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Real-time system for facial emotion detection using GPSO algorithm

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Main Authors: Bashir, Mohammed Ghandi, R., Nagarajan, Prof. Dr., Hazry, Desa, Assoc. Prof. Dr.
Other Authors: bmghandi@gmail.com
Format: Working Paper
Language:English
Published: Institute of Electrical and Electronics Engineers (IEEE) 2012
Subjects:
Emotion detection
Facial action units
Facial emotions
Facial expressions
Particle swarm optimization (PSO)
PSO
Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/19124
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spelling my.unimap-191242012-05-10T13:38:02Z Real-time system for facial emotion detection using GPSO algorithm Bashir, Mohammed Ghandi R., Nagarajan, Prof. Dr. Hazry, Desa, Assoc. Prof. Dr. bmghandi@gmail.com nagarajan@unimap.edu.my Emotion detection Facial action units Facial emotions Facial expressions Particle swarm optimization (PSO) PSO Link to publisher's homepage at http://www.ieee.org/ Particle Swarm Optimization (PSO) algorithm has been widely recognized as an efficient algorithm with applicability is many areas. Recently, we proposed the Guided Particle Swarm Optimization (GPSO) algorithm, which is a modification to PSO designed for facial emotion detection. GPSO involves keeping track of relevant points, called Action Units (AUs), which are specified on the face of a subject. Swarm of particles was defined such that each particle has a component within the neighborhood of each AU. We implement GPSO into a facial emotion detection system that can detect the six basic universal emotions. The system was tested on a variety of subjects and the results realized were very promising. However, application of the system was limited to pre-recorded video clips because the AUs must be pre-processed to obtain their positions over time, which were then fed as input to the system. In this paper, we present an improvement we made to the system by applying Lucas-Kanade (LK) optical flow algorithm. LK algorithm allowed us to keep track of the positions of the AUs in real-time, thereby eliminating the need for preprocessing. The improved system is now a real-time system that works on video streams to identify facial emotions and achieved the same promising detection success rates as the original system. 2012-05-10T13:38:02Z 2012-05-10T13:38:02Z 2010-10-03 Working Paper p. 40-45 978-142447647-3 http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=5679500 http://hdl.handle.net/123456789/19124 en Proceedings of the IEEE Symposium on Industrial Electronics and Applications (ISIEA 2010) Institute of Electrical and Electronics Engineers (IEEE)
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Emotion detection
Facial action units
Facial emotions
Facial expressions
Particle swarm optimization (PSO)
PSO
spellingShingle Emotion detection
Facial action units
Facial emotions
Facial expressions
Particle swarm optimization (PSO)
PSO
Bashir, Mohammed Ghandi
R., Nagarajan, Prof. Dr.
Hazry, Desa, Assoc. Prof. Dr.
Real-time system for facial emotion detection using GPSO algorithm
description Link to publisher's homepage at http://www.ieee.org/
author2 bmghandi@gmail.com
author_facet bmghandi@gmail.com
Bashir, Mohammed Ghandi
R., Nagarajan, Prof. Dr.
Hazry, Desa, Assoc. Prof. Dr.
format Working Paper
author Bashir, Mohammed Ghandi
R., Nagarajan, Prof. Dr.
Hazry, Desa, Assoc. Prof. Dr.
author_sort Bashir, Mohammed Ghandi
title Real-time system for facial emotion detection using GPSO algorithm
title_short Real-time system for facial emotion detection using GPSO algorithm
title_full Real-time system for facial emotion detection using GPSO algorithm
title_fullStr Real-time system for facial emotion detection using GPSO algorithm
title_full_unstemmed Real-time system for facial emotion detection using GPSO algorithm
title_sort real-time system for facial emotion detection using gpso algorithm
publisher Institute of Electrical and Electronics Engineers (IEEE)
publishDate 2012
url http://dspace.unimap.edu.my/xmlui/handle/123456789/19124
_version_ 1643792611300868096
score 13.222552

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