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This paper addresses the well-known problem of natural image matting. Most of the previous matting algorithms require the user to define the tri-map, which is an inconvenient work and sometimes a burden, especially in a complex situation. This paper uses ceratain user defined foreground and background strokes to estimate the image matte. First we use a Gauss Markov random field to model the matting problem. Then we use the least square optimization approach to solve it. Experimental results show that our approach could properly handle confused boundaries. It also could deal with semi-transparent conditions such as fire etc.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
139--152
Opis fizyczny
Bibliogr. 7 poz., il.
Twórcy
autor
autor
autor
- The Institute of Artificial Intelligence and Robotics Xi'an Jiao Tong University China, wkques@sina.com
Bibliografia
- [1] Smith A., Blinn J.: SIGGRAPH '96: Blue screen matting, 259-268.2, 1996.
- [2] Berman A., Vlahos P., Dadourian A.: Comprehensive method for removing from an image the background surrounding a selected object. U.S. Patent 6, 134, 135, 2000.
- [3] Ruzon M. A., Tomasic C.: CVPR: Alpha estimation in natural images, 18-25, 2000.
- [4] Chuang Y-Y., Curless B., Salesin D. H., Szeliski R.: CVPR: A Bayesian approach to digital matting, II, 264-271, 2001.
- [5] Sun J., Jia J., Tang C. K., Shum H. Y.: ACM SIGGRAPH: Poisson Matting, 2004.
- [6] Li J. Y., Sun J., Tang C. K., Shum H. Y.: ACM SIGGRAPH: Lazy snapping, 303-308, 2004.
- [7] Wang J., Cohen M. F.: ICCV: An Interative Optimization Approach for United Image Segmentation and Matting, 2005.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BWA1-0027-0018