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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.
Intelligent Vehicles Symposium, 2005. Proceedings. IEEE
Date of Conference: 6-8 June 2005