Portable real time emotion detection system for the disabled

This paper discusses the development of a portable real time emotion detection system for the use of disabled. This system allows the user to train the system with his/her profile comprising of expressions shown on the faces when different emotions occur. With a trained profile that can be updated flexibly, a user can detect his/her behaviour on real time basis. It utilizes the state of the art of face detection and recognition algorithms. The combination of Viola–Jones is used to detect frontal face from video which integrates Haar like features, integral image and AdaBoost learning rule. Principal Component Analysis that uses Eigenfaces to detect emotion shown on the faces is applied. For portability, it requires only a laptop or palmtop with built in camera and speaker that can be mounted on wheelchair easily. It works well in both indoor and outdoor environment day and night.