Facial Expression Detection by Combining Deep Learning Neural Networks

Abstract

In this paper we detail the construction of a video processing system dedicated to identifying and understanding facial expressions of persons. Our approach implies detection of faciall and marks and analysis of their position to identify emotions. The paper describes a system based on three convolutional neural networks and how to combine them to give more accurate results in the field of facial expression recognition. We adapted the networks which were initially constructed to work on colored or grayscale images to work with black and white images containing facial landmarks. The training, validation and query datasets were also adapted and preprocessed from consecrated computer vision datasets, with the addition of several images acquired by ourselves. We present and comment our experimental results, pointing out advantages and disadvantages.