TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Kopinski, Thomas
A1  - Geisler, Stefan
A1  - Handmann, Uwe
T1  - Gesture-based human-machine interaction for assistance systems
T2  - 2015 IEEE International Conference on Information and Automation
N2  - This contribution demonstrates the efficient embedding of a single depth-camera into the automotive environment making mid-air gesture interaction for mobile applications viable in such a scenario. In this setting a new human-machine interface is implemented to give an idea of future improvements in automation processes in industrial applications. Our system is based on a data-driven approach by learning hand poses as well as gestures from a large database in order to apply them on mobile devices. We register any movement in a nearby driver area and crop data efficiently with the means of PCA transforming it into so-called feature vectors which present the input for our multi-layer perceptrons (MLPs). After MLP classification, the interpretation of user input is sent via WiFi to a tablet PC mounted into the car interior visualizing an infotainment system which the user is able to interact with. We demonstrate that by this setup hand gestures as well as hand poses are easily and efficiently interpretable insofar as that they become an intuitive and supplementary means of interaction for automotive HMI in mobile scenarios realizable in real-time.
Y1  - 2015
UR  - https://ieeexplore.ieee.org/abstract/document/7279341
SN  - 978-1-4673-9104-7
SB  - 978-1-4673-9104-7
U6  - https://doi.org/10.1109/ICInfA.2015.7279341
DO  - https://doi.org/10.1109/ICInfA.2015.7279341
VL  - 2015
IS  - 8-10 Aug
SP  - 510-517
S1  - 510-517
ER  -