The Image Matting Method with Regularized Matte

Image matting refers to the problem of accurately extracting foreground objects in images and video. The most recent works in natural image matting relies on the local and manifold smoothness assumptions on foreground and background colors on which a cost function is established. In this paper, we present a framework of formulating new regularization for robust solutions and illustrate new algorithms using the standard benchmark images.

[1]  Jieping Ye,et al.  Multi-Task Feature Learning Via Efficient l2, 1-Norm Minimization , 2009, UAI.

[2]  Jean-Philippe Vert,et al.  Group lasso with overlap and graph lasso , 2009, ICML '09.

[3]  Guillermo Sapiro,et al.  Geodesic Matting: A Framework for Fast Interactive Image and Video Segmentation and Matting , 2009, International Journal of Computer Vision.

[4]  Marc Teboulle,et al.  A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems , 2009, SIAM J. Imaging Sci..

[5]  Michael F. Cohen,et al.  Image and Video Matting , 2008 .

[6]  Junbin Gao,et al.  Image Matting via Local Tangent Space Alignment , 2011, 2011 International Conference on Digital Image Computing: Techniques and Applications.

[7]  Jian Sun,et al.  Lazy snapping , 2004, SIGGRAPH 2004.

[8]  Hongyuan Zha,et al.  Principal Manifolds and Nonlinear Dimension Reduction via Local Tangent Space Alignment , 2002, ArXiv.

[9]  Guillermo Sapiro,et al.  A Geodesic Framework for Fast Interactive Image and Video Segmentation and Matting , 2007, 2007 IEEE 11th International Conference on Computer Vision.

[10]  Rüdiger Westermann,et al.  RANDOM WALKS FOR INTERACTIVE ALPHA-MATTING , 2005 .

[11]  Dani Lischinski,et al.  A Closed-Form Solution to Natural Image Matting , 2008 .

[12]  R. Tibshirani Regression Shrinkage and Selection via the Lasso , 1996 .

[13]  Jian Sun,et al.  Fast matting using large kernel matting Laplacian matrices , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[14]  Michael F. Cohen,et al.  Image and Video Matting: A Survey , 2007, Found. Trends Comput. Graph. Vis..

[15]  David Salesin,et al.  A Bayesian approach to digital matting , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[16]  Jiaya Jia,et al.  Poisson matting , 2004, SIGGRAPH 2004.

[17]  Y. Nesterov A method for solving the convex programming problem with convergence rate O(1/k^2) , 1983 .

[18]  Y. Nesterov Gradient methods for minimizing composite objective function , 2007 .

[19]  Hongyuan Zha,et al.  Principal manifolds and nonlinear dimensionality reduction via tangent space alignment , 2004, SIAM J. Sci. Comput..

[20]  Andrew Blake,et al.  "GrabCut" , 2004, ACM Trans. Graph..