Optical Camera Based Pedestrian Detection in Rainy Or Snowy Weather

  • Y. W. Xu
  • X. B. Cao
  • H. Qiao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4223)


Optical camera based detection method is a popular system to fulfill pedestrian detection; however, it is difficult to be used to detect pedestrians in complicated environment (e.g. rainy or snowy weather conditions). The difficulties mainly include: (1) The light is much weaker than in sunny days, therefore it is more difficult to design an efficient classification mechanism; (2) Since a pedestrian always be partly covered, only using its global features (e.g. appearance or motion) may be mis-detected; (3) The mirror images on wet road will cause a lot of false alarms. In this paper, based on our pervious work, we introduce a new system for pedestrian detection in rainy or snowy weather. Firstly, we propose a cascaded classification mechanism; and then, in order to improve detection rate, we adopt local appearance features of head, body and leg as well as global features. Besides that, a specific classifier is designed to detect mirror images in order to reduce false positive rate. The experiments in a single optical camera based pedestrian detection system show the effeteness of the proposed system.


False Alarm Candidate Selection Pedestrian Detection AdaBoost Algorithm Detection Speed 
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 2006

Authors and Affiliations

  • Y. W. Xu
    • 1
    • 2
  • X. B. Cao
    • 1
    • 2
  • H. Qiao
    • 3
  1. 1.Department of Computer Science and TechnologyUniversity of Science and Technology of ChinaHefeiP.R. China
  2. 2.Anhui Province Key Laboratory of Software in Computing and CommunicationHefeiP.R. China
  3. 3.Institute of AutomationChinese Academy of SciencesBeijingP.R. China

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