Pedestrian Detection from a Moving Vehicle

  • D. M. Gavrila
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1843)


This paper presents a prototype system for pedestrian detection on-board a moving vehicle. The system uses a generic two-step approach for efficient object detection. In the first step, contour features are used in a hierarchical template matching approach to efficiently “lock” onto candidate solutions. Shape matching is based on Distance Transforms. By capturing the objects shape variability by means of a template hierarchy and using a combined coarse-to-fine approach in shape and parameter space, this method achieves very large speed-ups compared to a brute-force method. We have measured gains of several orders of magnitude. The second step utilizes the richer set of intensity features in a pattern classification approach to verify the candidate solutions (i.e. using Radial Basis Functions). We present experimental results on pedestrian detection off-line and on-board our Urban Traffic Assistant vehicle and discuss the challenges that lie ahead.


Radial Basis Function Candidate Solution Object Detection Leaf Level Pedestrian Detection 
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 2000

Authors and Affiliations

  • D. M. Gavrila
    • 1
  1. 1.Image Understanding SystemsDaimlerChrysler ResearchUlmGermany

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