Trends and Controversies

  • Hugo Proenca
  • , Mark Nixon
  • , Michele Nappi
  • , Esam Ghaleb
  • , Gokhan Ozbulak
  • , Hua Gao
  • , Hazim Kemal Ekenel
  • , Klemen Grm
  • , Vitomir Struc
  • , Hailin Shi
  • , Xiangyu Zhu
  • , Shengcai Liao
  • , Zhen Lei
  • , Stan Z. Li
  • , Weronika Gutfeter
  • , Andrzej Pacut
  • , Joel Brogan
  • , Walter J. Scheirer
  • , Ester Gonzalez-Sosa
  • , Ruben Vera-Rodriguez
  • Julian Fierrez, Javier Ortega-Garcia, Daniel Riccio, Luigi De Maio

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Performing covert biometric recognition in surveillance environments has been regarded as a grand challenge, considering the adversity of the conditions where recognition should be carried out (e.g., poor resolution, bad lighting, off-pose and partially occluded data). This special issue compiles a group of approaches to this problem.

Original languageEnglish
Article number8423530
Pages (from-to)41-67
Number of pages27
JournalIEEE Intelligent Systems
Volume33
Issue number3
DOIs
StatePublished - May 1 2018
Externally publishedYes

Funding

This work is supported by ‘’FCT – Fundação para a Ciência e Tecnologia” (Portugal), through the project “UID/EEA/50008/2013”. This work has been partially supported by project CogniMetrics TEC2015-70627-R (MINECO/FEDER). E. GonzalezSosa is supported by a PhD scholarship from Universidad Au-tonoma de Madrid. This work was supported by TUBITAK project number 113E067 and by a Marie Curie FP7 Integration Grant within the 7th EU Framework Programme.

Keywords

  • QUIS-CAMPI
  • deep models
  • face recognition
  • surveillance

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