An effective facial expression recognition approach for intelligent game systems

Abstract

This paper presents a novel facial expression recognition approach based on an improved model of completed local binary pattern and support vector machine classification to propose a method for applying to intelligence game applications as well as intelligence communication systems. The capturing emotion of players can be applied in interactive games with various purposes, such as transferring player's emotions to his or her avatar, or activating suitable action to communicate with players in order to obtain positive attitude of the players in educational games. Our experiments on two databases included JAFFE 213 images and CK 2040 images databases show the effectiveness of the proposed method in comparison with some other methods. The accuracy recognition rate of JAFFE database is 96.28% and CK database is 99.85%. The advantage of this technique is simple, fast and high accuracy.