• DocumentCode
    1135738
  • Title

    Using Image-Based Metrics to Model Pedestrian Detection Performance With Night-Vision Systems

  • Author

    Bi, Luzheng ; Tsimhoni, Omer ; Liu, Yili

  • Author_Institution
    Sch. of Mech. & Vehicular Eng., Beijing Inst. of Technol., Beijing
  • Volume
    10
  • Issue
    1
  • fYear
    2009
  • fDate
    3/1/2009 12:00:00 AM
  • Firstpage
    155
  • Lastpage
    164
  • Abstract
    The primary purpose of night-vision systems in civilian vehicles is to help drivers detect pedestrians. Pedestrian detection distance with night-vision systems has been modeled based on image metrics. However, the probability of pedestrian detection, in particular considering the factor of distance, has not been modeled based on image metrics. In this paper, we first describe a model of the probability of pedestrian detection, which compares several combinations of image-based clutter, contrast, and pedestrian size metrics using a simple mathematical equation. Next, we describe a model of the probability of pedestrian detection as a function of distance and image-based metrics by combining the model of pedestrian-detection probability and a model that represents the relationship between the distance to a pedestrian and an image-based pedestrian size metric. In the final model, image-based metrics are used to predict pedestrian-detection performance and can also be used to evaluate and support the development of night-vision systems in vehicles.
  • Keywords
    night vision; object detection; probability; traffic engineering computing; civilian vehicle; image-based clutter; image-based contrast; image-based pedestrian size metric; mathematical equation; night-vision system; pedestrian detection probability model; Human-performance model; image-based metrics; night-vision systems; pedestrian detection;
  • fLanguage
    English
  • Journal_Title
    Intelligent Transportation Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1524-9050
  • Type

    jour

  • DOI
    10.1109/TITS.2008.2011719
  • Filename
    4770185