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基于笔画选取的高效视频对象切割

Efficient Video Cutout by Paint Selection

  • 摘要: 视频对象切割是从视频中提取出运动的对象,这是许多视频编辑任务中的重要操作.由于前人提出的算法在效率、交互方式和稳定性方面存在不足,本文提出了用于视频对象逐步提取的新方法.该方法减少了人工交互并能为用户提供快速的结果反馈.通过提取局部和紧凑的视频特征,建立了基于图的优化模型.该模型为视频中所有空域和时域上相邻的块建立了联系.该优化能够通过图割算法高效求解,进而得到视频对象逐步提取的结果.进一步地,本文提出了基于采样的帧间连续的透明值抠图算法来进一步提升视频对象提取的效果.实验结果表明本文提出的基于笔画选取的视频对象切割算法比先前基于笔画交互的方法更加直观和高效,因此能够应用于实际.

     

    Abstract: Video cutout refers to extracting moving objects from videos, which is an important step in many video editing tasks. Recent algorithms have limitations in terms of efficiency, interaction style and robustness. This paper presents a novel method for progressive video cutout with less user interaction and fast feedback. By exploring local and compact features, an optimization is constructed based on a graph model which establishes spatial and temporal relationship of neighboring patches in video frames. This optimization enables an efficient solution for progressive video cutout using graph cuts. Furthermore, a sampling-based method for temporally coherent matting is proposed to further refine video cutout results. Experiments demonstrate that our video cutout by paint selection is more intuitive and efficient for users than previous stroke-based methods, thus could be put into practical use.

     

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