Video Sequences Association for People Re-identification across Multiple Non-overlapping Cameras

  • Dung Nghi Truong Cong
  • Catherine Achard
  • Louahdi Khoudour
  • Lounis Douadi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5716)


This paper presents a solution of the appearance-based people re-identification problem in a surveillance system including multiple cameras with different fields of vision. We first utilize different color-based features, combined with several illuminant invariant normalizations in order to characterize the silhouettes in static frames. A graph-based approach which is capable of learning the global structure of the manifold and preserving the properties of the original data in a lower dimensional representation is then introduced to reduce the effective working space and to realize the comparison of the video sequences. The global system was tested on a real data set collected by two cameras installed on board a train. The experimental results show that the combination of color-based features, invariant normalization procedures and the graph-based approach leads to very satisfactory results.


Dimensionality Reduction Video Sequence Multiple Camera Invariant Normalization Nonlinear Dimensionality Reduction 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Dung Nghi Truong Cong
    • 1
  • Catherine Achard
    • 2
  • Louahdi Khoudour
    • 1
  • Lounis Douadi
    • 1
  1. 1.French National Institute for Transport and Safety Research (INRETS)Villeneuve d’AscqFrance
  2. 2.Institute of Intelligent Systems and Robotics (ISIR)UPMC Univ Paris 06IVRY SUR SEINEFrance

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