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A Kalman Filter Based Background Updating Algorithm Robust to Sharp Illumination Changes

  • Stefano Messelodi
  • Carla Maria Modena
  • Nicola Segata
  • Michele Zanin
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3617)

Abstract

A novel algorithm, based on Kalman filtering is presented for updating the background image within video sequences. Unlike existing implementations of the Kalman filter for this task, our algorithm is able to deal with both gradual and sudden global illumination changes. The basic idea is to measure global illumination change and to use it as an external control of the filter. This allows the system to better fit the assumptions about the process to be modeled. Moreover, we propose methods to estimate measurement noise variance and to deal with the problem of saturated pixels, to improve the accuracy and robustness of the algorithm. The algorithm has been successfully tested in a traffic surveillance task by comparing it to a background updating algorithm, based on Kalman filtering, taken from literature.

Keywords

Background Image Illumination Change Foreground Object Foreground Pixel Global Illumination 
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 2005

Authors and Affiliations

  • Stefano Messelodi
    • 2
  • Carla Maria Modena
    • 2
  • Nicola Segata
    • 1
  • Michele Zanin
    • 2
  1. 1.University of TrentoItaly
  2. 2.ITC-irstPovo (Trento)Italy

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