Web-Agile Facial Emotion Recognition and Eye-Tracking System (WAFER-ET)

This study presents the Web-Agile Facial Emotion Recognition and Eye-Tracking System (WAFER-ET), which combines AI-based facial expression recognition and eye-tracking models. Eye tracking is implemented using WebGazer.js, and facial expression recognition using a custom lightweight CNN-based model (CLCM). Experimental analysis showed effective performance in the system's real-time processing and data streaming. The low delay between the experimental and real-time results platforms and low memory load were achieved. Moreover, integrating facial expression recognition and eye tracking in the WAFER-ET system enables different fields of application.