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- Titel:
DriverMHG: A Multi-Modal Dataset for Dynamic Recognition of Driver Micro Hand Gestures and a Real-Time Recognition Framework
- Dokumenttyp:
- Konferenzbeitrag
- Autor(en):
- Köpüklü, Okan; Ledwon, Thomas; Rong, Yao; Köse, Neslihan; Rigoll, Gerhard
- Kongress- / Buchtitel:
- 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020)
- Jahr:
- 2020
- Monat:
- Nov
- Seiten:
- pp--275
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Vorkommen:
- mediaTUM GesamtbestandEinrichtungenSchools TUM School of Computation, Information and TechnologyDepartmentsComputer EngineeringMensch-Maschine-Kommunikation (Prof. Rigoll)AuthorKöse
- mediaTUM GesamtbestandEinrichtungenSchools TUM School of Computation, Information and TechnologyDepartmentsComputer EngineeringMensch-Maschine-Kommunikation (Prof. Rigoll)Publication Year2020
- mediaTUM GesamtbestandEinrichtungenSchools TUM School of Computation, Information and TechnologyDepartmentsComputer EngineeringMensch-Maschine-Kommunikation (Prof. Rigoll)AuthorKöpüklü