"Lattice Cut" - Constructing superpixels using layer constraints.
2010 IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR).
(pp. 2117 - 2124).
IEEE COMPUTER SOC
Unsupervised over-segmentation of an image into superpixels 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.
|Title:||"Lattice Cut" - Constructing superpixels using layer constraints|
|Event:||23rd IEEE Conference on Computer Vision and Pattern Recognition (CVPR)|
|Location:||San Francisco, CA|
|Dates:||2010-06-13 - 2010-06-18|
|UCL classification:||UCL > School of BEAMS
UCL > School of BEAMS > Faculty of Engineering Science
UCL > School of BEAMS > Faculty of Engineering Science > Management Science and Innovation
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