Cited By
View all- Chen XHe FPan YAi H(2017)Selective Image Matting with Scalable Variance and Model RectificationData Science10.1007/978-981-10-6385-5_45(534-548)Online publication date: 16-Sep-2017
Rank Reduced Alternative Matting Laplacian
Article No.: 7, Pages 1 - 7
Abstract
Cutting out objects from an image and estimating the corresponding transparency masks is a key step in post-production. One popular technique for pulling the transparency values is the closed-form approach of Levin et al.[6]. It is used in many matting algorithms for smoothing the initial noisy guess of the transparency map. Recently we proposed in [8] a more efficient alternative formulation to the original closed-form approach. In the new formulation the matting model parameters are fully exposed, which allows for more useful spatial constraints to be defined. We present in this paper how this new approach [8] can be sped up by considering local re-parametrisation of the matting model.
References
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X. Chen, D. Zou, S. Zhou, Q. Zhao, and P. Tan. Image matting with local and nonlocal smooth priors. In Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on, pages 1902--1907, June 2013.
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Y.-Y. Chuang, B. Curless, D. Salesin, and R. Szeliski. A bayesian approach to digital matting. In Computer Vision and Pattern Recognition, 2001. CVPR 2001. Proceedings of the 2001 IEEE Computer Society Conference on, volume 2, pages II--264--II--271 vol.2, 2001.
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K. He, C. Rhemann, C. Rother, X. Tang, and J. Sun. A global sampling method for alpha matting. In Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on, pages 2049--2056, June 2011.
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P. M. Hillman and J. M. Hannah. Natural Image Matting. In International Conference on Video, Vision and Graphics, pages 211--218, 2005.
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L. Karacan, A. Erdem, and E. Erdem. Image matting with kl-divergence based sparse sampling. June 2015.
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A. Levin, D. Lischinski, and Y. Weiss. A closed-form solution to natural image matting. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 30(2):228--242, Feb 2008.
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F. Pitié. Alternative Matting Laplacian reference code. https://github.com/frcs/alternative-matting-laplacian.
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F. Pitié. Alternative Matting Laplacian. In International Conference on Image Processing (ICIP). IEEE, 2016. https://arxiv.org/abs/1605.04785.
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C. Rhemann, C. Rother, J. Wang, M. Gelautz, P. Kohli, and P. Rott. Alpha matting evaluation website. http://www.alphamatting.com.
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C. Rhemann, C. Rother, J. Wang, M. Gelautz, P. Kohli, and P. Rott. A perceptually motivated online benchmark for image matting. In Proceddings of the IEEE Conference on Computer Vision and Pattern Recognition, 2009. Posterpräsentation: IEEE Conference on Computer Vision and Pattern Recognition, 2009. CVPR '09, Miami, Florida, USA; 2009-06-20 -- 2009-06-25.
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E. Shahrian, D. Rajan, B. Price, and S. Cohen. Improving image matting using comprehensive sampling sets. In Computer Vision and Pattern Recognition (CVPR), 2013 IEEE Conference on, pages 636--643, June 2013.
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D. Singaraju, C. Rother, and C. Rhemann. New appearance models for natural image matting. In Computer Vision and Pattern Recognition, 2009. CVPR 2009. IEEE Conference on, pages 659--666, June 2009.
Index Terms
- Rank Reduced Alternative Matting Laplacian
Index terms have been assigned to the content through auto-classification.
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Published In
December 2016
90 pages
ISBN:9781450347440
DOI:10.1145/2998559
Copyright © 2016 ACM.
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In-Cooperation
- The Foundry: The Foundry Visionmongers Ltd.
- University of Bath: University of Bath
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 12 December 2016
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CVMP 2016
CVMP 2016: 13th European Conference on Visual Media Production
December 12 - 13, 2016
London, United Kingdom
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Overall Acceptance Rate 40 of 67 submissions, 60%
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Cited By
View all- Chen XHe FPan YAi H(2017)Selective Image Matting with Scalable Variance and Model RectificationData Science10.1007/978-981-10-6385-5_45(534-548)Online publication date: 16-Sep-2017
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