A Visual Blindspot Monitoring System for Safe Lane Changes View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2011

AUTHORS

Jamal Saboune , Mehdi Arezoomand , Luc Martel , Robert Laganiere

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. More... »

PAGES

1-10

References to SciGraph publications

  • 2005-09. Cooperative Fusion for Multi-Obstacles Detection With Use of Stereovision and Laser Scanner in AUTONOMOUS ROBOTS
  • 2000-08. Real-time multiple vehicle detection and tracking from a moving vehicle in MACHINE VISION AND APPLICATIONS
  • 2010. An Embedded All-Time Blind Spot Warning System in ADVANCES IN NEURAL NETWORK RESEARCH AND APPLICATIONS
  • 2009. Real-Time Vision-Based Vehicle Detection for Rear-End Collision Mitigation Systems in COMPUTER AIDED SYSTEMS THEORY - EUROCAST 2009
  • Book

    TITLE

    Image Analysis and Processing – ICIAP 2011

    ISBN

    978-3-642-24087-4
    978-3-642-24088-1

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-642-24088-1_1

    DOI

    http://dx.doi.org/10.1007/978-3-642-24088-1_1

    DIMENSIONS

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