NDLI: Improved object classification of laserscanner measurements at intersections using precise high level maps

Content Provider	IEEE Xplore Digital Library
Author	Wender, S. Weiss, T. Dietmayer, K.
Copyright Year	2005
Description	Author affiliation: Dept. of Meas., Control & Microtechnol., Ulm Univ., Germany (Wender, S.; Weiss, T.; Dietmayer, K.)
Abstract	This paper deals with real-time object classification at intersection scenarios. Objects are observed using a multilayer laserscanner. The classification is performed using well-known methods of statistical learning. The statistical classification is corrected by rule based a priori knowledge. Precise high level maps provide the possibility to additionally improve the classification by using infrastructure information and the position of the objects in the scene. Classification results of several neural networks and support vector machines are described. Finally, the improvement by high level maps and the final system performance are presented.
Starting Page	756
Ending Page	761
File Size	995306
Page Count	6
File Format	PDF
ISBN	0780392159
DOI	10.1109/ITSC.2005.1520143
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-09-16
Publisher Place	Austria
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Accidents Laser modes Vehicle safety Optical control Feature extraction Data mining Intelligent sensors Intelligent transportation systems Nonhomogeneous media Statistical learning
Content Type	Text
Resource Type	Article

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Improved object classification of laserscanner measurements at intersections using precise high level maps