Data-driven Motion Capture
Data-Driven Motion Capture is a motion capture methodology that leverages empirical motion data as the primary source for modeling, predicting, or reconstructing human movement, distinguished from model-based or rule-based approaches by its reliance on observed data patterns rather than predefined biomechanical constraints or explicit kinematic rules.
51
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3.8K
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147
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68
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2017–2026
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51
Lucas Kovar, Michael Gleicher, Frédéric Pighin · 2008 · 1.1K citations
Lucas Kovar, Michael Gleicher, Frédéric Pighin · ACM Transactions on Graphics · 2002 · 591 citations
Lucas Kovar, Michael Gleicher, Frédéric Pighin · 2002 · 368 citations
ACM Transactions on Graphics · 2020 · 166 citations · Full text
A data-driven approach to quantifying natural human motion
Liu Ren, Alton Patrick, Alexei A. Efros et al. · ACM Transactions on Graphics · 2005 · 145 citations · Full text
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Georgia Institute of Technology
Atlanta, United States
4 h-index
12 publications
602 citations
Carnegie Mellon University
Pittsburgh, United States
4 h-index
11 publications
624 citations
University of Wisconsin–Madison
Madison, United States
4 h-index
8 publications
4.1K citations
University of Southern California
Los Angeles, United States
4 h-index
6 publications
2.2K citations

Bournemouth University
Poole, United Kingdom
4 h-index
13 publications
318 citations
California Southern University
Chandler, United States
3 h-index
3 publications
2K citations

Zhejiang University
Hangzhou, China
3 h-index
9 publications
391 citations
University of Sheffield
Sheffield, United Kingdom
3 h-index
4 publications
340 citations
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TOG · 4 publications · 932 citations
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2 publications · 42 citations
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TPAMI · 1 publications · 140 citations
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BRM · 1 publications · 15 citations
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1 publications · 11 citations
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