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Tracking Pedestrians Under Occlusion Using Multiple Cameras

  • Jorge P. Batista
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3212)

Abstract

This paper presents a integrated solution to track multiple non-rigid objects (pedestrians) in a multiple cameras system with ground-plane trajectory prediction and occlusion modelling. The resulting system is able to maintain the tracking of pedestrians before, during and after occlusion. Pedestrians are detected and segmented using a dynamic background model combined with motion detection and brightness and color distortion analysis. Two levels of tracking have been implemented: the image level tracking and the ground-plane level tracking. Several target cues are used to disambiguate between possible candidates of correspondence in the tracking process: spacial and temporal estimation, color and object height. A simple and robust solution for image occlusion monitoring and grouping management is described. Experiments in tracking multiple pedestrians in a dual camera setup with common field of view are presented.

Keywords

Sensor Node Multiple Camera Foreground Pixel Object Descriptor Shadow 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 2004

Authors and Affiliations

  • Jorge P. Batista
    • 1
  1. 1.ISR-Institute of Systems and Robotics, DEEC/FCTUniversity of CoimbraCoimbraPortugal

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