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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Moore, A.P. Prince, S.J.D. Warrell, J. |
| Copyright Year | 2010 |
| Description | Author affiliation: Oxford Brookes University, Oxford, OX33 1HX, UK (Warrell, J.) || University College London, Gower Street, WC1E 6BT, UK (Moore, A.P.; Prince, S.J.D.) |
| Abstract | Unsupervised over-segmentation of an image into super-pixels is a common preprocessing step for image parsing algorithms. Superpixels are used as both regions of support for feature vectors and as a starting point for the final segmentation. Recent algorithms that construct superpixels that conform to a regular grid (or superpixel lattice) have used greedy solutions. In this paper we show that we can construct a globally optimal solution in either the horizontal or vertical direction using a single graph cut. The solution takes into account both edges in the image, and the coherence of the resulting superpixel regions. We show that our method outperforms existing algorithms for computing superpixel lattices. Additionally, we show that performance can be comparable or better than other contemporary segmentation algorithms which are not constrained to produce a lattice. |
| Starting Page | 2117 |
| Ending Page | 2124 |
| File Size | 3804836 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781424469840 |
| ISSN | 10636919 |
| e-ISBN | 9781424469857 |
| DOI | 10.1109/CVPR.2010.5539890 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-06-13 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Lattices Image segmentation Layout Strips Educational institutions Computer vision Pipelines Inference algorithms Cost function Topology |
| Content Type | Text |
| Resource Type | Article |
| Subject | Computer Vision and Pattern Recognition Software |
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