Online Action Recognition

Online Action Recognition is a genre of action recognition methodology that enables real-time identification of human actions in video streams by processing frames sequentially as they become available, without access to future frames.

290

Publications

14.3K

Citations

929

Authors

367

Institutions

Publications per year

2017–2026

178

Variants

Real-time Action Recognition

Authors

929

  1. MX
    Mingze Xu

    South China Normal University, China

    5 publications · 278 citations

    5

    h-index

  2. FC
    Fabio Cuzzolin

    Oxford Brookes University, United Kingdom

    5 publications · 86 citations

    5

    h-index

  3. MG
    Mingfei Gao

    University of Maryland, College Park, United States

    5 publications · 320 citations

    5

    h-index

  4. LW
    Limin Wang

    Nanjing University, China

    4 publications · 702 citations

    4

    h-index

  5. LS
    Larry S. Davis

    University of Maryland, College Park, United States

    4 publications · 267 citations

    4

    h-index

1–5 of 929

Venues

  1. Pattern Recognition

    12 publications · 409 citations

    11

    h-index

  2. arXiv (Cornell University)

    Repository · 13 publications · 238 citations

    11

    h-index

  3. Sensors

    7 publications · 304 citations

    8

    h-index

  4. Multimedia Tools and Applications

    7 publications · 261 citations

    8

    h-index

  5. Neurocomputing

    6 publications · 400 citations

    6

    h-index

1–5