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Biologically Inspired Computing System for Facial Emotion Detection: A Design Approach

by Sonali Navghare, Shubhangi Giripunje, Preeti Bajaj
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 49 - Number 5
Year of Publication: 2012
Authors: Sonali Navghare, Shubhangi Giripunje, Preeti Bajaj
10.5120/7625-0685

Sonali Navghare, Shubhangi Giripunje, Preeti Bajaj . Biologically Inspired Computing System for Facial Emotion Detection: A Design Approach. International Journal of Computer Applications. 49, 5 ( July 2012), 26-33. DOI=10.5120/7625-0685

@article{ 10.5120/7625-0685,
author = { Sonali Navghare, Shubhangi Giripunje, Preeti Bajaj },
title = { Biologically Inspired Computing System for Facial Emotion Detection: A Design Approach },
journal = { International Journal of Computer Applications },
issue_date = { July 2012 },
volume = { 49 },
number = { 5 },
month = { July },
year = { 2012 },
issn = { 0975-8887 },
pages = { 26-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume49/number5/7625-0685/ },
doi = { 10.5120/7625-0685 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:45:30.564953+05:30
%A Sonali Navghare
%A Shubhangi Giripunje
%A Preeti Bajaj
%T Biologically Inspired Computing System for Facial Emotion Detection: A Design Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 49
%N 5
%P 26-33
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The bio-inspired computation algorithms are the excellent tools for global optimization. These algorithms are very easy to understand and simple to implement. These algorithms especially dominate the classical optimization methods. Particle Swarm Optimization (PSO) is a global optimization algorithm that originally took its inspiration from the biological examples by swarming, flocking and herding phenomena in vertebrates. This paper presents facial emotion recognition system using PSO for different video clips with different cameras, at different distances and light intensity changes. The analysis is done for recognizing "Happy" emotion from other emotions. The comparison of facial emotion recognition system using other techniques and PSO is done. It is found that PSO has better results over other techniques in terms of accuracy and time required.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Bio-inspired Computing Particle Swarm Optimization Lucas-Kanade algorithm