Vehicle Detection and Tracking for Visual understanding of Road Environments Articles uri icon

publication date

  • October 2010

start page

  • 847

end page

  • 860

volume

  • 28

international standard serial number (ISSN)

  • 0263-5747

electronic international standard serial number (EISSN)

  • 1469-8668

abstract

  • Many of the advanced driver assistance systems have the goal of perceiving the surroundings of a vehicle. One of them, adaptive cruise control, takes charge of searching for other vehicles in order to detect
    and track them with the aim of maintaining a safe distance and to avoid
    dangerous maneuvers. In the research described in this article, this
    task is accomplished using an on board camera. Depending on when the
    vehicles are detected the system analyzes movement or uses a vehicle
    geometrical model to perceive them. After, the detected vehicle is
    tracked and its behavior established. Optical flow is used for movement
    while the geometric model is associated with a likelihood function that
    includes information of the shape and symmetry of the vehicle and the
    shadow it casts. A genetic algorithm finds the optimum parameter values
    of this function for every image. As the algorithm receives information
    from a road detection module some geometric restrictions are applied.
    Additionally, a multiresolution approach is used to speed up the
    algorithm. Examples of real image sequences under different weather
    conditions are shown to validate the algorithm.