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      Detection of sudden pedestrian crossings for driving assistance systems

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      Author
      Xu, Yanwu
      Xu, Dong
      Lin, Stephen
      Han, Tony X.
      Cao, Xianbin
      Li, Xuelong
      Date of Issue
      2011
      School
      School of Computer Engineering
      Abstract
      In this paper, we study the problem of detecting sudden pedestrian crossings to assist drivers in avoiding accidents. This application has two major requirements: to detect crossing pedestrians as early as possible just as they enter the view of the car-mounted camera and to maintain a false alarm rate as low as possible for practical purposes. Although many current sliding-window-based approaches using various features and classification algorithms have been proposed for image-/video-based pedestrian detection, their performance in terms of accuracy and processing speed falls far short of practical application requirements. To address this problem, we propose a three-level coarse-to-fine video-based framework that detects partially visible pedestrians just as they enter the camera view, with low false alarm rate and high speed. The framework is tested on a new collection of high-resolution videos captured from a moving vehicle and yields a performance better than that of state-of-the-art pedestrian detection while running at a frame rate of 55 fps.
      Subject
      DRNTU::Engineering::Electrical and electronic engineering
      Type
      Journal Article
      Series/Journal Title
      IEEE transactions on systems, man, and cybernetics, part b (cybernetics)
      Rights
      © 2011 IEEE.
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      • SCSE Journal Articles
      http://dx.doi.org/10.1109/TSMCB.2011.2175726
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