Guest Editor(s)
Dr. Mariko Nakano
Email: mnakano@ipn.mx
Affiliation: Graduate and Research Seccion (SEPI), Instituto Politecnico Nacional, Mexico City, Mexico
Homepage:
Research Interests: image processing, signal processing, computer vision, face recognition, facial expression recognition, human action detection, video anomaly detection, machine learning, deep learning
Dr. Enrique Escamilla-Hernandez
Email: eescamillah@ipn.mx
Affiliation: Graduate and Research Seccion (SEPI), Instituto Politecnico Nacional, Mexico City, Mexico
Homepage:
Research Interests: signal processing, imagen processing, biomedical engineering, machine learning, real-time multimedia system
Dr. Oswaldo Ulises Juarez-Sandoval
Email: ojuarezs@ipn.mx
Affiliation: Graduate and Research Seccion (SEPI), Instituto Politecnico Nacional, Mexico City, Mexico
Homepage:
Research Interests: signal processing, imagen processing, computer vision, pattern recognition, ownership authentication, information security, cybersecurity in power electronics systems
Summary
Facial recognition (FR) has become an essential technology in modern society, with applications ranging from security and surveillance to access control and identity verification. Although significant progress has been achieved in recognizing high-resolution facial images, real-world deployment remains challenging due to factors such as low image quality, occlusions, poor illumination, long-distance image acquisition, and pose variations. These challenges often lead to a considerable reduction in recognition accuracy, highlighting the need for more robust and reliable FR systems. Consequently, advancing face recognition technologies for practical applications continues to be an important research topic.
At the same time, facial expression recognition (FER) has attracted increasing attention because of its potential in human–computer interaction, telemedicine, e-learning, and affective computing. Dynamic facial expression recognition (DFER), which analyzes facial expressions from video sequences rather than static images, has emerged as a promising research direction. The rapid development of deep learning has accelerated progress in both FR and FER, resulting in numerous innovative methods and improved performance.
This Special Issue aims to present recent advances in face and facial expression recognition, with an emphasis on practical applications and real-world deployment. It welcomes original contributions addressing novel algorithms, robust recognition systems, emerging challenges, and interdisciplinary applications. Through these contributions, the Special Issue seeks to provide insights into current developments and future research directions in these rapidly evolving fields.
Suggested Topics
Authors are invited to submit original research articles, reviews, and application papers related to, but not limited to, the following topics:
· Face recognition in unconstrained environments
· Face recognition under occlusions, illumination, and pose variations
· Video-based face recognition
· Facial expression recognition (FER)
· Dynamic facial expression recognition (DFER)
· Explainable and trustworthy face recognition systems
· Face anti-spoofing and presentation attack detection
· Face recognition for forensic applications
· Intelligent video surveillance systems
· Human–computer interaction based on facial behavior analysis
· Affective computing and emotion-aware systems
· Real-time and edge-AI face analysis systems
Keywords
face recognition, facial expression recognition, biometrics, affective computing, emotion recognition, human–computer interaction, face anti-spoofing, video surveillance, forensic analysis
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