Transactions on Machine Intelligence

Transactions on Machine Intelligence

Facial Emotional State Recognition Inspired by the Human Brain

Document Type : Original Article

Authors
A. Kulkarni 1
N. Rajput 2
1 Department of Computer Science and Automation, Indian Institute of Science (IISc), Bengaluru, India
2 Department of Electronics and Communication Engineering, National Institute of Technology Tiruchirappalli (NIT Trichy), Tiruchirappalli, India
10.22034/tmi.2025.253007
Abstract
Facial emotional expressions play a fundamental role in conveying intentions and enhancing the quality of human communication. With the rapid advancement of facial recognition technologies and the increasing importance of emotion recognition, this study investigates facial emotional expression recognition using a Brain Emotional Learning (BEL) model. The Brain Emotional Learning model is inspired by the human brain’s limbic system, which is responsible for processing emotional stimuli. The primary objective of this study is to improve the recognition rate of facial emotional expressions. The input to the proposed model is the standard Cohn–Kanade (CK) dataset, which contains six emotional states: happiness, sadness, anger, surprise, fear, and disgust. Image features are extracted using Principal Component Analysis (PCA) and subsequently fed into the classification stage of the Brain Emotional Learning model to determine the recognition rate of facial emotional expressions. In addition, a correlation matrix comprising the eyebrow, eye, and mouth features is constructed, and facial emotional states are identified through an averaging process. The correlation matrix is capable of recognizing facial emotional states when only one of these features is provided as input to the system. The analysis of the dataset demonstrates a facial emotion recognition rate of 95.81%. The findings indicate that the proposed Brain Emotional Learning model achieves a high level of accuracy in recognizing facial emotional expressions.
Keywords
Brain Emotional Learning (BEL) Model
Principal Component Analysis (PCA)
Correlation Matrix
Facial Expression Recognition
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Transactions on Machine Intelligence
Volume 8, Issue 4
Autumn 2025
Pages 248-258

  • Receive Date 20 August 2025
  • Revise Date 13 November 2025
  • Accept Date 04 December 2025