@inproceedings{55df9ce67cfd416b9c9a9375db43ca47,
title = "Contour-constrained superpixels for image and video processing",
abstract = "A novel contour-constrained superpixel (CCS) algorithm is proposed in this work. We initialize superpixels and regions in a regular grid and then refine the superpixel label of each region hierarchically from block to pixel levels. To make superpixel boundaries compatible with object contours, we propose the notion of contour pattern matching and formulate an objective function including the contour constraint. Furthermore, we extend the CCS algorithm to generate temporal superpixels for video processing. We initialize superpixel labels in each frame by transferring those in the previous frame and refine the labels to make superpixels temporally consistent as well as compatible with object contours. Experimental results demonstrate that the proposed algorithm provides better performance than the state-of-the-art superpixel methods.",
author = "Lee, \{Se Ho\} and Jang, \{Won Dong\} and Kim, \{Chang Su\}",
note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017 ; Conference date: 21-07-2017 Through 26-07-2017",
year = "2017",
month = nov,
day = "6",
doi = "10.1109/CVPR.2017.621",
language = "English",
series = "Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "5863--5871",
booktitle = "Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2017",
}