Sparse codes as alpha matte

• Main Authors: Johnson, Jubin, Rajan, Deepu, Cholakkal, Hisham
• Other Authors: School of Computer Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2015
• Subjects: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision; DRNTU::Engineering::Computer science and engineering::Computing methodologies::Computer graphics
• Online Access: https://hdl.handle.net/10356/93714; http://hdl.handle.net/10220/38388; http://www.bmva.org/bmvc/2014/files/paper052.pdf
• Institution: Nanyang Technological University

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.