Person Re-identification Using Robust Brightness Transfer Functions Based on Multiple Detections

  • Amran BhuiyanEmail author
  • Behzad Mirmahboub
  • Alessandro Perina
  • Vittorio Murino
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9280)


Re-identification systems aim at recognizing the same individuals in multiple cameras and one of the most relevant problems is that the appearance of same individual varies across cameras due to illumination and viewpoint changes. This paper proposes the use of Minimum Multiple Cumulative Brightness Transfer Functions to model this appearance variations. It is multiple frame-based learning approach which leverages consecutive detections of each individual to transfer the appearance, rather than learning brightness transfer function from pairs of images. We tested our approach on standard multi-camera surveillance datasets showing consistent and significant improvements over existing methods on two different datasets without any other additional cost. Our approach is general and can be applied to any appearance-based method.


Re-identification Brightness transfer function Video surveillance 


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Amran Bhuiyan
    • 1
    Email author
  • Behzad Mirmahboub
    • 1
  • Alessandro Perina
    • 1
  • Vittorio Murino
    • 1
  1. 1.Pattern Analysis and Computer Vision (PAVIS)Istituto Italiano di TecnologiaGenovaItaly

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