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.

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Metadaten
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
Pagenumber:6
First Page:336
Last Page:342
Institutes:Fachbereich 1 - Institut Informatik
DDC class:000 Allgemeines, Informatik, Informationswissenschaft / 004 Informatik
Licence (German):License LogoNo Creative Commons