Educator's feedback through expression recognition

Abstract

Evaluating educator's effectiveness is important in nearly every institution of higher education. Assessing the effectiveness with which various functions are performed is essential to a variety of important administration recommendations and decisions. Assessing a faculty member's teaching capabilities constitutes a serious challenge. A facial expression results from one or more motions or positions of the muscles of the face. These movements convey the emotional state of the individual to observers. Facial expression analysis refers to computer systems that attempt to automatically analyze and recognize facial motions from visual information. We are exploring the potential of technology enabled feedback system to provide authentic feedback of the teacher while teaching. Images are captured in the class and feedback is generated by studying the expressions of the students in the class in non intrusive technique. This paper proposes a framework for evaluating the faculty member's feedback through facial expression analysis of the students. It reports on the progress made in the development of a facial expression analysis component for assessing the feedback of teacher in a classroom. Digital camera is used to grab the image of the learner and signal processing techniques such as Wavelet and ANN are employed to extract facial expressions. We have suggested a framework for detecting learner's face and locating permanent facial features such as eyebrow, eyes, and mouth. Facial expression analysis is performed based on both permanent and transient facial features in a nearly frontal-view face image sequence.