Bi-Directional Center-Constrained Top-Ranking for Visible Thermal Person Re-Identification

Mang Ye, Xiangyuan Lan, Zheng Wang, Pong Chi Yuen*

*Corresponding author for this work

Research output: Contribution to journalJournal articlepeer-review

232 Citations (Scopus)


Visible thermal person re-identification (VT-REID) is a task of matching person images captured by thermal and visible cameras, which is an extremely important issue in night-time surveillance applications. Existing cross-modality recognition works mainly focus on learning sharable feature representations to handle the cross-modality discrepancies. However, apart from the cross-modality discrepancy caused by different camera spectrums, VT-REID also suffers from large cross-modality and intra-modality variations caused by different camera environments and human poses, and so on. In this paper, we propose a dual-path network with a novel bi-directional dual-constrained top-ranking (BDTR) loss to learn discriminative feature representations. It is featured in two aspects: 1) end-to-end learning without extra metric learning step and 2) the dual-constraint simultaneously handles the cross-modality and intra-modality variations to ensure the feature discriminability. Meanwhile, a bi-directional center-constrained top-ranking (eBDTR) is proposed to incorporate the previous two constraints into a single formula, which preserves the properties to handle both cross-modality and intra-modality variations. The extensive experiments on two cross-modality re-ID datasets demonstrate the superiority of the proposed method compared to the state-of-the-arts.

Original languageEnglish
Pages (from-to)407-419
Number of pages13
JournalIEEE Transactions on Information Forensics and Security
Early online date6 Jun 2019
Publication statusPublished - Jan 2020

Scopus Subject Areas

  • Safety, Risk, Reliability and Quality
  • Computer Networks and Communications

User-Defined Keywords

  • cross-modality
  • Person re-identification (REID)
  • top-ranking
  • visible thermal (VT)


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