INTODUCTION OF FACIAL EXPRESSIONS USING THE PRINCIPAL COMPONENT ANALYSIS METHOD AND BACKPROPAGATION ARTIFICIAL NEURAL NETWORKS

HANDAYANI, RATIH and Sutarno, Sutarno (2019) INTODUCTION OF FACIAL EXPRESSIONS USING THE PRINCIPAL COMPONENT ANALYSIS METHOD AND BACKPROPAGATION ARTIFICIAL NEURAL NETWORKS. Undergraduate thesis, Sriwijaya University.

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Abstract

The amount of system design that can be used to identify various types of objects proves that technological development is increasingly rapid. In terms of pattern recognition, the application of artificial neural networks has proven its success, especially in computer science. ANN method is one method that is quite good for the case of the introduction of patterns, such as letters, shapes, faces, etc. This study aims to build or design a prototype that can recognize a person's facial expressions in real time. The face is part of the human head which covers the area of the forehead to the chin which plays a role in showing one's expression. Basically facial expression is nonverbal communication in humans which aims to convey intentions and emotions to others. By using a face recognition system, faces can be identified for the sake of attendance, population data collection, and security systems because human faces present something complex. In this study used the Backpropagation and Principal Component Analysis (PCA) method. The success rate of the system in this study reached 90%.

Item Type: Thesis (Undergraduate)
Uncontrolled Keywords: Pattern Recognition, Pattern Recognation, Recognition of Facial Expressions, Principal Component Analysis, Backpropagation, real time.
Subjects: Q Science > QA Mathematics > QA75-76.95 Calculating machines > QA75 Electronic computers. Computer science
Divisions: 09-Faculty of Computer Science > 56201-Computer Systems (S1)
Depositing User: Users 831 not found.
Date Deposited: 16 Aug 2019 22:19
Last Modified: 16 Aug 2019 22:19
URI: http://repository.unsri.ac.id/id/eprint/2146

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