Multimodal Gesture Recognition

Multimodal Gesture Recognition is a gesture recognition paradigm that integrates multiple sensory inputs or data modalities—such as visual, depth, inertial, and audio signals—to improve the accuracy, robustness, and contextual understanding of gesture interpretation beyond what unimodal approaches can achieve.

525

Publications

27.2K

Citations

1.8K

Authors

547

Institutions

Publications per year

2017–2026

273

Authors

1.8K

  1. SE
    Sérgio Escalera

    Universitat de Barcelona, Spain

    9 publications · 879 citations

    9

    h-index

  2. DJ
    Du Jiang

    Wuhan University of Science and Technology, China

    7 publications · 547 citations

    7

    h-index

  3. IG
    Isabelle Guyon

    Gleason (United States), United States

    7 publications · 745 citations

    7

    h-index

  4. JW
    Jun Wan

    Chinese Academy of Sciences, China

    6 publications · 611 citations

    6

    h-index

  5. VA
    Vassilis Athitsos

    The University of Texas at Arlington, United States

    6 publications · 751 citations

    6

    h-index

1–5 of 1.8K

Venues

  1. Sensors

    19 publications · 683 citations

    15

    h-index

  2. IEEE Access

    16 publications · 889 citations

    14

    h-index

  3. IEEE Sensors Journal

    13 publications · 512 citations

    13

    h-index

  4. 9

    h-index

  5. arXiv (Cornell University)

    Repository · 7 publications · 148 citations

    7

    h-index

1–5