A Visual Blindspot Monitoring System for Safe Lane Changes

  • Jamal Saboune
  • Mehdi Arezoomand
  • Luc Martel
  • Robert Laganiere
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6979)

Abstract

The goal of this work is to propose a solution to improve a driver’s safety while changing lanes on the highway. In fact, if the driver is not aware of the presence of a vehicle in his blindspot a crash can occur. In this article we propose a method to monitor the blindspot zone using video feeds and warn the driver of any dangerous situation. In order to fit in a real time embedded car safety system, we avoid using any complex techniques such as classification and learning. The blindspot monitoring algorithm we expose here is based on a features tracking approach by optical flow calculation. The features to track are chosen essentially given their motion patterns that must match those of a moving vehicle and are filtered in order to overcome the presence of noise. We can then take a decision on a car presence in the blindspot given the tracked features density. To illustrate our approach we present some results using video feeds captured on the highway.

Keywords

Motion Vector Stereo Vision Intelligent Transportation System Vehicle Detection Collision Avoidance System 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Jamal Saboune
    • 1
  • Mehdi Arezoomand
    • 1
  • Luc Martel
    • 2
  • Robert Laganiere
    • 1
  1. 1.VIVA Lab, School of Information Technology and EngineeringUniversity of OttawaOttawaCanada
  2. 2.Cognivue CorporationGatineauCanada

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