A Review of Deep Learning Methods in Automatic Facial Micro-expression Recognition
- Title
- A Review of Deep Learning Methods in Automatic Facial Micro-expression Recognition
- Creator
- Mukku L.; Thomas J.
- Description
- Facial expression analysis to understand human emotion is the base for affective computing. Until the last decade, researchers mainly used facial macro-expressions for classification and detection problems. Micro-expressions are the tiny muscle moments in the face that occur as responses to feelings and emotions. They often reveal true emotions that a person attempts to suppress, hide, mask, or conceal. These expressions reflect a persons real emotional state. They can be used to achieve a range of goals, including public protection, criminal interrogation, clinical assessment, and diagnosis. It is still relatively new to utilize computer vision to assess facial micro-expressions in video sequences. Accurate machine analysis of facial micro-expression is now conceivable due to rapid progress in computational methodologies and video acquisition methods, as opposed to a decade ago when this had been a realm of therapists and assessment seemed to be manual. Even though the research of facial micro-expressions has become a longstanding topic in psychology, this is still a comparatively recent computational science with substantial obstacles. This paper a provides a comprehensive review of current databases and various deep learning methodologies to analyze micro-expressions. The automation of these procedures is broken down into individual steps, which are documented and debated. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
- Source
- Lecture Notes on Data Engineering and Communications Technologies, Vol-163, pp. 1-16.
- Date
- 2023-01-01
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Subject
- Deep learning; Emotion recognition; Facial image analysis; LBP-TOP; Micro-expression recognition; Micro-expressions; Optical flow
- Coverage
- Mukku L., CHRIST (Deemed to be University), Bangalore, 560064, India; Thomas J., CHRIST (Deemed to be University), Bangalore, 560064, India
- Rights
- Restricted Access
- Relation
- ISSN: 23674512
- Format
- Online
- Language
- English
- Type
- Book chapter
Collection
Citation
Mukku L.; Thomas J., “A Review of Deep Learning Methods in Automatic Facial Micro-expression Recognition,” CHRIST (Deemed To Be University) Institutional Repository, accessed November 4, 2025, https://archives.christuniversity.in/items/show/18470.