Alpha estimation in natural images
Publication
, Journal Article
Ruzon, MA; Tomasi, C
Published in: Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
January 1, 2000
Many boundaries between objects in the world project onto curves in an image. However, boundaries involving natural objects (e.g., trees, hair, water, smoke) are often unworkable under this model because many pixels receive light from more than one object. We propose a technique for estimating alpha, the proportion in which two colors mix to produce a color at the boundary. The technique extends blue screen matting to backgrounds that have almost arbitrary color distributions, though coarse knowledge of the boundary's location is required. Results show a number of different objects moved from one image to another while maintaining naturalism.
Duke Scholars
Published In
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN
1063-6919
Publication Date
January 1, 2000
Volume
1
Start / End Page
18 / 25
Citation
APA
Chicago
ICMJE
MLA
NLM
Ruzon, M. A., & Tomasi, C. (2000). Alpha estimation in natural images. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1, 18–25.
Ruzon, M. A., and C. Tomasi. “Alpha estimation in natural images.” Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition 1 (January 1, 2000): 18–25.
Ruzon MA, Tomasi C. Alpha estimation in natural images. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2000 Jan 1;1:18–25.
Ruzon, M. A., and C. Tomasi. “Alpha estimation in natural images.” Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition, vol. 1, Jan. 2000, pp. 18–25.
Ruzon MA, Tomasi C. Alpha estimation in natural images. Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition. 2000 Jan 1;1:18–25.
Published In
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
ISSN
1063-6919
Publication Date
January 1, 2000
Volume
1
Start / End Page
18 / 25