Automatic pedestrian recognition using real-time motion analysis

  • Patrick Vannoorenberghe
  • Cina Motamed
  • Jean-Marc Blosseville
  • Jack-Gérard Postaire
Poster Session D: Biomedical Applications, Detection, Control & Surveillance, Inspection, Optical Character Recognition
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1311)

Abstract

This paper presents a real-time vision system for automatic pedestrian recognition using image sequences analysis. We first introduce a robust motion detector based on a specific background structural model. The motion detection process exploits the structural difference between the model and features extracted from the current scene. The pedestrian recognition process analyses the signal provided by the motion detector in order to separate pedestrians from other moving objects (vehicles, buses, ...). The detection signal processing consists in the extraction of several kinematics and pattern features of each classes of objects. The percentage of good pedestrian discrimination, tested with real traffic image sequences under several illumination conditions, is about 85%.

Keywords

Motion Detection Vehicle Detection Pedestrian Detection Surveillance Area Urban Scene 
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 1997

Authors and Affiliations

  • Patrick Vannoorenberghe
    • 1
  • Cina Motamed
    • 1
  • Jean-Marc Blosseville
    • 2
  • Jack-Gérard Postaire
    • 3
  1. 1.Laboratoire d'Analyse des Systèmes du Littoral 195Rue du Pasteur Martin Luther KingCalais CEDEXFrance
  2. 2.Institut National de Recherche sur les Transports et leur Sécurité 2Arcueil CEDEXFrance
  3. 3.Centre d'Automatique de LilleEquipe Image et Décision Université des Sciences et Technologies de LilleVilleneuve d'Ascq CEDEXFrance

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