Challenges of Embedded Computer Vision in Automotive Safety Systems

  • Yan Zhang
  • Arnab S. Dhua
  • Stephen J. Kiselewich
  • William A. Bauson
Part of the Advances in Pattern Recognition book series (ACVPR)

Abstract

Vision-based automotive safety systems have received considerable attention over the past decade. Such systems have advantages compared to those based on other types of sensors such as radar, because of the availability of lowcost and high-resolution cameras and abundant information contained in video images. However, various technical challenges exist in such systems. One of the most prominent challenges lies in running sophisticated computer vision algorithms on low-cost embedded systems at frame rate. This chapter discusses these challenges through vehicle detection and classification in a collision warning system.

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Copyright information

© Springer-Verlag London Limited 2009

Authors and Affiliations

  • Yan Zhang
    • 1
  • Arnab S. Dhua
    • 1
  • Stephen J. Kiselewich
    • 1
  • William A. Bauson
    • 1
  1. 1.Delphi Electronics & SafetyKokomoUSA

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