Simultaneous face and facial expression recognition using a MLP neural network based on constructive training algorithm Online publication date: Fri, 21-Jul-2017
by Hayet Boughrara; Mohamed Chtourou; Chokri Ben Amar
International Journal of Applied Pattern Recognition (IJAPR), Vol. 4, No. 2, 2017
Abstract: This paper proposes a system for simultaneous recognition of faces and facial expressions using a constructive training algorithm. A MLP classifier has been developed to recognise at the same time face and facial expression. Feature extraction step is based on perceived facial images. The algorithm is formed by a reduced number of hidden neurons and a set of training patterns. A new hidden neuron is added when mean square error (MSE) of training data (TD) is not reduced to a predefined value. Input patterns are trained incrementally until all patterns of TD are learned. The proposed algorithm seeks to find synthesis parameters as patterns number corresponding for the subsets of each class to be presented initially in training step, initial number of hidden neurons, iterations number as well as the MSE value. By comparing with a fixed MLP and feature extraction techniques, the effectiveness of the proposed approach has been proven.
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