The goal of this research is to catalog the myriad of emotions that are experienced by people and to determine a person's state of mind by observing his or her behavior and drawing conclusions from those observations. Anger, sadness, fear, pleasure, disgust, surprise, and neutral are some of the facial emotion classes that may be recognized by utilizing facial expression recognition, often known as FER. Finding the database in the emotion by applying the Fluorescence‐activated cell sorting (FACS) action unit (AU), such as impression investigation, diagnosing depression and behavioral disorders, lying detection, and (hidden) emotion identification, among other things. A deep convolutional neural network (CNN) approach was used in order to realize the goal of recognizing different facial expressions. The technique that was recommended puts a significant focus on achieving a high degree of accuracy when determining the feelings that are communicated in live video footage.
Drivers’ Emotions’ Recognition Using Facial Expression from Live Video Clips in Autonomous Vehicles
2024-05-29
20 pages
Article/Chapter (Book)
Electronic Resource
English
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