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.…
| Dokumentart: | Konferenzveröffentlichung |
|---|---|
| Art der Konferenzveröffentlichung: | Konferenzartikel |
| Zitierlink: | https://opus.hs-offenburg.de/4369 | Bibliografische Angaben |
| Titel (Englisch): | Optical 3D Object Recognition for Automated Driving |
| Konferenzangaben: | The Upper-Rhine Artificial Intelligence Symposium (UR-AI 2020), Karlsruhe, 13th May 2020 |
| Verfasserangaben: | Raphael Schwarz, Marin B. MarinovORCiD, Stefan HenselStaff MemberORCiDGND |
| Erscheinungsjahr: | 2020 |
| Urhebende Körperschaft: | Hochschule Offenburg |
| Seitenanzahl: | 9 |
| Erste Seite: | 127 |
| Letzte Seite: | 135 |
| Titel des übergeordneten Werkes (Englisch): | Artificial Intelligence : Research Impact on Key Industries. Proceedings of the Upper-Rhine Artificial Intelligence Symposium |
| Herausgeber*in: | Andreas Christ ORCiDGND, Franz Quint |
| ISBN: | 978-3-943301-29-8 (eBook) |
| ISBN: | 978-3-943301-28-1 (Print) |
| Sprache: | Englisch | Inhaltliche Informationen |
| Fakultäten / Einrichtungen: | Fakultät Elektrotechnik, Medizintechnik und Informatik (EMI) (ab 04/2019) |
| Sammlungen der Hochschule Offenburg: | Bibliografie |
| Projekte / Schluckspecht | Formale Angaben |
| Open-Access-Status: | Open Access |
| Lizenz (Deutsch): |  Creative Commons - CC BY - Namensnennung 4.0 International |
| ArXiv-Id: | http://arxiv.org/abs/2010.16241 |