2013
CVPR
CVPR 2013
Image Matting with Local and Nonlocal Smooth Priors
Abstract
In this paper we propose a novel alpha matting method with local and nonlocal smooth priors. We observe that the manifold preserving editing propagation [4] essentially introduced a nonlocal smooth prior on the alpha matte. This nonlocal smooth prior and the well known local smooth prior from matting Laplacian complement each other. So we combine them with a simple data term from color sampling in a graph model for nature image matting. Our method has a closed-form solution and can be solved efficiently. Compared with the state-of-the-art methods, our method produces more accurate results according to the evaluation on standard benchmark datasets.
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Conference Pioneer
— CVPR 2013
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Topic Pioneer
— Image Editing
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Interdisciplinary Bridge
— Computer Vision and Deep Learning and Machine Learning and Mathematics & Optimization
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Trend Setter
— Model Architecture
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Keyword Pioneer
— image matting
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Hot Topic Early Bird
— image processing
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Machine Learning > Optimization & Theory > Optimization
Deep Learning > Techniques > Model Architecture
Mathematics & Optimization > Mathematics > Graph Theory
Computer Vision > Processing > Image Processing
Computer Vision > Generation > Image Editing
Mathematics & Optimization > Optimization > Graph Theory