Feature-based Visual Odometry

Feature-Based Visual Odometry is a method within visual odometry that estimates camera motion by tracking and matching distinctive image features across consecutive frames, differing from direct methods through its reliance on sparse, explicitly detected feature points rather than dense pixel intensities.

137

Publications

21.7K

Citations

389

Authors

149

Institutions

Publications per year

2017–2026

90

Authors

389

  1. DC
    Daniel Cremers

    Technical University of Munich, Germany

    5 publications · 872 citations

    5

    h-index

  2. DS
    Davide Scaramuzza

    University of Zurich, Switzerland

    5 publications · 1.4K citations

    5

    h-index

  3. PJ
    Patric Jensfelt

    KTH Royal Institute of Technology, Sweden

    3 publications · 298 citations

    3

    h-index

  4. JF
    John Folkesson

    KTH Royal Institute of Technology, Sweden

    3 publications · 298 citations

    3

    h-index

  5. TK
    Takeo Kanade

    Carnegie Mellon University, United States

    3 publications · 282 citations

    3

    h-index

1–5 of 389

Venues

  1. arXiv (Cornell University)

    Repository · 8 publications · 252 citations

    8

    h-index

  2. IEEE Robotics and Automation Letters

    7 publications · 522 citations

    7

    h-index

  3. 5

    h-index

  4. Sensors

    5 publications · 412 citations

    5

    h-index

  5. IEEE Access

    4 publications · 123 citations

    5

    h-index

1–5