Automatic Assessment of Engagement and Attention of the Student by Means of Facial Expressions

Facial expressions provide non-verbal information about people's emotional and mental states without the need for verbal communication, so the extraction and automatic tracking of facial components are the main tasks that artificial vision systems must solve in the realm of Human behavior, detection of facial expressions, man-machine interfaces, among other areas. In this work are proposed to use Kinect and the facetracking library to create a system that automatically locates the face and perform an interpretation of its elements to detect the motivation in an activity. The evaluation of the tests of this system obtained for cases where the system determined that the subjects were paying attention was 89.79%. For the cases where the system evaluated that the test subjects did not pay attention was 90.72%.