Optical Flow Features

Optical Flow Features is a type of motion representation in computer vision that characterizes the apparent motion of pixels between consecutive image frames by encoding the direction and magnitude of displacement vectors derived from temporal intensity changes.

634

Publications

40K

Citations

1.9K

Authors

660

Institutions

Publications per year

2017–2026

346

Authors

1.9K

  1. HS
    Hichem Snoussi

    Université de Technologie de Troyes, France

    7 publications · 418 citations

    7

    h-index

  2. TW
    Tian Wang

    Beihang University, China

    6 publications · 356 citations

    6

    h-index

  3. BS
    Bernt Schiele

    Max Planck Institute for Informatics, Germany

    5 publications · 1.2K citations

    5

    h-index

  4. MJ
    Manuel J. Marín‐Jiménez

    University of Córdoba, Spain

    3 publications · 151 citations

    4

    h-index

  5. TY
    Toshihiko Yamasaki

    The University of Tokyo, Japan

    4 publications · 77 citations

    4

    h-index

1–5 of 1.9K

Venues

  1. arXiv (Cornell University)

    Repository · 23 publications · 1.2K citations

    16

    h-index

  2. IEEE Transactions on Image Processing

    13 publications · 977 citations

    13

    h-index

  3. IEEE Transactions on Multimedia

    12 publications · 787 citations

    12

    h-index

  4. Sensors

    10 publications · 303 citations

    11

    h-index

  5. Pattern Recognition Letters

    9 publications · 363 citations

    10

    h-index

1–5