Multimodal Gesture Analysis
Multimodal Gesture Analysis is a systematic framework that integrates and analyzes gesture data across multiple communication modalities—such as visual, auditory, and kinesthetic signals—to identify, interpret, and model gestural behavior in relation to speech and contextual cues.
182
Publications
7.2K
Citations
582
Authors
249
Institutions
Publications per year
2017–2026
75
Parents
182
Francis Quek, David McNeill, Robert Bryll et al. · ACM Transactions on Computer-Human Interaction · 2002 · 293 citations
ChaLearn Looking at People RGB-D Isolated and Continuous Datasets for Gesture Recognition
Jun Wan, Stan Z. Li, Yibing Zhao et al. · 2016 · 278 citations
Toward a Minimal Representation of Affective Gestures
Donald Glowinski, Nele Dael, Antonio Camurri et al. · IEEE Transactions on Affective Computing · 2011 · 203 citations · Full text
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Centre National de la Recherche Scientifique
Paris, France
8 h-index
19 publications
613 citations

Institut de Recherche et Coordination Acoustique Musique
Paris, France
5 h-index
10 publications
264 citations
Wright State University
Dayton, United States
5 h-index
16 publications
1.9K citations
University of Chicago
Chicago, United States
5 h-index
12 publications
1.5K citations
Stanford University
Stanford, United States
5 h-index
8 publications
372 citations

University of Hong Kong
Pok Fu Lam, Hong Kong
4 h-index
11 publications
698 citations

Sorbonne Université
Paris, France
4 h-index
8 publications
208 citations
Purdue University West Lafayette
West Lafayette, United States
4 h-index
9 publications
259 citations
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TAC · 4 publications · 309 citations
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3 publications · 59 citations
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BRM · 3 publications · 142 citations
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3 publications · 87 citations
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JASA · 3 publications · 176 citations
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