People’s Re-identification Across Multiple Non-overlapping Cameras by Local Discriminative Patch Matching

  • Rabah IguernaissiEmail author
  • Djamal Merad
  • Pierre Drap
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10317)


People’s tracking in multi-camera systems is one of the most important parts for the study of human’s behavior. In this work, we propose a re-identification method for associating people across non-overlapping cameras for tracking purposes. The proposed method is based on the use of discriminatives patches (salient regions). Our method is based on the proposal of a new framework that is used for selecting the most discriminative patches for each tracked individual. This framework is based on exploiting both appearance and spatial information to find the most discriminative salient regions. In this framework, each individual is represented by a set of values representing a rough description for several local patches extracted from the given individual. Then, this representation is used to select some interest patches that most represent the individual of interest compared to other individuals. At the end, these patches are used for associating new detected individuals to tracked ones.


People re-identification Multi-camera tracking Salient regions 


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Aix-Marseille University, LSIS - UMR CNRS 7296Marseille Cedex 9France

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