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Reseach Article

Facial Expression Detection and Recognition using VGG- 16

by Aradhana Singh Parihar, Shweta Agrawal
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 183 - Number 41
Year of Publication: 2021
Authors: Aradhana Singh Parihar, Shweta Agrawal
10.5120/ijca2021921803

Aradhana Singh Parihar, Shweta Agrawal . Facial Expression Detection and Recognition using VGG- 16. International Journal of Computer Applications. 183, 41 ( Dec 2021), 9-16. DOI=10.5120/ijca2021921803

@article{ 10.5120/ijca2021921803,
author = { Aradhana Singh Parihar, Shweta Agrawal },
title = { Facial Expression Detection and Recognition using VGG- 16 },
journal = { International Journal of Computer Applications },
issue_date = { Dec 2021 },
volume = { 183 },
number = { 41 },
month = { Dec },
year = { 2021 },
issn = { 0975-8887 },
pages = { 9-16 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume183/number41/32201-2021921803/ },
doi = { 10.5120/ijca2021921803 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:19:21.250377+05:30
%A Aradhana Singh Parihar
%A Shweta Agrawal
%T Facial Expression Detection and Recognition using VGG- 16
%J International Journal of Computer Applications
%@ 0975-8887
%V 183
%N 41
%P 9-16
%D 2021
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Facial expression recognition software is useful in a variety of circumstances. In recent years, there has been a lot of research on facial expression detection and recognition. Facial expression recognition software is useful in a variety of circumstances such as, security, camera surveillance, criminal investigations, smart card applications, database management systems, and in modern devices for identity verification etc. This paper shows how to implement facial expression detection and recognition system. The facial recognition is to recognize and validate facial traits. However, Haar cascade detection is used to captured facial features in real time. In three different phases the sequential process work can be define, In the first step, a camera detects a human face, and the acquired input is processed based on features with the help of the Keras convolutional neural network model database. Human faces are validated in the third stage to categorize human emotions as happy, neutral, furious, sad, and surprised. This suggested study is broken down into two aspirations: face detection and expression identification. This work will comes under computer vision field. We will use opencv, keras and python programming in this project. The testing result illustrates the system's perfection in detecting and recognizing facial expressions. Finally, we will be able to obtain accurate facial expression detection and identification results.

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Index Terms

Computer Science
Information Sciences

Keywords

Facial Expression Detection VGG- 16