Facial expression recognition using bezier curves with hausdorff distance

Emotion recognition is one of the challenging problems in machine vision systems. The most expressive way humans display emotions is through facial expressions. In this project, we extend texture based facial expression recognition with a method of 2D image processing implemented for extracting of features and a neural network based decision trees. The algorithm applies a set of preprocessing and divides the image into two main parts (eyes and lips) and draws Bezier curves for main parts in order to find the emotions. An experimental result shows that the accuracy of the system is 80% through proposed method.