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A survey on techniques to handle face recognition challenges: occlusion, single sample per subject and expression

  • Badr Lahasan
  • Syaheerah Lebai Lutfi
  • Rubén San-Segundo
Article

Abstract

Face recognition is receiving a significant attention due to the need of facing important challenges when developing real applications under unconstrained environments. The three most important challenges are facial occlusion, the problem of dealing with a single sample per subject (SSPS) and facial expression. This paper describes and analyzes various strategies that have been developed recently for overcoming these three major challenges that seriously affect the performance of real face recognition systems. This survey is organized in three parts. In the first part, approaches to tackle the challenge of facial occlusion are classified, illustrated and compared. The second part briefly describes the SSPS problem and the associated solutions. In the third part, facial expression challenge is illustrated. In addition, pros and cons of each technique are stated. Finally, several improvements for future research are suggested, providing a useful perspective for addressing new research in face recognition.

Keywords

Face recognition Facial occlusion challenge Single sample per subject (SSPS) problem Expression 

Notes

Acknowledgements

The authors would like to thank Universiti Sains Malaysia for the funding of this work from the Grant No. 304/PKOMP/6312153. Authors also express their gratitude to Ms. Amal Azazi for her insights and knowledge shared.

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© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.School of Computer ScienceUniverisiti Sains MalaysiaGelugorMalaysia
  2. 2.Department of Computer Science, Faculty of Education-ShabwaUniversity of AdenAdenYemen
  3. 3.Grupo Technología del HablaE.T.S.I. Telecomunicación (ETSIT) Universidad Politécnica de Madrid (UPM)MadridSpain

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