Facial Landmark Visualization and Emotion Recognition Through Neural Networks

• URL: http://arxiv.org/abs/2506.17191v1
• Date: Fri, 20 Jun 2025 17:45:34 GMT
• Title: Facial Landmark Visualization and Emotion Recognition Through Neural Networks
• Authors: Israel Juárez-Jiménez, Tiffany Guadalupe Martínez Paredes, Jesús García-Ramírez, Eric Ramos Aguilar,
• Abstract summary: Emotion recognition from facial images is a crucial task in human-computer interaction.<n>Previous studies have shown that facial images can be used to train deep learning models.<n>We propose facial landmark box plots, a visualization technique designed to identify outliers in facial datasets.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Emotion recognition from facial images is a crucial task in human-computer interaction, enabling machines to learn human emotions through facial expressions. Previous studies have shown that facial images can be used to train deep learning models; however, most of these studies do not include a through dataset analysis. Visualizing facial landmarks can be challenging when extracting meaningful dataset insights; to address this issue, we propose facial landmark box plots, a visualization technique designed to identify outliers in facial datasets. Additionally, we compare two sets of facial landmark features: (i) the landmarks' absolute positions and (ii) their displacements from a neutral expression to the peak of an emotional expression. Our results indicate that a neural network achieves better performance than a random forest classifier.

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