DriverMHG: A Multi-Modal Dataset for Dynamic Recognition of Driver Micro Hand Gestures and a Real-Time Recognition Framework

Document type:: Konferenzbeitrag
Author(s):: Köpüklü, O.; Ledwon, T.; Rong, Y.; Köse, N.; Rigoll, G.
Title:: DriverMHG: A Multi-Modal Dataset for Dynamic Recognition of Driver Micro Hand Gestures and a Real-Time Recognition Framework
Pages contribution:: pp. 275-282
Keywords:: hand gesture recognition; dataset for driver gestures; online recognition; 3d cnns
Book / Congress title:: 15th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2020)
Organization:: IEEE
Publisher address:: Los Alamitos, CA, USA
Year:: 2020
Month:: May
WWW:: https://doi.ieeecomputersociety.org/10.1109/FG47880.2020.00041
TUM Institution:: Lehrstuhl für Mensch-Maschine-Kommunikation
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