A light-weight real-time ap- plicable hand gesture recognition system for automotive applications
- We present a novel approach for improved hand-gesture recognition by a single time-of-flight(ToF) sensor in an automotive environment. As the sensor's lateral resolution is comparatively low, we employ a learning approach comprising multiple processing steps, including PCA-based cropping, the computation of robust point cloud descriptors and training of a Multilayer perceptron (MLP) on a large database of samples. A sophisticated temporal fusion technique boosts the overall robustness of recognition by taking into account data coming from previous classification steps. Overall results are very satisfactory when evaluated on a large benchmark set of ten different hand poses, especially when it comes to generalization on previously unknown persons.
Author: | Thomas Kopinski, Stéphane Magand, Alexander Gepperth, Uwe Handmann |
---|---|
URL: | https://ieeexplore.ieee.org/document/7225708 |
DOI: | https://doi.org/10.1109/IVS.2015.7225708 |
ISBN: | 978-1-4673-7266-4 |
ISSN: | 1931-0587 |
Parent Title (English): | IEEE Intelligent Vehicles Symposiume (IV 2015) |
Publisher: | IEEE |
Document Type: | Conference Proceeding |
Language: | English |
Year of Completion: | 2015 |
Release Date: | 2019/07/08 |
Volume: | 2015 |
Page Number: | 6 |
First Page: | 336 |
Last Page: | 342 |
Institutes: | Fachbereich 1 - Institut Informatik |
DDC class: | 000 Allgemeines, Informatik, Informationswissenschaft / 004 Informatik |
Licence (German): | ![]() |