Ransac

Ransac is an iterative model estimation method that distinguishes itself by robustly fitting a mathematical model to observed data containing outliers through random sampling of minimal subsets and consensus evaluation.

470

Publications

54.4K

Citations

1.3K

Authors

471

Institutions

Publications per year

2017–2026

170

Variants

Random Sample Consensus

Authors

1.3K

  1. MP
    Marc Pollefeys

    ETH Zurich, Switzerland

    9 publications · 1.1K citations

    9

    h-index

  2. OC
    Ondřej Chum

    Czech Technical University in Prague, Czechia

    8 publications · 3K citations

    8

    h-index

  3. JM
    Jiřı́ Matas

    Czech Technical University in Prague, Czechia

    7 publications · 2.2K citations

    7

    h-index

  4. KÅ
    Kalle Åström

    Lund University, Sweden

    6 publications · 159 citations

    6

    h-index

  5. DB
    Dániel Baráth

    Czech Technical University in Prague, Czechia

    5 publications · 506 citations

    5

    h-index

1–5 of 1.3K