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数字抠像的最新研究进展 被引量：13

The Latest Research Progress on Digital Matting
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摘要 数字抠像是图像处理、视频编辑和电影制作中的关键技术.通过数字抠像,从图像或视频的背景中精确地分离出前景,是计算机视觉领域的重要问题.本文首先介绍了目前数字抠像的交互方式,然后把抠像技术分为基于颜色采样、基于像素相似性、基于能量函数以及基于机器学习的四类技术,介绍和分析了其中的典型算法和最新研究成果,并对这些算法的测试结果进行了定量和定性比较,最后总结了数字抠像技术目前的研究状况和未来的发展方向. Digital matting is the key technology in image processing, video editing and film-making applications. It refers to the problem of extracting the foreground objects in the images or videos accurately, which is an important issue in the field of computer vision. In this paper, the interaction modes for digital matting are introduced firstly. After that, matting techniques are divided into four categories： color sampling based, pixel affinity based, energy function based and machine learning based. Classic algorithms and the latest research progress are presented and analyzed, followed by quantitative and qualitative evaluations of these techniques. Finally, the research progress is summarized and future research directions are suggested.
作者 张展鹏 朱青松 谢耀钦
机构地区 中国科学院深圳先进技术研究院 中山大学
出处 《自动化学报》 EI CSCD 北大核心 2012年第10期1571-1584,共14页 Acta Automatica Sinica
基金 国家重点基础研究发展计划(973计划)(2010CB732606) 国家自然科学基金(81171402 30928030)资助~~
关键词 数字抠像 自然图像抠像 图像分割 图像处理 Digital matting, natural image matting, image segmentation, image processing
分类号 TP391.41 [自动化与计算机技术—计算机应用技术]
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参考文献66

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  • 2Smith A R, Blinn J F. Blue screen matting. In: Proceedings of the 23rd ACM Conference on Computer Graphics and Interactive Techniques (SIGGRAPH). New Orleans, USA: ACM, 1996. 259-268.
  • 3Chuang Y Y, Curless B, Salesin D H, Szeliski R. A Bayesian approach to digital matting. In: Proceedings of the 2001 IEEE Conference on Computer Vision and Pattern Recog- nition. Kauai, USA: IEEE, 2001. 264-271.
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  • 5林生佑,潘瑞芳,杜辉,石教英.数字抠图技术综述[J].计算机辅助设计与图形学学报,2007,19(4):473-479. 被引量：19
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二级参考文献58

  • 1林生佑,石教英.基于感知颜色空间的自然图像抠图[J].计算机辅助设计与图形学学报,2005,17(5):915-920. 被引量：16
  • 2Wang J, Cohen MF. Optimized color sampling for robust matting. In: Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition. Minneapolis, 2007. http://ieeexplore.ieee.org/searctVwrapper.jsp?arnumber=4270031.
  • 3Chuang YY, Curless B, Salesin DH, Szeliski R. A Bayesian approach to digital matting. In: Jacobs A, Baldwin T, eds. Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition. Los Alamitos: IEEE Computer Society Press, 2001. 264-271.
  • 4Lin SY, Pan RF, Du H, Shi JY. A survey on digital matting. Journal of Computer--Aided Design & Computer Graphics, 2007,19(4):473--479 (in Chinese with English abstract).
  • 5Wang J, Cohen MF. An iterative optimization approach for unified image segmentation and matting. In: Ma SD, Shum HY, eds. Proc. of the IEEE lnt'! Conf. on Computer Vision. New York: IEEE Computer Society Press, 2005. 936-943.
  • 6Guan Y, Chen W, Liang X, Ding ZG, Peng QS. Easy matting--A stroke based approach for continuous image matting. Computer Graphics Forum, Eurographics, 2006,25(3):567-576.
  • 7Sun J, Jia JY, Tang CK, Shum HY. Poisson matting. ACM Trans. on Graphics, 2004,23(3):315-321.
  • 8Grady L, Schiwietz T, Aharon S, Westermann R. Random walks for interactive alpha-matting. In: Villanueva JJ, ed. Proc. of the 5th IASTED Int'l Conf. on Visualization, Imaging and Image Processing. Benidorm: ACTA Press, 2005.423--429.
  • 9Levin A, Lischinski D, Weiss Y. A closed form solution to natural image matting, ln: Fitzgibbon A, Taylor C, LeCun Y, eds. Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition. Los Alamitos: IEEE Computer Society Press, 2006. 61-68.
  • 10Levin A, Alex RA, Lischinski D. Spectral matting. In: Proc. of the IEEE Conf. on Computer Vision and Pattern Recognition.Minneapolis, 2007. http://people.csail.mit.edu/alevin/papers/spectral-matting-levin-etal-cvpr07.pdf.

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二级引证文献28

自动化学报
2012年 第10期

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