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Fast Superpixel Segmentation via Boundary Sampling and Interpolation
Li XU Bing LUO Mingming KONG Bo LI Zheng PEI
Publication
IEICE TRANSACTIONS on Information and Systems
Vol.E102-D
No.4
pp.871-874 Publication Date: 2019/04/01 Publicized: 2019/01/22 Online ISSN: 1745-1361
DOI: 10.1587/transinf.2018EDL8168 Type of Manuscript: LETTER Category: Image Recognition, Computer Vision Keyword: superpixel, acceleration, sampling, interpolation,
Full Text: PDF(1.8MB)>>
Summary:
This letter proposes a fast superpixel segmentation method based on boundary sampling and interpolation. The basic idea is as follow: instead of labeling local region pixels, we estimate superpixel boundary by interpolating candidate boundary pixel from a down-sampling image segmentation. On the one hand, there exists high spatial redundancy within each local region, which could be discarded. On the other hand, we estimate the labels of candidate boundary pixels via sampling superpixel boundary within corresponding neighbour. Benefiting from the reduction of candidate pixel distance calculation, the proposed method significantly accelerates superpixel segmentation. Experiments on BSD500 benchmark demonstrate that our method needs half the time compared with the state-of-the-arts while almost no accuracy reduction.
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