SIGGRAPH '96 Proceedings of the 23rd annual conference on Computer graphics and interactive techniques
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Example-Based Super-Resolution
IEEE Computer Graphics and Applications
Stereo Matching Using Belief Propagation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
ACM SIGGRAPH 2004 Papers
An Iterative Optimization Approach for Unified Image Segmentation and Matting
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision - Volume 2
A Closed Form Solution to Natural Image Matting
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
An automatic evaluation method of image mattes
VIIP '07 The Seventh IASTED International Conference on Visualization, Imaging and Image Processing
Approximate maximum likelihood hyperparameter estimation for Gibbs priors
IEEE Transactions on Image Processing
An introduction to kernel-based learning algorithms
IEEE Transactions on Neural Networks
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Image matting is a technique used for extracting a foreground object in a static image by estimating the opacity, called alpha matte, at each pixel in the foreground image layer. The common drawback of the previous matting approaches is the decrease in performance when a foreground and its background have similar colors. In order to overcome this problem, we propose a method of estimating alpha mattes by using the color information of neighboring pixels and the support vector machine. We define a cost function on the basis of a Markov random field by considering not only a single pixel but also its neighboring pixels and utilizing the support vector machine to enhance the discrimination between the foreground and the background. This cost function is minimized by the belief propagation and the sampling methods. Qualitative and quantitative results have shown a favorable matting performance compared to the other methods.