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EDPLVO: Efficient Direct Point-Line Visual Odometry

  • Lipu Zhou
  • , Guoquan Huang
  • , Yinian Mao
  • , Shengze Wang
  • , Michael Kaess
  • Meituan
  • University of North Carolina at Chapel Hill
  • Carnegie Mellon University

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

Abstract

This paper introduces an efficient direct visual odometry (VO) algorithm using points and lines. Pixels on lines are generally adopted in direct methods. However, the original photometric error is only defined for points. It seems difficult to extend it to lines. In previous works, the collinear constraints for points on lines are either ignored [1] or introduce heavy computational load into the resulting optimization system [2]. This paper extends the photometric error for lines. We prove that the 3D points of the points on a 2D line are determined by the inverse depths of the endpoints of the 2D line, and derive a closed-form solution for this problem. This property can significantly reduce the number of variables to speed up the optimization, and can make the collinear constraint exactly satisfied. Furthermore, we introduce a two-step method to further accelerate the optimization, and prove the convergence of this method. The experimental results show that our algorithm outperforms the state-of-the-art direct VO algorithms.

Original languageEnglish
Title of host publication2022 IEEE International Conference on Robotics and Automation, ICRA 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages7559-7565
Number of pages7
ISBN (Electronic)9781728196817
DOIs
StatePublished - 2022
Externally publishedYes
Event39th IEEE International Conference on Robotics and Automation, ICRA 2022 - Philadelphia, United States
Duration: 23 May 202227 May 2022

Publication series

NameProceedings - IEEE International Conference on Robotics and Automation
Volume2022-January
ISSN (Print)1050-4729

Conference

Conference39th IEEE International Conference on Robotics and Automation, ICRA 2022
Country/TerritoryUnited States
CityPhiladelphia
Period23/05/2227/05/22

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