Global-map-registered local visual odometry using on-the-fly pose graph updates

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

研究成果: Conference contribution

抄録

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.

本文言語English
ホスト出版物のタイトルAugmented Reality, Virtual Reality, and Computer Graphics - 7th International Conference, AVR 2020, Proceedings
編集者Lucio Tommaso De Paolis, Patrick Bourdot
出版社Springer Science and Business Media Deutschland GmbH
ページ299-311
ページ数13
ISBN(印刷版)9783030584641
DOI
出版ステータスPublished - 2020
イベント7th International Conference on Augmented Reality, Virtual Reality, and Computer Graphics, AVR 2020 - Lecce, Italy
継続期間: 2020 9 72020 9 10

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
12242 LNCS
ISSN(印刷版)0302-9743
ISSN(電子版)1611-3349

Conference

Conference7th International Conference on Augmented Reality, Virtual Reality, and Computer Graphics, AVR 2020
CountryItaly
CityLecce
Period20/9/720/9/10

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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