Abstract
An object classification system is introduced. The system observes the vehicle’s environment with a laser scanner. Preprocessing and object tracking algorithms are applied. The object classification combines a pattern classifier with rule based a priori knowledge and high level map information. The pattern classifier uses significant features to calculate membership values for each class. These membership values are verified and corrected by a priori knowledge. Furthermore, a precise position of the test vehicle is estimated. The positions of observed objects in the high level map can be determined exploiting this information. As the object position is restricted for some object classes, this knowledge can be used in the classification, which significantly improves its performance. Finally, the system is evaluated with labeled test data of several sequences at different intersections.
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References
K. Ch. Fuerstenberg, U. Lages, “New European Approach for Intersection Safety — The EC-Project INTERSAFE”, Proceedings of 2005 IEEE Intelligent Vehicles Symposium, Las Vegas, 2005
Homepage of the IBEO Automobile Sensor GmbH, http://www.ibeo-as.de, January 2006
K. Ch. Fuerstenberg, K. Dietmayer, “Fahrzeugumfelderfassung mit mehrzeiligen Laserscannern”, Journal Technisches Messen 71 (2004) 3, Oldenbourg Verlag, Munich, 2004
N. Kaempchen, M. Buehler, K. Dietmayer, “Feature-Level Fusion for Free-Form Object Tracking using Laserscanner and Video”, Proceedings of 2005 IEEE Intelligent Vehicles Symposium, Las Vegas, 2005
S. Wender, M. Schoenherr, N. Kaempchen, K. Dietmayer, “Classification of Laserscanner Measurements at Intersection Scenarios with Automatic Parameter Optimization”, Proceedings of 2005 IEEE Intelligent Vehicles Symposium, Las Vegas, 2005
S. Wender, K. C. J. Dietmayer, “Statistical Approaches for Vehicle Environment Classification at Intersections with a Laserscanner”, Proceedings of ITS 2005, 12th World Congress on Intelligent Transportation Systems, San Francisco, 2005
Fuerstenberg, K.; Weiss, T. “Feature-Level Map Building and Object Recognition for Intersection Safety Applications” Proceedings of IEEE Intelligent Vehicles Symposium 2005, Las Vegas, USA, June 2005
Thorsten Weiss, Nico Kaempchen, Klaus Dietmayer, “Precise Ego-Localization in Urban Areas Using Laserscanner and High Accuracy Feature Maps”, Proceedings of IEEE Intelligent Vehicles Symposium 2005, Las Vegas, USA, June 2005
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© 2006 Springer-Verlag Berlin Heidelberg
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Wender, S., Weiss, T., Dietmayer, K.C.J., Fürstenberg, K. (2006). Object Classification exploiting High Level Maps of Intersections. In: Valldorf, J., Gessner, W. (eds) Advanced Microsystems for Automotive Applications 2006. VDI-Buch. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-33410-6_15
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DOI: https://doi.org/10.1007/3-540-33410-6_15
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33409-5
Online ISBN: 978-3-540-33410-1
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