Video-based Fall Detection
Video-Based Fall Detection is a methodological framework within the domain of activity recognition that uses visual data from video sequences to automatically identify human falls by analyzing spatiotemporal motion patterns, body posture, and contextual scene information.
204
Publications
11.7K
Citations
627
Authors
258
Institutions
Publications per year
2017–2026
92
Parents
204
Fall Detection from Human Shape and Motion History Using Video Surveillance
Caroline Rougier, Jean Meunier, Alain St-Arnaud et al. · 2007 · 320 citations
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258
Université de Montréal
Montreal, Canada
7 h-index
20 publications
3.9K citations
Chalmers University of Technology
Gothenburg, Sweden
6 h-index
13 publications
288 citations
KU Leuven
Leuven, Belgium
6 h-index
33 publications
1.2K citations

University of British Columbia
Vancouver, Canada
6 h-index
17 publications
508 citations
Institut Universitaire de Gériatrie de Montréal
Montreal, Canada
6 h-index
12 publications
1.9K citations
Loughborough University
Loughborough, United Kingdom
5 h-index
19 publications
927 citations
Thomas More Kempen
Geel, Belgium
5 h-index
7 publications
252 citations
University of Missouri
Columbia, United States
5 h-index
22 publications
2.5K citations
1–8 of 258
6 publications · 402 citations
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4 publications · 236 citations
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4 publications · 259 citations
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4 publications · 819 citations
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3 publications · 120 citations
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