Feature Point Tracking

Feature Point Tracking is a computer vision method that identifies and follows distinct, salient locations in an image sequence to estimate motion and reconstruct spatial structure across frames in augmented reality representation.

490

Publications

35K

Citations

1.5K

Authors

532

Institutions

Publications per year

2017–2026

80

Authors

1.5K

  1. TK
    Takeo Kanade

    Carnegie Mellon University, United States

    8 publications · 843 citations

    8

    h-index

  2. JF
    Jeffrey F. Cohn

    University of Pittsburgh, United States

    7 publications · 877 citations

    7

    h-index

  3. GR
    Gerhard Reitmayr

    Graz University of Technology, Austria

    6 publications · 1.2K citations

    6

    h-index

  4. UN
    Ulrich Neumann

    University of Southern California, United States

    5 publications · 336 citations

    5

    h-index

  5. VL
    Vincent Lepetit

    École Polytechnique Fédérale de Lausanne, Switzerland

    5 publications · 375 citations

    5

    h-index

1–5 of 1.5K

Venues

  1. IEEE Transactions on Visualization and Computer Graphics

    TVCG · 7 publications · 791 citations

    7

    h-index

  2. Sensors

    6 publications · 126 citations

    6

    h-index

  3. IEEE Robotics and Automation Letters

    6 publications · 1K citations

    6

    h-index

  4. IEEE Access

    5 publications · 107 citations

    5

    h-index

  5. International Journal of Computer Vision

    4 publications · 330 citations

    4

    h-index

1–5