Local Feature Descriptors

Local Feature Descriptors is a computational method in image feature engineering that characterizes the distinctive appearance of localized image regions in a manner invariant to geometric and photometric transformations, thereby enabling reliable matching across different views of a scene.

2.9K

Publications

266.9K

Citations

7.5K

Authors

1.8K

Institutions

Publications per year

2017–2026

963

Authors

7.5K

  1. KM
    Krystian Mikolajczyk

    University of Surrey, United Kingdom

    20 publications · 10.2K citations

    17

    h-index

  2. CS
    Cordelia Schmid

    Institut national de recherche en sciences et technologies du numérique, France

    16 publications · 5.2K citations

    15

    h-index

  3. BF
    Bin Fan

    Chinese Academy of Sciences, China

    15 publications · 1.7K citations

    15

    h-index

  4. MB
    Mohammed Bennamoun

    The University of Western Australia, Australia

    16 publications · 2.5K citations

    14

    h-index

  5. GZ
    Guoying Zhao

    University of Oulu, Finland

    17 publications · 2.7K citations

    14

    h-index

1–5 of 7.5K

Venues

  1. 56

    h-index

  2. IEEE Transactions on Image Processing

    97 publications · 12.9K citations

    52

    h-index

  3. Pattern Recognition

    78 publications · 4.7K citations

    38

    h-index

  4. arXiv (Cornell University)

    Repository · 89 publications · 5.2K citations

    33

    h-index

  5. IEEE Transactions on Multimedia

    39 publications · 2.3K citations

    25

    h-index

1–5