hSGM: hierarchical pyramid based stereo matching algorithm

Authors:
Kwang Hee Won;Soon Ki Jung
Affiliations:
School of Computer Science and Engineering, College of IT Engineering, Kyungpook National University, Buk-gu, Daegu, South Korea;School of Computer Science and Engineering, College of IT Engineering, Kyungpook National University, Buk-gu, Daegu, South Korea
Venue:
ACIVS'11 Proceedings of the 13th international conference on Advanced concepts for intelligent vision systems
Year:
2011

Citing 6
Cited 0

Visual Correspondence Using Energy Minimization and Mutual Information

ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
Symmetric Stereo Matching for Occlusion Handling

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Accurate and Efficient Stereo Processing by Semi-Global Matching and Mutual Information

CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Stereo Vision in Structured Environments by Consistent Semi-Global Matching

CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
Mutual Information Based Semi-Global Stereo Matching on the GPU

ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing
An optimal time---space algorithm for dense stereo matching

Journal of Real-Time Image Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we propose a variant of Semi-Global Matching, hSGM which is a hierarchical pyramid based dense stereo matching algorithm. Our method aggregates the matching costs from the coarse to fine scale in multiple directions to determine the optimal disparity for each pixel. It has several advantages over the original SGM: a low space complexity and efficient implementation on GPU. We show several experimental results to demonstrate our method is efficient and obtains a good quality of disparity maps.