A revisit to cost aggregation in stereo matching: How far can we reduce its computational redundancy?

Authors:
Dongbo Min;Jiangbo Lu;Minh N. Do
Affiliations:
Advanced Digital Sciences Center (ADSC), Singapore;Advanced Digital Sciences Center (ADSC), Singapore;University of Illinois at Urbana-Champaign, USA
Venue:
ICCV '11 Proceedings of the 2011 International Conference on Computer Vision
Year:
2011

Citing 0
Cited 4

Secrets of adaptive support weight techniques for local stereo matching

Computer Vision and Image Understanding
Information permeability for stereo matching

Image Communication
A Parallel Proximal Splitting Method for Disparity Estimation from Multicomponent Images Under Illumination Variation

Journal of Mathematical Imaging and Vision
Fast stereo matching using adaptive guided filtering

Image and Vision Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a novel method for performing an efficient cost aggregation in stereo matching. The cost aggregation problem is re-formulated with a perspective of a histogram, and it gives us a potential to reduce the complexity of the cost aggregation significantly. Different from the previous methods which have tried to reduce the complexity in terms of the size of an image and a matching window, our approach focuses on reducing the computational redundancy which exists among the search range, caused by a repeated filtering for all disparity hypotheses. Moreover, we also reduce the complexity of the window-based filtering through an efficient sampling scheme inside the matching window. The trade-off between accuracy and complexity is extensively investigated into parameters used in the proposed method. Experimental results show that the proposed method provides high-quality disparity maps with low complexity. This work provides new insights into complexity-constrained stereo matching algorithm design.