Reliable frame-to-frame motion estimation for vehicle-mounted surround-view camera systems

Yifu Wang, Kun Huang, Xin Peng, Hongdong Li, Laurent Kneip

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

    7 Citations (Scopus)

    Abstract

    Modern vehicles are often equipped with a surround-view multi-camera system. The current interest in autonomous driving invites the investigation of how to use such systems for a reliable estimation of relative vehicle displacement. Existing camera pose algorithms either work for a single camera, make overly simplified assumptions, are computationally expensive, or simply become degenerate under non-holonomic vehicle motion. In this paper, we introduce a new, reliable solution able to handle all kinds of relative displacements in the plane despite the possibly non-holonomic characteristics. We furthermore introduce a novel two-view optimization scheme which minimizes a geometrically relevant error without relying on 3D point related optimization variables. Our method leads to highly reliable and accurate frame-to-frame visual odometry with a full-size, vehicle-mounted surround-view camera system.

    Original languageEnglish
    Title of host publication2020 IEEE International Conference on Robotics and Automation, ICRA 2020
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages1660-1666
    Number of pages7
    ISBN (Electronic)9781728173955
    DOIs
    Publication statusPublished - May 2020
    Event2020 IEEE International Conference on Robotics and Automation, ICRA 2020 - Paris, France
    Duration: 31 May 202031 Aug 2020

    Publication series

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

    Conference

    Conference2020 IEEE International Conference on Robotics and Automation, ICRA 2020
    Country/TerritoryFrance
    CityParis
    Period31/05/2031/08/20

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