SMURFS: superpixels from multi-scale refinement of super-regions
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 (S...
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| Format: | Conference or Workshop Item |
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2016
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| Online Access: | https://eprints.nottingham.ac.uk/37025/ |
| _version_ | 1848795377245880320 |
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| author | Luengo, Imanol Basham, Mark French, Andrew P. |
| author_facet | Luengo, Imanol Basham, Mark French, Andrew P. |
| author_sort | Luengo, Imanol |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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). |
| first_indexed | 2025-11-14T19:31:07Z |
| format | Conference or Workshop Item |
| id | nottingham-37025 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T19:31:07Z |
| publishDate | 2016 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-370252020-05-04T18:11:33Z https://eprints.nottingham.ac.uk/37025/ SMURFS: superpixels from multi-scale refinement of super-regions Luengo, Imanol Basham, Mark French, Andrew P. 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). 2016-09-20 Conference or Workshop Item PeerReviewed Luengo, Imanol, Basham, Mark and French, Andrew P. (2016) SMURFS: superpixels from multi-scale refinement of super-regions. In: British Machine Vision Conference (BMVC 2016), 20-22nd Sept 2016, York, UK. Segmentation Super pixels http://www.bmva.org/bmvc/2016/papers/paper004/index.html |
| spellingShingle | Segmentation Super pixels Luengo, Imanol Basham, Mark French, Andrew P. SMURFS: superpixels from multi-scale refinement of super-regions |
| title | SMURFS: superpixels from multi-scale refinement of super-regions |
| title_full | SMURFS: superpixels from multi-scale refinement of super-regions |
| title_fullStr | SMURFS: superpixels from multi-scale refinement of super-regions |
| title_full_unstemmed | SMURFS: superpixels from multi-scale refinement of super-regions |
| title_short | SMURFS: superpixels from multi-scale refinement of super-regions |
| title_sort | smurfs: superpixels from multi-scale refinement of super-regions |
| topic | Segmentation Super pixels |
| url | https://eprints.nottingham.ac.uk/37025/ https://eprints.nottingham.ac.uk/37025/ |