Facial Expression Analysis and Its Potentials in IoT Systems: A Contemporary Survey

TL;DR

This survey reviews recent advancements in facial expression analysis techniques, emphasizing their integration with IoT systems for applications in healthcare and security, and discusses future challenges and opportunities.

Contribution

It provides a comprehensive overview of facial expression analysis methods and explores their potential integration with IoT, highlighting recent developments and future research directions.

Findings

Enhanced real-time emotion monitoring in healthcare IoT systems

Improved surveillance accuracy through IoT-based micro-expression detection

Identification of key challenges and future research directions

Abstract

Facial expressions convey human emotions and can be categorized into macro-expressions (MaEs) and micro-expressions (MiEs) based on duration and intensity. While MaEs are voluntary and easily recognized, MiEs are involuntary, rapid, and can reveal concealed emotions. The integration of facial expression analysis with Internet-of-Thing (IoT) systems has significant potential across diverse scenarios. IoT-enhanced MaE analysis enables real-time monitoring of patient emotions, facilitating improved mental health care in smart healthcare. Similarly, IoT-based MiE detection enhances surveillance accuracy and threat detection in smart security. Our work aims to provide a comprehensive overview of research progress in facial expression analysis and explores its potential integration with IoT systems. We discuss the distinctions between our work and existing surveys, elaborate on advancements in MaE and MiE analysis techniques across various learning paradigms, and examine their potential applications in IoT. We highlight challenges and future directions for the convergence of facial expression-based technologies and IoT systems, aiming to foster innovation in this domain. By presenting recent developments and practical applications, our work offers a systematic understanding of the ways of facial expression analysis to enhance IoT systems in healthcare, security, and beyond.