Multi-View Gesture Recognition in Conflict Situations
Non-verbal cues play a crucial role in social interactions and can influence conflict dynamics. For law enforcement officers, recognizing these cues is essential for effective deescalation, yet traditional training may not fully address their complexity. This paper focuses on body gestures and presents an automated system for recognizing specific body gestures relevant to social conflict situations, aiming to foster awareness for unconsciously performed body gestures and thereby enabling the training of de-escalation strategies.
Authors
- Peter Eisert (ORCID: https://orcid.org/0000-0001-8378-4805)
- Andreas Bock
- Sebastian Bosse (ORCID: https://orcid.org/0000-0002-8104-3904)
- Martin Heinze (ORCID: https://orcid.org/0000-0003-3645-1033)
- Denny Meyer (ORCID: https://orcid.org/0000-0002-9902-0858)
- Anna Hilsmann (ORCID: https://orcid.org/0000-0002-2086-0951)
- Thomas Koch (ORCID: https://orcid.org/0009-0001-0381-0653)
- David J. Martin
- Donald Knuth
- Karam Tomotaki-Dawoud
- Julia Schander
- Birgit Nierula
- Farelle Toumaleu Siewe
Institutions
- Fraunhofer Institute for Telecommunications, Heinrich Hertz Institute (DE)
- IB Hochschule (DE)
Publication Details
- Published
- 2024-12-11
- DOI
- https://doi.org/10.1109/ism63611.2024.00060
- Primary Topic
- Hand Gesture Recognition Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Ministry of Education