Video cutout refers to extracting moving objects from videos, which is an important step in many video editing tasks. Recent Mgorithms have limitations in terms of efficiency interaction style and robustness. This pap...Video cutout refers to extracting moving objects from videos, which is an important step in many video editing tasks. Recent Mgorithms 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, and thus could be put into practical use.展开更多
基金This work was supported by the National High Technology Research and Development 863 Program of China under Grant No. 2013AA013903, the Zhejiang Provincial Natural Science Foundation of China under Grant No. LY14F020050, and the National Basic Research 973 Program of China under Grant No. 2011CB302205. Acknowledgement The authors would like to thank anonymous reviewers and editors for their valuable comments.
文摘Video cutout refers to extracting moving objects from videos, which is an important step in many video editing tasks. Recent Mgorithms 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, and thus could be put into practical use.
