异步摄像机阵列的高速视频

Si Lu
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引用次数: 2

摘要

本文提出了一种利用异步摄像机阵列捕捉高速视频的方法。我们的方法以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装成高速视频。然而,由此产生的视频会受到摄像机阵列中传感器视点差异引起的视差抖动的影响。为了解决这个问题,我们开发了一种专用的新颖视图合成算法,可以将视频帧转换为单个参考传感器捕获的视频帧。具体来说,对于来自非参考传感器的任何帧,我们找到由参考传感器捕获的两个时间相邻帧。利用这三帧,我们从参考传感器的角度呈现了一个与非参考帧具有相同时间戳的新帧。具体来说,我们将这些帧分割成超像素,然后应用局部内容保留扭曲来扭曲它们以形成新帧。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,场景动态和摄像机运动的各种场景的高质量和高速视频,并且优于几种基线和最先进的方法。
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High-Speed Video from Asynchronous Camera Array
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.
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