Multi-camera Visual Slam

Multi-Camera Visual SLAM is a visual simultaneous localization and mapping framework that utilizes inputs from multiple cameras with varied configurations to jointly estimate ego-motion and reconstruct the environment, distinguished by its integration of multi-perspective visual data to enhance robustness and coverage compared to single-camera systems.

38

Publications

2K

Citations

140

Authors

53

Institutions

Publications per year

2017–2026

18

Authors

140

  1. SY
    Shaowu Yang

    National University of Defense Technology, China

    4 publications · 130 citations

    4

    h-index

  2. MP
    Marc Pollefeys

    ETH Zurich, Switzerland

    4 publications · 389 citations

    4

    h-index

  3. GH
    Gim Hee Lee

    National University of Singapore, Singapore

    4 publications · 389 citations

    4

    h-index

  4. LH
    Lionel Heng

    ETH Zurich, Switzerland

    4 publications · 389 citations

    4

    h-index

  5. SS
    Sebastian Scherer

    University of Tübingen, Germany

    3 publications · 117 citations

    3

    h-index

1–5 of 140

Venues

  1. Sensors

    2 publications · 23 citations

    2

    h-index

  2. arXiv (Cornell University)

    Repository · 2 publications · 124 citations

    2

    h-index

  3. Computer Vision and Image Understanding

    CVIU · 2 publications · 88 citations

    2

    h-index

  4. Robotics and Autonomous Systems

    2 publications · 138 citations

    2

    h-index

  5. Zurich Open Repository and Archive (University of Zurich)

    Repository · 1 publications · 51 citations

    1

    h-index

1–5