Depth-based Gesture Recognition
Depth-Based Gesture Recognition is a gesture recognition approach that utilizes depth information from three-dimensional sensor data to identify and interpret human gestures, distinguished from other methods by its reliance on spatial depth cues rather than color or intensity alone.
205
Publications
12.6K
Citations
632
Authors
255
Institutions
Publications per year
2017–2026
66
Parents
205
Hand gesture recognition with 3D convolutional neural networks
Pavlo Molchanov, Shalini Gupta, Kihwan Kim et al. · 2015 · 529 citations
Intel(R) RealSense(TM) Stereoscopic Depth Cameras
Leonid Keselman, J. Woodfill, A. Grunnet-Jepsen et al. · 2017 · 432 citations
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255
University of Portsmouth
Portsmouth, United Kingdom
6 h-index
12 publications
326 citations
Microsoft (United States)
Redmond, United States
5 h-index
8 publications
795 citations

University of Wollongong
Wollongong, Australia
5 h-index
23 publications
1.7K citations
National Taiwan University of Science and Technology
Taipei, Taiwan
4 h-index
10 publications
209 citations

University of Padua
Padua, Italy
4 h-index
14 publications
2.5K citations

Central South University
Changsha, China
4 h-index
6 publications
280 citations
University of Sheffield
Sheffield, United Kingdom
3 h-index
6 publications
949 citations
Wuhan University of Science and Technology
Wuhan, China
3 h-index
13 publications
571 citations
1–8 of 255
8 publications · 308 citations
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8 publications · 359 citations
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3 publications · 195 citations
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3 publications · 80 citations
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Repository · 3 publications · 55 citations
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