Vision-based Gesture Recognition
Vision-Based Gesture Recognition is a method within the field of human-computer interaction that uses visual input from cameras and computer vision algorithms to detect, track, and interpret human gestures as meaningful commands or inputs, distinguishing itself from other gesture recognition approaches by relying exclusively on optical sensing modalities rather than wearable sensors or touch-based devices.
683
Publications
33.1K
Citations
2K
Authors
635
Institutions
Publications per year
2017–2026
219
683
Vision-based hand-gesture applications
Juan Wachs, Mathias Kölsch, Helman I. Stern et al. · Communications of the ACM · 2011 · 642 citations
Hand gesture recognition with 3D convolutional neural networks
Pavlo Molchanov, Shalini Gupta, Kihwan Kim et al. · 2015 · 529 citations
1–5 of 683
2K
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Central Electronics Engineering Research Institute, India
6 publications · 216 citations
6
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635
Indian Institute of Technology Guwahati
Guwahati, India
9 h-index
22 publications
1.2K citations
Microsoft (United States)
Redmond, United States
8 h-index
19 publications
1K citations
National Institute of Technology Rourkela
Rourkela, India
8 h-index
17 publications
587 citations
University of California San Diego
San Diego, United States
8 h-index
21 publications
1.9K citations

Savitribai Phule Pune University
Pune, India
8 h-index
15 publications
396 citations

University of Ottawa
Ottawa, Canada
8 h-index
26 publications
1.9K citations

Chinese Academy of Sciences
Beijing, China
7 h-index
24 publications
841 citations
Massachusetts Institute of Technology
Cambridge, United States
7 h-index
16 publications
2.2K citations
1–8 of 635
9 publications · 536 citations
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8 publications · 300 citations
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8 publications · 160 citations
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8 publications · 457 citations
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8 publications · 239 citations
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