Artificial neural network for the recognition of human emotions under a backpropagation algorithm

Abstract

The era of the technological revolution increasingly encourages the development of technologies that facilitate in one way or another people's daily activities, thus generating a great advance in information processing. The purpose of this work is to implement a neural network that allows classifying the emotional states of a person based on the different human gestures. A database is used with information on students from the PUCE-E School of Computer Science and Engineering. Said information are images that express the gestures of the students and with which the comparative analysis with the input data is carried out. The environment in which this work converges proposes that the implementation of this project be carried out under the programming of a multilayer neuralnetwork. Multilayer feeding neural networks possess a number of properties that make them particularly suitable for complex pattern classification problems [8]. Back-Propagation [4], which is a backpropagation algorithm used in the Feedforward neural network, was taken into consideration to solve the classification of emotions.
 Keywords: Image processing, neural networks, gestures, back-propagation, feedforward, classification, emotions.
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