A structural approach to Person Re-identification problem

Amal Mahboubi 1 Luc Brun 1 Donatelo Conte 2
1 Equipe Image - Laboratoire GREYC - UMR6072
GREYC - Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen
Abstract : Although it has been studied extensively during past decades, object tracking is still a difficult problem due to many challenges. Several improvements have been done, but more and more complex scenes (dense crowd, complex interactions) need more sophisticated approaches. Particularly long-term tracking is an interesting problem that allow to track objects even after it may become longtime occluded or it leave/re-enter the field-of-view. In this case the major challenges are significantly changes in appearance, scale and so on. At the heart of the solution of long-term tracking is the re-identification technique, that allows to identify an object coming back visible after an occlusion or re-entering on the scene. This paper proposes an approach for pedestrian re-identification based on structural representation of people. The experimental evaluation is carried out on two public data sets (ETHZ and CAVIAR4REID datasets) and they show promising results compared to others state-of-the-art approaches.
Type de document :
Communication dans un congrès
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Contributeur : Luc Brun <>
Soumis le : jeudi 6 septembre 2018 - 11:21:23
Dernière modification le : mardi 2 juillet 2019 - 16:02:04
Document(s) archivé(s) le : vendredi 7 décembre 2018 - 14:38:59


  • HAL Id : hal-01865218, version 1


Amal Mahboubi, Luc Brun, Donatelo Conte. A structural approach to Person Re-identification problem. 24th International Conference on Pattern Recognition (ICPR), Aug 2018, Pékin, China. pp.1616-1621. ⟨hal-01865218⟩



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