This paper presents a novel facial expression recognition approach based on Completed Local Binary Pattern model and Support Vector Machine classification to propose a method for applying to intelligent game applications and intelligent communication systems. More clearly, 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 both JAFFE (213 images) and FEED (2268 images) databases show the effectiveness of the proposed method in comparison with some other methods. The advantage of this technique is simple, fast and high accuracy.