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Classification of laserscanner measurements at intersection scenarios with automatic parameter optimization

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4 Author(s)
Wender, S. ; Dept. of Measure., Control & Microtechnol., Ulm Univ., Germany ; Schoenherr, M. ; Kaempchen, N. ; Dietmayer, K.

Object classification at intersection scenarios is necessary in order to provide a general environment description. Objects are observed using a multilayer laserscanner. Significant features for object classification are identified and their extraction is described. Classification is performed using well-known techniques of statistical learning. Classification results of several neural networks are described and compared with classification performance of support vector machines.

Published in:

Intelligent Vehicles Symposium, 2005. Proceedings. IEEE

Date of Conference:

6-8 June 2005