Face Detection and Adaptive Zooming for Intelligent Lecturer Tracking System

Distant learning has gained much importance during the global pandemic. Due to the restriction on offline classes, universities and schools were compelled to adapt to the online teaching mode in which live classes and recorded sessions played the key role. For this purpose, an intelligent lecturer tracking system is developed for improving the quality of lectures. In this research study, a face detection technique with adaptive zooming for an Intelligent Lecturer Tracking and Capturing system is proposed. Real-time video is captured and an adaptive zooming technique is applied to maintain a stable output of the lecturer.