Comparison of Three Approaches for Scenario Classification for the Automotive Field

  • Nicola Bernini
  • Massimo Bertozzi
  • Luca Devincenzi
  • Luca Mazzei
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8156)

Abstract

To extend the functionalities of Advanced Driver Assistance Systems (ADAS) and have a more accurate control on the parameters of sensors mounted on an intelligent vehicle, a tool that can classify the scenarios which the vehicle moves in, is needed.

This article presents a comparison of three classification techniques (PCA, ANN and SVM) to obtain a fast and robust scene classifier based only on images. The systems presented in this paper have been trained on three different categories of traffic scenarios: urban, highway, and rural, on a total of more than 23 hours of driving in different countries.

Keywords

scenario classification intelligent vehicles automotive 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Nicola Bernini
    • 1
  • Massimo Bertozzi
    • 1
  • Luca Devincenzi
    • 1
  • Luca Mazzei
    • 1
  1. 1.Dip. Ing InformazioneParmaItaly

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