Virtual learning surveillance processing

Abstract

Virtual learning is an environment where trainees make use of computerized technologies for accessing educational modules exterior to conventional classrooms consigned completely through online. Though it takes over a huge benefit today, learners could lose their concentration easily. To overcome this major drawback, we put forward the idea of surveillance of eye gaze. This uses the technique of Feature extraction method called Kalman filter for gaze movement process. First the eye area is located by Haar’s cascade classifier and once found, the classification is done with the trained datasets which is done through support vector machine (SVM). The salient patches on the image of the face which detects the state of emotions facial landmarks using automatic follow free facial landmark detectioing technique. This gives the result of the attentiveness of the learner by moving to the next webpage if they losses their concentration over it. This technique gives rise to better performance in an e-learning process by almost 3% when compared to the existing system. Thus the eye gazing process increases a better environment for virtual learning process.