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High-Speed Video from Asynchronous Camera Array

机译:来自异步摄像机阵列的高速视频

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This paper presents a method for capturing high-speed video using an asynchronous camera array. Our method sequentially fires each sensor in a camera array with a small time offset and assembles captured frames into a high-speed video according to the time stamps. The resulting video, however, suffers from parallax jittering caused by the viewpoint difference among sensors in the camera array. To address this problem, we develop a dedicated novel view synthesis algorithm that transforms the video frames as if they were captured by a single reference sensor. Specifically, for any frame from a non-reference sensor, we find the two temporally neighboring frames captured by the reference sensor. Using these three frames, we render a new frame with the same time stamp as the non-reference frame but from the viewpoint of the reference sensor. Specifically, we segment these frames into super-pixels and then apply local content-preserving warping to warp them to form the new frame. We employ a multi-label Markov Random Field method to blend these warped frames. Our experiments show that our method can produce high-quality and high-speed video of a wide variety of scenes with large parallax, scene dynamics, and camera motion and outperforms several baseline and state-of-the-art approaches.
机译:本文提出了一种使用异步摄像机阵列捕获高速视频的方法。我们的方法以较小的时间偏移顺序触发相机阵列中的每个传感器,并根据时间戳将捕获的帧组合成高速视频。然而,由于摄像机阵列中的传感器之间的视点差异,所产生的视频遭受视差抖动的影响。为了解决这个问题,我们开发了一种专用的新颖的视图合成算法,该算法可以对视频帧进行转换,就好像它们是由单个参考传感器捕获的一样。具体来说,对于来自非参考传感器的任何帧,我们找到参考传感器捕获的两个时间相邻的帧。使用这三个帧,我们从参考传感器的角度渲染了一个与非参考帧具有相同时间戳的新帧。具体来说,我们将这些帧分割为超像素,然后应用保留局部内容的扭曲对它们进行扭曲以形成新的帧。我们采用多标签马尔可夫随机场方法来混合这些扭曲的帧。我们的实验表明,我们的方法可以产生具有大视差,场景动态和相机运动的各种场景的高质量和高速视频,并且性能优于几种基线和最新方法。

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