Nonlocal matting

Philip Lee*, Ying Wu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

120 Scopus citations

Abstract

This work attempts to considerably reduce the amount of user effort in the natural image matting problem. The key observation is that the nonlocal principle, introduced to denoise images, can be successfully applied to the alpha matte to obtain sparsity in matte representation, and therefore dramatically reduce the number of pixels a user needs to manually label. We show how to avoid making the user provide redundant and unnecessary input, develop a method for clustering the image pixels for the user to label, and a method to perform high-quality matte extraction. We show that this algorithm is therefore faster, easier, and higher quality than state of the art methods.

Original languageEnglish (US)
Title of host publication2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011
Pages2193-2200
Number of pages8
DOIs
StatePublished - Sep 22 2011
Event2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011 - Colorado Springs, CO, United States
Duration: Jun 20 2011Jun 25 2011

Other

Other2011 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2011
Country/TerritoryUnited States
CityColorado Springs, CO
Period6/20/116/25/11

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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