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Efficient Facial Expression Recognition System Based on Geometric Features Using Neural Network

Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 10)

Abstract

In this paper, facial expression recognition (FER) system is presented using eigenvector to recognize expressions from facial images. One of the distance metric approaches called Euclidean distance is used to discover the distance of the facial features which was associated with each of the face images. A comprehensive, efficient model using a multilayer perceptron has been advanced whose input is a 2D facial spatial feature vector incorporating left eye, right eye, lips, nose, and lips and nose together. The expression recognition definiteness of the proposed methodology using multilayer perceptron model has been compared with J48 decision tree and support vector machine. The final result shows that the designed model is very efficacious in recognizing six facial emotions. The proposed methodology shows that the recognition rate is far better than J48 and support vector machine.

Keywords

Facial expression recognition Facial expressions Eigenvectors Eigenvalues 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Mody University of Science and Technology, CETLakshmangarhIndia

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