• DocumentCode
    970977
  • Title

    Survey of Pedestrian Detection for Advanced Driver Assistance Systems

  • Author

    Gerónimo, David ; López, Antonio M. ; Sappa, Angel D. ; Graf, Thorsten

  • Author_Institution
    Comput. Sci. Dept., Univ. Autonoma de Barcelona, Barcelona, Spain
  • Volume
    32
  • Issue
    7
  • fYear
    2010
  • fDate
    7/1/2010 12:00:00 AM
  • Firstpage
    1239
  • Lastpage
    1258
  • Abstract
    Advanced driver assistance systems (ADASs), and particularly pedestrian protection systems (PPSs), have become an active research area aimed at improving traffic safety. The major challenge of PPSs is the development of reliable on-board pedestrian detection systems. Due to the varying appearance of pedestrians (e.g., different clothes, changing size, aspect ratio, and dynamic shape) and the unstructured environment, it is very difficult to cope with the demanded robustness of this kind of system. Two problems arising in this research area are the lack of public benchmarks and the difficulty in reproducing many of the proposed methods, which makes it difficult to compare the approaches. As a result, surveying the literature by enumerating the proposals one--after-another is not the most useful way to provide a comparative point of view. Accordingly, we present a more convenient strategy to survey the different approaches. We divide the problem of detecting pedestrians from images into different processing steps, each with attached responsibilities. Then, the different proposed methods are analyzed and classified with respect to each processing stage, favoring a comparative viewpoint. Finally, discussion of the important topics is presented, putting special emphasis on the future needs and challenges.
  • Keywords
    driver information systems; advanced driver assistance systems; pedestrian detection; pedestrian protection systems; traffic safety; ADAS; on-board vision; pedestrian detection; survey.; Accident Prevention; Accidents, Traffic; Automobile Driving; Humans; Image Processing, Computer-Assisted; Pattern Recognition, Automated; Walking;
  • fLanguage
    English
  • Journal_Title
    Pattern Analysis and Machine Intelligence, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0162-8828
  • Type

    jour

  • DOI
    10.1109/TPAMI.2009.122
  • Filename
    5010438