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SMURFS: Superpixels from multi-scale refinement of super-regions

Luengo, Imanol; Basham, Mark; French, Andrew P.

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Authors

Imanol Luengo

Mark Basham

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ANDREW FRENCH andrew.p.french@nottingham.ac.uk
Professor of Computer Science



Abstract

Recent applications in computer vision have come to rely on superpixel segmentation as a pre-processing step for higher level vision tasks, such as object recognition, scene labelling or image segmentation. Here, we present a new algorithm, Superpixels from MUlti-scale ReFinement of Super-regions (SMURFS), which not only obtains state-of-the-art superpixels, but can also be applied hierarchically to form what we call n-th order super-regions. In essence, starting from a uniformly distributed set of super-regions, the algorithm iteratively alternates graph-based split and merge optimization schemes which yield superpixels that better represent the image. The split step is performed over the pixel grid to separate large super-regions into different smaller superpixels. The merging process, conversely, is performed over the superpixel graph to create 2nd-order super-regions (super-segments). Iterative refinement over two scale of regions allows the algorithm to achieve better over-segmentation results than current state-of-the-art methods, as experimental results show on the public Berkeley Segmentation Dataset (BSD500).

Citation

Luengo, I., Basham, M., & French, A. P. (2016). SMURFS: Superpixels from multi-scale refinement of super-regions. In Proceedings of the British Machine Vision Conference 2016. https://doi.org/10.5244/C.30.4

Conference Name British Machine Vision Conference (BMVC 2016)
Conference Location York, UK
Start Date Sep 19, 2016
End Date Sep 22, 2016
Acceptance Date Jul 14, 2016
Publication Date Sep 20, 2016
Deposit Date Sep 21, 2016
Publicly Available Date Mar 29, 2024
Peer Reviewed Peer Reviewed
Book Title Proceedings of the British Machine Vision Conference 2016
ISBN 1-901725-59-6
DOI https://doi.org/10.5244/C.30.4
Keywords Segmentation, Super pixels
Public URL https://nottingham-repository.worktribe.com/output/816801
Publisher URL http://www.bmva.org/bmvc/2016/papers/paper004/index.html
Related Public URLs http://www.bmva.org/bmvc/2016/toc.html

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