Computer vision research analyzes student attention and academic performance

Research conducted at Uninove explores the use of computer vision to monitor student attention in classrooms. The study aims to address the subjectivity of traditional observation methods by using automated visual information extraction.

Using YOLOv11 and YOLO Face models, the researcher developed a computational method to detect faces and people to correlate attention indicators with academic performance. The study utilized data from a private educational institution in São Paulo to establish these correlations.