Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings - 2013 IEEE International Conference on Computer Vision |
| Subtitle of host publication | ICCV 2013 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 385-392 |
| Number of pages | 8 |
| ISBN (print) | 9781479928392 |
| Publication status | Published - 2014 |
| Event | 2013 14th IEEE International Conference on Computer Vision, ICCV 2013 - Sydney, NSW, Australia Duration: 1 Dec 2013 → 8 Dec 2013 |
Publication series
| Name | Proceedings of the IEEE International Conference on Computer Vision |
|---|
Abstract
Super pixel algorithms represent a very useful and increasingly popular preprocessing step for a wide range of computer vision applications, as they offer the potential to boost efficiency and effectiveness. In this regards, this paper presents a highly competitive approach for temporally consistent super pixels for video content. The approach is based on energy-minimizing clustering utilizing a novel hybrid clustering strategy for a multi-dimensional feature space working in a global color subspace and local spatial subspaces. Moreover, a new contour evolution based strategy is introduced to ensure spatial coherency of the generated super pixels. For a thorough evaluation the proposed approach is compared to state of the art super voxel algorithms using established benchmarks and shows a superior performance.
Keywords
- over-segmentation, superpixel, supervoxel, tracking, video segmentation
ASJC Scopus subject areas
- Computer Science(all)
- Software
- Computer Science(all)
- Computer Vision and Pattern Recognition
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Proceedings - 2013 IEEE International Conference on Computer Vision: ICCV 2013. Institute of Electrical and Electronics Engineers Inc., 2014. p. 385-392 6751157 (Proceedings of the IEEE International Conference on Computer Vision).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - Temporally Consistent Superpixels
AU - Reso, Matthias
AU - Jachalsky, Jorn
AU - Rosenhahn, Bodo
AU - Ostermann, Jorn
PY - 2014
Y1 - 2014
N2 - Super pixel algorithms represent a very useful and increasingly popular preprocessing step for a wide range of computer vision applications, as they offer the potential to boost efficiency and effectiveness. In this regards, this paper presents a highly competitive approach for temporally consistent super pixels for video content. The approach is based on energy-minimizing clustering utilizing a novel hybrid clustering strategy for a multi-dimensional feature space working in a global color subspace and local spatial subspaces. Moreover, a new contour evolution based strategy is introduced to ensure spatial coherency of the generated super pixels. For a thorough evaluation the proposed approach is compared to state of the art super voxel algorithms using established benchmarks and shows a superior performance.
AB - Super pixel algorithms represent a very useful and increasingly popular preprocessing step for a wide range of computer vision applications, as they offer the potential to boost efficiency and effectiveness. In this regards, this paper presents a highly competitive approach for temporally consistent super pixels for video content. The approach is based on energy-minimizing clustering utilizing a novel hybrid clustering strategy for a multi-dimensional feature space working in a global color subspace and local spatial subspaces. Moreover, a new contour evolution based strategy is introduced to ensure spatial coherency of the generated super pixels. For a thorough evaluation the proposed approach is compared to state of the art super voxel algorithms using established benchmarks and shows a superior performance.
KW - over-segmentation
KW - superpixel
KW - supervoxel
KW - tracking
KW - video segmentation
UR - http://www.scopus.com/inward/record.url?scp=84898833837&partnerID=8YFLogxK
U2 - 10.1109/ICCV.2013.55
DO - 10.1109/ICCV.2013.55
M3 - Conference contribution
AN - SCOPUS:84898833837
SN - 9781479928392
T3 - Proceedings of the IEEE International Conference on Computer Vision
SP - 385
EP - 392
BT - Proceedings - 2013 IEEE International Conference on Computer Vision
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2013 14th IEEE International Conference on Computer Vision, ICCV 2013
Y2 - 1 December 2013 through 8 December 2013
ER -