An efficient local method for stereo matching using daisy features

Xiaoming Peng, Abdesselam Bouzerdoum, Son Lam Phung

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, a local method is proposed to estimate the visibility and disparity of pixels from a stereo pair using the DAISY feature. The problem is formulated as a joint optimization over disparity and visibility of individual pixels. The constraints on the range of disparities and the binary visibility variables are enforced by incorporating penalty terms into the cost function. Finally, the unconstrained optimization problem is solved using a Newton scheme with appropriate approximations to the Hessian matrices and gradients. The computation time of the proposed optimization method is around one minute to run for 768 × 512 stereo pairs using the DAISY feature descriptor in a C++ implementation.

Original languageEnglish
Title of host publication2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings
PublisherIEEE Computer Society
Pages2503-2507
Number of pages5
ISBN (Electronic)9781509021758
DOIs
Publication statusPublished - 2 Jul 2017
Event24th IEEE International Conference on Image Processing, ICIP 2017 - Beijing, China
Duration: 17 Sept 201720 Sept 2017

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2017-September
ISSN (Print)1522-4880

Conference

Conference24th IEEE International Conference on Image Processing, ICIP 2017
Country/TerritoryChina
CityBeijing
Period17/09/1720/09/17

Keywords

  • Local optimization
  • Stereo matching
  • The DAISY feature vector

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