Parallel accelerated matting method based on local learning

1Citations
Citations of this article
2Readers
Mendeley users who have this article in their library.
Get full text

Abstract

To pursue effective and fast matting method is of great importance in digital image editing. This paper proposes a scheme to accelerate learning based digital matting and implement it on modern GPU in parallel, which involves learning stage and solving stage. Firstly, we present GPU-based method to accelerate the pixel-wise learning stage. Then, trimap skeleton based algorithm is proposed to divide the image into blocks and process blocks in parallel to speed up the solving stage. Experimental results demonstrated that the proposed scheme achieves a maximal 12+ speedup over previous serial methods without degrading segmentation precision.

Cite

CITATION STYLE

APA

Li, X., & Cui, Q. (2017). Parallel accelerated matting method based on local learning. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10111 LNCS, pp. 152–162). Springer Verlag. https://doi.org/10.1007/978-3-319-54181-5_10

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free