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International Workshop on Variational, Geometric, and Level Set Methods in Computer Vision

VLSM 2005: Variational, Geometric, and Level Set Methods in Computer Vision pp 186–197Cite as

Trimap Segmentation for Fast and User-Friendly Alpha Matting

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3752))

Abstract

Given an image, digital matting consists in extracting a foreground element from the background. Standard methods are initialized with a trimap, a partition of the image into three regions: a definite foreground, a definite background, and a blended region where pixels are considered as a mixture of foreground and background colors. Recovering these colors and the proportion of mixture between both is an under-constrained inverse problem, sensitive to its initialization: one has to specify an accurate trimap, leaving undetermined as few pixels as possible.

First, we propose a new segmentation scheme to extract an accurate trimap from just a coarse indication of some background and/or foreground pixels. Standard statistical models are used for the foreground and the background, while a specific one is designed for the blended region. The segmentation of the three regions is conducted simultaneously by an iterative Graph Cut based optimization scheme. This user-friendly trimap is similar to carefully hand specified ones.

As a second step, we take advantage of our blended region model to design an improved matting method coherent. Based on global statistics rather than on local ones, our method is much faster than standard Bayesian matting, without quality loss, and also usable with manual trimaps.

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Author information

Authors and Affiliations

  1. CERTIS, ENPC, 77455, Marne-la-Vallée, France

    Olivier Juan & Renaud Keriven

Authors
  1. Olivier Juan
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  2. Renaud Keriven
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Editor information

Editors and Affiliations

  1. MAS - Ecole Centrale Paris, Grande Voie des Vignes, 92295, Chatenay-Malabry, France

    Nikos Paragios

  2. I.N.R.I.A, 2004 route des lucioles,, 06902, Sophia-Antipolis, France

    Olivier Faugeras

  3. Department of Mathematics, UCLA,  

    Tony Chan

  4. Image and Pattern Analysis Group, Heidelberg Collaboratory for Image Processing, University of Heidelberg, Germany

    Christoph Schnörr

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© 2005 Springer-Verlag Berlin Heidelberg

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Juan, O., Keriven, R. (2005). Trimap Segmentation for Fast and User-Friendly Alpha Matting. In: Paragios, N., Faugeras, O., Chan, T., Schnörr, C. (eds) Variational, Geometric, and Level Set Methods in Computer Vision. VLSM 2005. Lecture Notes in Computer Science, vol 3752. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11567646_16

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  • DOI: https://doi.org/10.1007/11567646_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29348-4

  • Online ISBN: 978-3-540-32109-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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