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Soft scissors: an interactive tool for realtime high quality matting
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Source
ACM Transactions on Graphics (TOG) archive
Volume 26 ,  Issue 3  (July 2007) table of contents
Proceedings of ACM SIGGRAPH 2007
SESSION: Image slicing & stretching table of contents
Article No. 9  
Year of Publication: 2007
ISSN:0730-0301
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Authors
Jue Wang  University of Washington
Maneesh Agrawala  University of California, Berkeley
Michael F. Cohen  Microsoft Research
Publisher
ACM  New York, NY, USA
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ABSTRACT

We present Soft Scissors, an interactive tool for extracting alpha mattes of foreground objects in realtime. We recently proposed a novel offline matting algorithm capable of extracting high-quality mattes for complex foreground objects such as furry animals [Wang and Cohen 2007]. In this paper we both improve the quality of our offline algorithm and give it the ability to incrementally update the matte in an online interactive setting. Our realtime system efficiently estimates foreground color thereby allowing both the matte and the final composite to be revealed instantly as the user roughly paints along the edge of the foreground object. In addition, our system can dynamically adjust the width and boundary conditions of the scissoring paint brush to approximately capture the boundary of the foreground object that lies ahead on the scissor's path. These advantages in both speed and accuracy create the first interactive tool for high quality image matting and compositing.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Chuang, Y.-Y., Curless, B., Salesin, D. H., and Szeliski, R. 2001. A bayesian approach to digital mating. In Proceedings of IEEE CVPR, 264--271.
 
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CORPORATION, C. 2002. Knockout user guide.
 
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INCORP., A. S. 2002. Adobe photoshop user guide.
 
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Wang, J., and Cohen, M. F. 2007. Optimized color sampling for robust matting. In Proceedings of IEEE CVPR.


Collaborative Colleagues:
Jue Wang: colleagues
Maneesh Agrawala: colleagues
Michael F. Cohen: colleagues