Facial Expression Recognition using Neural Network

This approach proposed a system for the recognition of the facial expression, which can be using cross-correlation of optical flow and mathematical models from the facial points. That defined these facial points of interest in the first frame of an input face sequence image, which utilized manually marker. The facial points were automatically tracked by using a cross-correlation based on optical flow, and extracted feature vectors. The mathematical model extracted features from feature vectors. We were used to classifying expressions when an ELMAN neural network was used. The performances of the proposed facial expressions recognition were computed using Cohn–Kanade facial expressions database. The proposed method achieved a high recognition rate. Keyword—facial expression recognition, optical flow, mathematical model, neural network