TY  - CHAP
U1  - Konferenzveröffentlichung
A1  - Kopinski, Thomas
A1  - Maysiak, Darius
A1  - Gepperth, Alexander
A1  - Handmann, Uwe
T1  - Time-of-flight based multi- sensor fusion strategies for hand gesture recognition
T2  - 15th International Symposium on Computational Intelligence and Informatics (CINTI)
N2  - Building upon prior results, we present an alternative approach to efficiently classifying a complex set of 3D hand poses obtained from modern Time-Of-Flight-Sensors (TOF). We demonstrate it is possible to achieve satisfactory results in spite of low resolution and high noise (inflicted by the sensors) and a demanding outdoor environment. We set up a large database of pointclouds in order to train multilayer perceptrons as well as support vector machines to classify the various hand poses. Our goal is to fuse data from multiple TOF sensors, which observe the poses from multiple angles. The presented contribution illustrates that real-time capability can be maintained with such a setup as the used 3D descriptors, the fusion strategy as well as the online confidence measures are computationally efficient.
Y1  - 2014
UR  - https://ieeexplore.ieee.org/document/7028683
SN  - 978-1-4799-5338-7
SB  - 978-1-4799-5338-7
U6  - https://doi.org/10.1109/CINTI.2014.7028683
DO  - https://doi.org/10.1109/CINTI.2014.7028683
VL  - 2014
IS  - 15
SP  - 243
EP  - 248
S1  - 6
PB  - IEEE
ER  -