Global-Map-Registered Local Visual Odometry Using On-the-Fly Pose Graph Updates

Masahiro Yamaguchi*, Shohei Mori, Hideo Saito, Shoji Yachida, Takashi Shibata

*Corresponding author for this work

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


Real-time camera pose estimation is one of the indispensable technologies for Augmented Reality (AR). While a large body of work in Visual Odometry (VO) has been proposed for AR, practical challenges such as scale ambiguities and accumulative errors still remain especially when we apply VO to large-scale scenes due to limited hardware and resources. We propose a camera pose registration method, where a local VO is consecutively optimized with respect to a large-scale scene map on the fly. This framework enables the scale estimation between a VO map and a scene map and reduces accumulative errors by finding corresponding locations in the map to the current frame and by on-the-fly pose graph optimization. The results using public datasets demonstrated that our approach reduces the accumulative errors of naïve VO.
Original languageEnglish
Title of host publicationAugmented Reality, Virtual Reality, and Computer Graphics - 7th International Conference, AVR 2020, Proceedings
EditorsLucio Tommaso De Paolis, Patrick Bourdot
PublisherSpringer, Cham
Number of pages13
ISBN (Print)9783030584641
Publication statusPublished - 7 Sept 2020
Event7th International Conference on Augmented Reality, Virtual Reality, and Computer Graphics: AVR 2020 - Virtual, Lecce, Italy
Duration: 7 Sept 202010 Sept 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12242 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference7th International Conference on Augmented Reality, Virtual Reality, and Computer Graphics
CityVirtual, Lecce


  • Graph optimization
  • Location-based AR
  • Structure from motion
  • Visual Odometry

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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