Jia Jiaya, Tai Yu-Wing, Wu Tai-Pang, Tang Chi-Keung
Department of Computer Science and Engineering, the Chinese University of Hong Kong, Shatin NT.
IEEE Trans Pattern Anal Mach Intell. 2006 May;28(5):832-9. doi: 10.1109/TPAMI.2006.108.
This paper presents a complete system capable of synthesizing a large number of pixels that are missing due to occlusion or damage in an uncalibrated input video. These missing pixels may correspond to the static background or cyclic motions of the captured scene. Our system employs user-assisted video layer segmentation, while the main processing in video repair is fully automatic. The input video is first decomposed into the color and illumination videos. The necessary temporal consistency is maintained by tensor voting in the spatio-temporal domain. Missing colors and illumination of the background are synthesized by applying image repairing. Finally, the occluded motions are inferred by spatio-temporal alignment of collected samples at multiple scales. We experimented on our system with some difficult examples with variable illumination, where the capturing camera can be stationary or in motion.
本文提出了一个完整的系统，该系统能够合成由于遮挡或损坏而在未校准输入视频中缺失的大量像素。这些缺失的像素可能对应于捕获场景的静态背景或循环运动。我们的系统采用用户辅助的视频层分割，而视频修复中的主要处理是完全自动的。首先将输入视频分解为颜色视频和光照视频。通过时空域中的张量投票来保持必要的时间一致性。通过应用图像修复来合成背景的缺失颜色和光照。最后，通过在多个尺度上对收集的样本进行时空对齐来推断被遮挡的运动。我们用一些光照变化的困难示例对我们的系统进行了实验，其中捕获相机可以是静止的或运动的。
