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Scene-aware Video Stabilization by Visual Fixation

机译:视觉固定的场景感知视频稳定

摘要

Visual fixation is employed by humans and some animals to keep a specific 3D location at the center of the visual gaze. Inspired by this phenomenon in nature, this paper explores the idea to transfer this mechanism to the context of video stabilization for a hand-held video camera. A novel approach is presented that stabilizes a video by fixating on automatically extracted 3D target points. This approach is different from existing automatic solutions that stabilize the video by smoothing. To determine the 3D target points, the recorded scene is analyzed with a state-of-the-art structure-from-motion algorithm, which estimates camera motion and reconstructs a 3D point cloud of the static scene objects. Special algorithms are presented that search either virtual or real 3D target points, which back-project close to the center of the image for as long a period of time as possible. The stabilization algorithm then transforms the original images of the sequence so that these 3D target points are kept exactly in the center of the image, which, in case of real 3D target points, produces a perfectly stable result at the image center. The approach is evaluated on a variety of videos taken with a hand-held camera in natural scenes.
机译:人类和某些动物使用视觉固定,以将特定的3D位置保持在视线的中心。受到自然界中这种现象的启发,本文探讨了将这种机制转移到手持摄像机视频稳定环境中的想法。提出了一种新颖的方法,该方法通过固定在自动提取的3D目标点上来稳定视频。这种方法不同于现有的通过平滑来稳定视频的自动解决方案。为了确定3D目标点,使用最先进的运动结构算法对记录的场景进行分析,该算法可估算摄像机运动并重建静态场景对象的3D点云。提出了可以搜索虚拟或真实3D目标点的特殊算法,这些目标点会在尽可能长的时间内反向投影到图像中心附近。然后,稳定算法对序列的原始图像进行转换,以使这些3D目标点精确地保持在图像的中心,如果是真实的3D目标点,则在图像中心产生完美稳定的结果。在自然场景中,可以使用手持摄像机拍摄的各种视频对这种方法进行评估。

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