Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/93714
Title: Sparse codes as alpha matte
Authors: Johnson, Jubin
Rajan, Deepu
Cholakkal, Hisham
Keywords: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
DRNTU::Engineering::Computer science and engineering::Computing methodologies::Computer graphics
Issue Date: 2014
Source: Johnson, J., Rajan, D., & Cholakkal, H. (2014). Sparse codes as alpha matte. Proceedings of the British Machine Vision Conference. BMVA Press.
Abstract: In this paper, image matting is cast as a sparse coding problem wherein the sparse codes directly give the estimate of the alpha matte. Hence, there is no need to use the matting equation that restricts the estimate of alpha from a single pair of foreground (F) and background (B) samples. A probabilistic segmentation provides a confidence value on the pixel belonging to F or B, based on which a dictionary is formed for use in sparse coding. This allows the estimate of alpha from more than just one pair of (F, B) samples. Experimental results on a benchmark dataset show the proposed method performs close to state-of-the-art methods.
URI: https://hdl.handle.net/10356/93714
http://hdl.handle.net/10220/38388
Rights: ©The Author(s) (British Machines Vision Conference) This paper was published in [Proceedings of the British Machine Vision Conference] and is made available as an electronic reprint (preprint) with permission of [British Machines Vision Conference]. The published version is available at: [http://www.bmva.org/bmvc/2014/files/paper052.pdf]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.
metadata.item.grantfulltext: open
metadata.item.fulltext: With Fulltext
Appears in Collections:SCSE Conference Papers

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