DocumentCode
3295955
Title
The Image Matting Method with Regularized Matte
Author
Gao, Junbin ; Paul, Manoranjan ; Liu, Jun
Author_Institution
Sch. of Comput. & Math., Charles Sturt Univ., Bathurst, NSW, Australia
fYear
2012
fDate
9-13 July 2012
Firstpage
550
Lastpage
555
Abstract
Image matting refers to the problem of accurately extracting foreground objects in images and video. The most recent works in natural image matting relies on the local and manifold smoothness assumptions on foreground and background colors on which a cost function is established. In this paper, we present a framework of formulating new regularization for robust solutions and illustrate new algorithms using the standard benchmark images.
Keywords
feature extraction; image colour analysis; smoothing methods; video signal processing; background color; cost function; foreground color; foreground object extraction; local smoothness assumption; manifold smoothness assumption; natural image matting; regularized matte; video; Cost function; Image color analysis; Laplace equations; Linear programming; Manifolds; Vectors; Image Matting; Laplacian Matrix; Local Tangent Space Alignment; Manifold Learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Multimedia and Expo (ICME), 2012 IEEE International Conference on
Conference_Location
Melbourne, VIC
ISSN
1945-7871
Print_ISBN
978-1-4673-1659-0
Type
conf
DOI
10.1109/ICME.2012.182
Filename
6298459
Link To Document