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Erschienen in:
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2018 | OriginalPaper | Buchkapitel

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

verfasst von : Ankita Tripathi, Shivam Pandey, Hitesh Jangir

Erschienen in: Information and Communication Technology for Sustainable Development

Verlag: Springer Singapore

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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.

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Vorheriges Kapitel Cross-Domain Sentiment Analysis Employing Different Feature Selection and Classification Techniques
Nächstes Kapitel Extended Four-Step Travel Demand Forecasting Model for Urban Planning
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Metadaten
Titel
Efficient Facial Expression Recognition System Based on Geometric Features Using Neural Network
verfasst von
Ankita Tripathi
Shivam Pandey
Hitesh Jangir
Copyright-Jahr
2018
Verlag
Springer Singapore
Buch
Information and Communication Technology for Sustainable Development

Print ISBN: 978-981-10-3919-5

Electronic ISBN: 978-981-10-3920-1

Copyright-Jahr: 2018

DOI
https://doi.org/10.1007/978-981-10-3920-1_18

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