Open AccessFacial expression recognition techniques: a comprehensive survey
Author(s) -
Rajan Saranya,
Chenniappan Poongodi,
Devaraj Somasundaram,
Madian Nirmala
Publication year - 2019
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2018.6647
Subject(s) - biometrics , computer science , facial expression , task (project management) , facial recognition system , artificial intelligence , facial expression recognition , machine learning , motion (physics) , computer vision , pattern recognition (psychology) , engineering , systems engineering
Over the past decades, facial expression recognition (FER) has become an interesting research area and achieved substantial progress in computer vision. FER is to detect human emotional state related to biometric traits. Developing a machine based human FER system is a quite challenging task. Various FER systems are developed by analysing facial muscle motion and skin deformation based algorithms. In conventional FER system, the developed algorithms work on the constrained database. In the unconstrained environment, the efficacy of existing algorithms is limited due to certain issues during image acquisition. This study presents a detailed study on FER techniques, classifiers and datasets used for analysing the efficacy of the recognition techniques. Moreover, this survey will assist researchers in understanding the strategies and innovative methods that address the issues in a real‐time application. Finally, the review presents the challenges encountered by FER system along with the future direction.