Fundamental Matrix Estimation

Fundamental Matrix Estimation is a methodological procedure in multi-view geometry that computes the fundamental matrix—a 3×3 rank-2 matrix encoding the epipolar constraint between corresponding points in two uncalibrated images—by estimating the geometric relationship that enables the determination of epipolar lines and correspondences across views.

221

Publications

13.4K

Citations

464

Authors

208

Institutions

Publications per year

2017–2026

28

Authors

464

  1. ZZ
    Zhengyou Zhang

    Microsoft (United States), United States

    6 publications · 407 citations

    6

    h-index

  2. MS
    Mubarak Shah

    University of Central Florida, United States

    6 publications · 302 citations

    6

    h-index

  3. MJ
    Michael J. Brooks

    The University of Adelaide, Australia

    6 publications · 363 citations

    6

    h-index

  4. DG
    D. Gawley

    The University of Adelaide, Australia

    6 publications · 363 citations

    6

    h-index

  5. DB
    Dániel Baráth

    Czech Technical University in Prague, Czechia

    6 publications · 541 citations

    6

    h-index

1–5 of 464

Venues

  1. IEEE Transactions on Pattern Analysis and Machine Intelligence

    TPAMI · 21 publications · 2.8K citations

    19

    h-index

  2. IEEE Access

    5 publications · 102 citations

    5

    h-index

  3. Computer Vision and Image Understanding

    CVIU · 4 publications · 309 citations

    4

    h-index

  4. IET Computer Vision

    3 publications · 39 citations

    3

    h-index

  5. Pattern Recognition Letters

    3 publications · 88 citations

    3

    h-index

1–5