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Optical 3D Object Recognition for Automated Driving

  • In this contribution, we propose an system setup for the detection andclassification of objects in autonomous driving applications. The recognition algo-rithm is based upon deep neural networks, operating in the 2D image domain. Theresults are combined with data of a stereo camera system to finally incorporatethe 3D object information into our mapping framework. The detection systemisIn this contribution, we propose an system setup for the detection andclassification of objects in autonomous driving applications. The recognition algo-rithm is based upon deep neural networks, operating in the 2D image domain. Theresults are combined with data of a stereo camera system to finally incorporatethe 3D object information into our mapping framework. The detection systemis locally running upon the onboard CPU of the vehicle. Several network archi-tectures are implemented and evaluated with respect to accuracy and run-timedemands for the given camera and hardware setup.show moreshow less

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Metadaten
Author:Raphael Schwarz, Marin B. Marinov, Stefan HenselGND
Editor:Andreas Christ, Franz Quint
Creating Corporation:Hochschule Offenburg
Year of Publication:2020
Page Number:9
ISBN:978-3-943301-29-8 (eBook)
ISBN:978-3-943301-28-1 (Print)
Language:English
Parent Title (English):Artificial Intelligence : Research Impact on Key Industries. Proceedings of the Upper-Rhine Artificial Intelligence Symposium
First Page:127
Last Page:135
Document Type:Conference Proceeding
Open Access:Frei zugänglich
Institutes:Bibliografie
Release Date:2020/12/17
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International
Note:
Konferenz: The Upper-Rhine Artificial Intelligence Symposium (UR-AI 2020). Collection of accepted papers of the canceled symposium  Karlsruhe, 13th May 2020
ArXiv Id:http://arxiv.org/abs/2010.16241