Automated marker placement based real-time facial emotional expression recognition system

Facial expression recognition attracted several researchers over the past several decades and most of the researchers in the literature focus on facial expression recognition in “offline” and very few research works concentrated on real-time facial expression recognition. In order to develop an inte...

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Format:	Thesis
Language:	English
Subjects:	Face detection Emotion recognition Intelligent real-time facial expression recognition system > Design and construction Intelligent real-time facial expression recognition system
Online Access:	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77170/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77170/2/Full%20text.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77170/4/Vasanthan.pdf
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id	my-unimap-77170
record_format	uketd_dc
spelling	my-unimap-771702022-11-24T07:26:41Z Automated marker placement based real-time facial emotional expression recognition system Wan Khairunizam, Wan Ahmad, Assoc. Prof. Dr. Facial expression recognition attracted several researchers over the past several decades and most of the researchers in the literature focus on facial expression recognition in “offline” and very few research works concentrated on real-time facial expression recognition. In order to develop an intelligent real-time facial expression recognition system, this thesis proposed an automated marker placement method for classifying six basic facial expressions (happiness, sadness, anger, fear, disgust and surprise) using real-time video sequence. Initially, manual marker placement was carried out to detect the mean position (distance between the centre of the face to the marker’s location) of each marker on the subject’s face. This position was used to expand the automated marker placement algorithm for facial emotion recognition. In this experiment, subjects were requested manually to place ten markers (four markers on the upper face and six markers on lower face) on their face in specified locations based on Facial Action Coding System (FACS). Trial and error approach devised the number of markers used for facial expression detection. Manual markers were placed by clicking the cursor at each position on the facial image in video sequence. The mean marker position distance was calculated from the centre of the face. Calculation of each marker position concerning the middle of the face via manual marker placement was then used to develop the automatic marker placement algorithm. Universiti Malaysia Perlis (UniMAP) Thesis en http://dspace.unimap.edu.my:80/xmlui/handle/123456789/77170 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77170/3/license.txt 8a4605be74aa9ea9d79846c1fba20a33 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77170/1/Page%201-24.pdf 2ea4c98abb6a5899482f1b58da2ca9c3 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77170/2/Full%20text.pdf 1b760bac1d856b27372a06bb4efc8025 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77170/4/Vasanthan.pdf 097b3c20f544db8e4b1ca4aac1b0770c Universiti Malaysia Perlis (UniMAP) Face detection Emotion recognition Intelligent real-time facial expression recognition system -- Design and construction Intelligent real-time facial expression recognition system School of Mechatronic Engineering
institution	Universiti Malaysia Perlis
collection	UniMAP Institutional Repository
language	English
advisor	Wan Khairunizam, Wan Ahmad, Assoc. Prof. Dr.
topic	Face detection Emotion recognition Intelligent real-time facial expression recognition system -- Design and construction Intelligent real-time facial expression recognition system
spellingShingle	Face detection Emotion recognition Intelligent real-time facial expression recognition system -- Design and construction Intelligent real-time facial expression recognition system Automated marker placement based real-time facial emotional expression recognition system
description	Facial expression recognition attracted several researchers over the past several decades and most of the researchers in the literature focus on facial expression recognition in “offline” and very few research works concentrated on real-time facial expression recognition. In order to develop an intelligent real-time facial expression recognition system, this thesis proposed an automated marker placement method for classifying six basic facial expressions (happiness, sadness, anger, fear, disgust and surprise) using real-time video sequence. Initially, manual marker placement was carried out to detect the mean position (distance between the centre of the face to the marker’s location) of each marker on the subject’s face. This position was used to expand the automated marker placement algorithm for facial emotion recognition. In this experiment, subjects were requested manually to place ten markers (four markers on the upper face and six markers on lower face) on their face in specified locations based on Facial Action Coding System (FACS). Trial and error approach devised the number of markers used for facial expression detection. Manual markers were placed by clicking the cursor at each position on the facial image in video sequence. The mean marker position distance was calculated from the centre of the face. Calculation of each marker position concerning the middle of the face via manual marker placement was then used to develop the automatic marker placement algorithm.
format	Thesis
title	Automated marker placement based real-time facial emotional expression recognition system
title_short	Automated marker placement based real-time facial emotional expression recognition system
title_full	Automated marker placement based real-time facial emotional expression recognition system
title_fullStr	Automated marker placement based real-time facial emotional expression recognition system
title_full_unstemmed	Automated marker placement based real-time facial emotional expression recognition system
title_sort	automated marker placement based real-time facial emotional expression recognition system
granting_institution	Universiti Malaysia Perlis (UniMAP)
granting_department	School of Mechatronic Engineering
url	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77170/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77170/2/Full%20text.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77170/4/Vasanthan.pdf
_version_	1776104234422370304

Automated marker placement based real-time facial emotional expression recognition system

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