Embedded Computer Vision

Part of the series Advances in Pattern Recognition pp 257-279

Challenges of Embedded Computer Vision in Automotive Safety Systems

  • Yan ZhangAffiliated withDelphi Electronics & Safety
  • , Arnab S. DhuaAffiliated withDelphi Electronics & Safety
  • , Stephen J. KiselewichAffiliated withDelphi Electronics & Safety
  • , William A. BausonAffiliated withDelphi Electronics & Safety

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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.