Learning the Scene Illumination for Color-Based People Tracking in Dynamic Environment

  • Sinan Mutlu
  • Tao Hu
  • Oswald Lanz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8157)


People tracking under non-uniform illumination is challenging, as observed appearance may change as they move around in the environment. Appearance model adaptation is inconvenient over the long run as it is subject to drift, while filtering illumination information in the data through built-in invariance is sub-optimal in terms of discriminative capability. In this work, we are interested in modeling the spatial and temporal dimensions of appearance variation induced by non-uniform illumination, and to learn and adapt related parameters over time by using walking people as illumination probes. We propose a hybrid graphical model and a new message passing scheme that sequentially updates parameters of the model, so that scene illumination can be learnt online and used for robust tracking in dynamic environment.


tracking online learning belief propagation message passing particle filter illumination 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Sinan Mutlu
    • 1
    • 2
  • Tao Hu
    • 1
    • 2
  • Oswald Lanz
    • 1
  1. 1.FBK Fondazione Bruno KesslerPovoItaly
  2. 2.ICT Doctoral SchoolUniversity of TrentoPovoItaly

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