A facial expression recognition system using neural networks
Jyh‐Yeong Chang, Jialin Chen · 2003
This paper proposes an automatic facial expression recognition system using neural network classifiers. First, we use the rough contour estimation routine, mathematical morphology, and point contour detection method to extract the precise contours of the eyebrows, eyes, and mouth of a face image. Then we define 30 facial characteristic points to describe the position and shape of these three organs. Facial expressions can be described by combining different action units that are used for describing the basic muscle movement of a human face. We choose six main action units, being composed of facial characteristic points movements, as the input vectors for two different neural network-based expression classifiers including radial basis function network and multilayer perceptron network. Using these two networks, we have obtained the same recognition rate as high as 92.1%. Simulation results by the computer demonstrate that computers are capable of extracting high-level or abstract information like human.