Skip to Main content Skip to Navigation
Conference papers

Ré-identification de personne avec perte min-triplet

yiqiang Chen Stefan Duffner 1 Andrei Stoian 2 Jean-yves Dufour 2 Atilla Baskurt 1 
1 imagine - Extraction de Caractéristiques et Identification
LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
Abstract : In this paper, we propose a person re-identification method based on a triplet neural network. The person re-identification problem consists to find one identity among a set of people in different places with one or several non-overlapping surveillance cameras. In order to do this, our system extracts first viewpoint invariant features, then uses a triplet neural network to learn a metric. We propose a new loss function for this neural network called min-triplet loss. Finally, we compare our results with the state-of-art on several public person re-identification benchmarks.
Document type :
Conference papers
Complete list of metadata

Cited literature [31 references]  Display  Hide  Download
Contributor : Yiqiang CHEN Connect in order to contact the contributor
Submitted on : Friday, October 27, 2017 - 4:27:01 PM
Last modification on : Monday, April 4, 2022 - 10:40:40 AM
Long-term archiving on: : Sunday, January 28, 2018 - 4:12:35 PM


Files produced by the author(s)


  • HAL Id : hal-01625496, version 1


yiqiang Chen, Stefan Duffner, Andrei Stoian, Jean-yves Dufour, Atilla Baskurt. Ré-identification de personne avec perte min-triplet. 16èmes Journées francophones des jeunes chercheurs en vision par ordinateur (ORASIS 2017), Jun 2017, Colleville-sur-Mer, France. ⟨hal-01625496⟩



Record views


Files downloads