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ECCV
2002
Springer

Bayesian Estimation of Layers from Multiple Images

12 years 7 months ago
Bayesian Estimation of Layers from Multiple Images
When estimating foreground and background layers (or equivalently an alpha matte), it is often the case that pixel measurements contain mixed colours which are a combination of foreground and background. Object boundaries, especially at thin sub-pixel structures like hair, pose a serious problem. In this paper we present a multiple view algorithm for computing the alpha matte. Using a Bayesian framework, we model each pixel as a combined sample from the foreground and background and compute a MAP estimate to factor the two. The novelties in this work include the incorporation of three different types of priors for enhancing the results in problematic scenes. The priors used are inequality constraints on colour and alpha values, spatial continuity, and the probability distribution of alpha values. The combination of these priors result in accurate and visually satisfying estimates. We demonstrate the method on real image sequences with varying degrees of geometric and photometric comple...
Yonatan Wexler, Andrew W. Fitzgibbon, Andrew Zisse
Added 16 Oct 2009
Updated 16 Oct 2009
Type Conference
Year 2002
Where ECCV
Authors Yonatan Wexler, Andrew W. Fitzgibbon, Andrew Zisserman
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