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

Dongbo Min, Jiangbo Lu, Minh N Do

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish (US)
Title of host publication2011 International Conference on Computer Vision, ICCV 2011
Pages1567-1574
Number of pages8
DOIs
StatePublished - Dec 1 2011
Event2011 IEEE International Conference on Computer Vision, ICCV 2011 - Barcelona, Spain
Duration: Nov 6 2011Nov 13 2011

Publication series

NameProceedings of the IEEE International Conference on Computer Vision

Other

Other2011 IEEE International Conference on Computer Vision, ICCV 2011
CountrySpain
CityBarcelona
Period11/6/1111/13/11

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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  • Cite this

    Min, D., Lu, J., & Do, M. N. (2011). A revisit to cost aggregation in stereo matching: How far can we reduce its computational redundancy? In 2011 International Conference on Computer Vision, ICCV 2011 (pp. 1567-1574). [6126416] (Proceedings of the IEEE International Conference on Computer Vision). https://doi.org/10.1109/ICCV.2011.6126416