Real-Time System of Hand Detection And Gesture Recognition In Cyber Presence Interactive System For E-Learning

TL;DR

This paper presents a real-time hand detection and gesture recognition system designed to monitor learner participation in e-learning environments, aiming to reduce learner isolation and improve engagement through gesture-based indicators.

Contribution

It introduces a novel real-time system that captures and analyzes hand gestures to assess learner participation in virtual classes, enhancing e-learning supervision.

Findings

Effective real-time hand gesture recognition achieved

Participation indicators accurately reflect learner engagement

System alerts tutors about learners with participation difficulties

Abstract

The development of technologies of multimedia, linked to that of Internet and democratization of high outflow, has made henceforth E-learning possible for learners being in virtual classes and geographically distributed. The quality and quantity of asynchronous and synchronous communications are the key elements for E-learning success. It is important to have a propitious supervision to reduce the feeling of isolation in E-learning. This feeling of isolation is among the main causes of loss and high rates of stalling in E-learning. The researches to be conducted in this domain aim to bring solutions of convergence coming from real time image for the capture and recognition of hand gestures. These gestures will be analyzed by the system and transformed as indicator of participation. This latter is displayed in the table of performance of the tutor as a curve according to the time. In case of isolation of learner, the indicator of participation will become red and the tutor will be informed of learners with difficulties to participate during learning session.