Stereo Visual Slam

Stereo Visual SLAM is a visual simultaneous localization and mapping framework that employs stereoscopic camera inputs to jointly estimate the camera trajectory and reconstruct the three-dimensional environment by exploiting parallax for metric depth estimation.

195

Publications

29.4K

Citations

607

Authors

229

Institutions

Publications per year

2017–2026

108

Authors

607

  1. TP
    Taihú Pire

    Centro Internacional Franco-Argentino de Ciencias de la Información y de Sistemas, Argentina

    5 publications · 351 citations

    5

    h-index

  2. GD
    Gamini Dissanayake

    University of Technology Sydney, Australia

    5 publications · 106 citations

    5

    h-index

  3. RG
    Riccardo Giubilato

    University of Padua, Italy

    5 publications · 163 citations

    5

    h-index

  4. SL
    Simon Lacroix

    Laboratoire d'Analyse et d'Architecture des Systèmes, France

    5 publications · 368 citations

    5

    h-index

  5. JC
    Javier Civera

    Universidad de Zaragoza, Spain

    4 publications · 1.2K citations

    4

    h-index

1–5 of 607

Venues

  1. Robotics and Autonomous Systems

    11 publications · 468 citations

    11

    h-index

  2. IEEE Robotics and Automation Letters

    10 publications · 374 citations

    10

    h-index

  3. Journal of Intelligent & Robotic Systems

    8 publications · 199 citations

    8

    h-index

  4. IEEE Access

    5 publications · 157 citations

    5

    h-index

  5. Machine Vision and Applications

    4 publications · 133 citations

    4

    h-index

1–5