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A Bayesian Approach to Digital Matting

Yung-Yu Chuang1     Brian Curless1     David Salesin1,2     Richard Szeliski2

1University of Washington     2Microsoft Research



Abstract
This paper proposes a new Bayesian framework for solving the matting problem, i.e. extracting a foreground element from a background image by estimating an opacity for each pixel of the foreground element. Our approach models both the foreground and background color distributions with spatially-varying mixtures of Gaussians, and assumes a fractional blending of the foreground and background colors to produce the final output. It then uses a maximum-likelihood criterion to estimate the optimal opacity, foreground and background simultaneously. In addition to providing a principled approach to the matting problem, our algorithm effectively handles objects with intricate boundaries, such as hair strands and fur, and provides an improvement over existing techniques for these difficult cases.

Citation (bibTex)
Yung-Yu Chuang, Brian Curless, David H. Salesin, and Richard Szeliski. A Bayesian Approach to Digital Matting. In Proceedings of IEEE Computer Vision and Pattern Recognition (CVPR 2001), Vol. II, 264-271, December 2001

Paper

CVPR 2001 paper (3.6MB PDF)

Addendum
Results

Inputs, Masks and Composites
Blue-screen matting Difference matting Natural image matting
Input
Segmentation
Composite
(Bayesian)
Lighthouse image and background images used in composite courtesy Philip Greenspun, http://philip.greenspun.com.
Woman image was obtained from Corel Knockout's tutorial, Copyright © 2001 Yung-Yu Chuang, Brian Curless, David Salesin, Richard Szeliski and its licensors Corel. All rights reserved.


Blue-screen Matting
Alpha Matte Composite (black) Inset Composite
Mishima
Bayesian
Ground truth


"Synthetic" Natural Image Matting
Alpha Matte Composite Inset
Difference
Matting
Knockout
Ruzon &
Tomasi
Bayesian
Ground
Truth


Natural Image Matting
Alpha Matte Composite Inset Alpha Matte Composite Inset
Knockout
Ruzon &
Tomasi
Bayesian


Additional results
Input
Alpha
Composite
The first two images courtesy Philip Greenspun, http://philip.greenspun.com.
Woman image was obtained from Corel Knockout's tutorial.


cyy -a-t- cs.washington.edu