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Artificial Intelligence Review
Erschienen in: Artificial Intelligence Review 2/2019

14.09.2017

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

verfasst von: Badr Lahasan, Syaheerah Lebai Lutfi, Rubén San-Segundo

Erschienen in: Artificial Intelligence Review | Ausgabe 2/2019

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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.
Vorheriger Artikel Face detection techniques: a review
Nächster Artikel Age invariant face recognition: a survey on facial aging databases, techniques and effect of aging

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Metadaten
Titel
A survey on techniques to handle face recognition challenges: occlusion, single sample per subject and expression
verfasst von
Badr Lahasan
Syaheerah Lebai Lutfi
Rubén San-Segundo
Publikationsdatum
14.09.2017
Verlag
Springer Netherlands
Erschienen in
Artificial Intelligence Review / Ausgabe 2/2019
Print ISSN: 0269-2821
Elektronische ISSN: 1573-7462
DOI
https://doi.org/10.1007/s10462-017-9578-y

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