A Survey of Automatic Facial Micro-expression Analysis: Databases, Methods and Challenges

TL;DR

This survey reviews recent progress in automatic facial micro-expression analysis, covering databases, methods, challenges, and future directions to enhance applications in clinical, forensic, and security domains.

Contribution

It provides a comprehensive overview of current databases, methods, and challenges in micro-expression analysis, highlighting recent advancements and future research directions.

Findings

Reviewed state-of-the-art micro-expression databases

Analyzed various methods for spotting and recognition

Discussed key challenges and future research directions

Abstract

Over the last few years, automatic facial micro-expression analysis has garnered increasing attention from experts across different disciplines because of its potential applications in various fields such as clinical diagnosis, forensic investigation and security systems. Advances in computer algorithms and video acquisition technology have rendered machine analysis of facial micro-expressions possible today, in contrast to decades ago when it was primarily the domain of psychiatrists where analysis was largely manual. Indeed, although the study of facial micro-expressions is a well-established field in psychology, it is still relatively new from the computational perspective with many interesting problems. In this survey, we present a comprehensive review of state-of-the-art databases and methods for micro-expressions spotting and recognition. Individual stages involved in the automation of these tasks are also described and reviewed at length. In addition, we also deliberate on the challenges and future directions in this growing field of automatic facial micro-expression analysis.