Media type: E-Book; Thesis Title: Fully bayesian vehicle tracking using extended object models Contributor: Scheel, Alexander [Author] Published: Ulm: Universität Ulm, 2019 Published in: Schriftenreihe des Instituts für Mess-, Regel- und Mikrotechnik ; 30 Extent: Online-Ressource Language: English DOI: 10.18725/OPARU-22843 ISBN: 9783941543454; 9783941543461 Identifier: Keywords: Radar ; Optical radar ; Vehicles ; Multisensor data fusion ; Machine learning ; Objektverfolgung ; Umweltwahrnehmung ; Autonomes Fahrzeug ; Maschinelles Lernen ; Lidar ; Multi-object tracking ; Random finite sets ; Sensor fusion ; Environment perception ; Self-driving car ; Autonomous driving ; Variational Gaussian mixtures ; Extended object tracking ; Vehicle tracking ; Scene labeling ; (LCSH)Multisensor data fusion ; (LCSH)Automated vehicles ; (LCSH)Machine learning ; (LCSH)Radar ; Origination: University thesis: Dissertation, Ulm, Universität Ulm, 2019 Footnote: Access State: Open Access