficient motion estimation solution for night video stabilization. Small imaging-sensors used in compact hand-held cameras become very prone to noise and blur under low illumination condition. Restricted lighting results in dark boundaries and degrades textural information of the frame. Presence of these combined textural artifacts makes night-shooting a hard problem for accurate motion estimation. At poor lighting, local intensity variations result in failure of inter-frame feature or block matching correspondence. In the proposed technique, use of projection ensures accuracy under local perturbations, noise and blur conditions, while dual-accumulation eliminates the effect of dark-regions adding robustness to night-shooting condition. Efficiency of the proposed algorithm over the existing motion estimation techniques is tested and verified over different categories of night shooting videos. In addition to night video stabilization the proposed scheme also performs well under normal illumination. (C) 2016 Elsevier Inc. All rights reserved.
机译:本文介绍了一种双重累积约束投影变形的新颖概念,作为一种用于夜间视频稳定的强大而有效的运动估计解决方案。紧凑型手持相机中使用的小型成像传感器在低照度条件下非常容易出现噪声和模糊。受限的照明会导致暗边界,并降低框架的纹理信息。这些组合纹理伪像的存在使夜间拍摄成为精确运动估计的难题。在光线不足的情况下,局部强度变化会导致帧间特征或块匹配对应关系失败。在提出的技术中,使用投影可确保在局部扰动,噪声和模糊条件下的准确性,而双重累加消除了暗区的影响,从而为夜间拍摄条件增加了鲁棒性。在不同类别的夜间拍摄视频上测试和验证了所提出算法相对于现有运动估计技术的效率。除了夜间视频稳定之外,所提出的方案在正常照明下也表现良好。 (C)2016 Elsevier Inc.保留所有权利。

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