The first look: a biometric analysis of emotion recognition using key facial features
Author
Other authors
Publication date
2025ISSN
2624-9898
Abstract
Introduction: Facial expressions play a crucial role in human emotion recognition and social interaction. Prior research has highlighted the significance of the eyes and mouth in identifying emotions; however, limited studies have validated these claims using robust biometric evidence. This study investigates the prioritization of facial features during emotion recognition and introduces an optimized approach to landmark-based analysis, enhancing efficiency without compromising accuracy.
Methods: A total of 30 participants were recruited to evaluate images depicting six emotions: anger, disgust, fear, neutrality, sadness, and happiness. Eye-tracking technology was utilized to record gaze patterns, identifying the specific facial regions participants focused on during emotion recognition. The collected data informed the development of a streamlined facial landmark model, reducing the complexity of traditional approaches while preserving essential information.
Results: The findings confirmed a consistent prioritization of the eyes and mouth, with minimal attention allocated to other facial areas. Leveraging these insights, we designed a reduced landmark model that minimizes the conventional 68-point structure to just 24 critical points, maintaining recognition accuracy while significantly improving processing speed.
Discussion: The proposed model was evaluated using multiple classifiers, including Multi-Layer Perceptron (MLP), Random Decision Forest (RDF), and Support Vector Machine (SVM), demonstrating its robustness across various machine learning approaches. The optimized landmark selection reduces computational costs and enhances real-time emotion recognition applications. These results suggest that focusing on key facial features can improve the efficiency of biometric-based emotion recognition systems without sacrificing accuracy.
Document Type
Article
Document version
Published version
Language
English
Subject (CDU)
004 - Computer science and technology. Computing. Data processing
159.9 - Psychology
Keywords
Emotion recognition
Eye-tracking analysis
Facial landmarks
Biometric validation
Machine learning and AI
Emocions
Seguiment de la mirada
Expressió facial
Identificació biomètrica
Aprenentatge automàtic
Intel·ligència artificial
Pages
p.16
Publisher
Frontiers Media
Is part of
Frontiers in Computer Science 2025, 7
This item appears in the following Collection(s)
Rights
© L'autor/a
Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by/4.0/