Exploiting the Use of Ensemble Classifiers to Enhance the Precision of User's Emotion Classification


There is an increasing number of studies in the area of Human-Computer Interaction (HCI) that bears witness to the importance of taking account of emotional factors in interactions with computer systems. By getting to know the emotions of the users, it is possible for artificial agents to have an influence on human feelings with a view to stimulating them in a particular or everyday activities. Thus, one of the great challenges of the HCI area is to enable computer systems to recognize and interpret the feelings of the users. This article sets out a functional Ensemble model for the classification of emotions based on the motor facial expressions of the users. The results described in this article show that the Ensemble Classification that is put forward, can achieve greater rates of accuracy in classifying feelings than what can be obtained by using a single classifier.

In International Conference on Engineering Applications of Neural Networks - EANN.