Facial expression recognition techniques: a comprehensive survey. Issue 7 (7th May 2019)

• Record Type: Journal Article
• Authors: Rajan, Saranya; Chenniappan, Poongodi; Devaraj, Somasundaram; Madian, Nirmala
• Is Part Of: IET image processing. Volume 13:Issue 7(2019)
• Page Start: 1031
• Page End: 1040
• Publication Date: 2019-05-07
• Subjects: emotion recognition -- face recognition -- computer vision -- skin -- muscle -- feature extraction; biometric traits -- human FER system -- facial muscle motion -- skin deformation based algorithms -- conventional FER system -- developed algorithms -- existing algorithms -- classifiers -- datasets -- facial expression recognition techniques -- comprehensive survey -- interesting research area -- substantial progress -- computer vision -- human emotional state; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2018.6647
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : 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.