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Investigation of nonlinear feature extraction techniques for facial emotion recognition

Doctor of Philosophy in Mechatronic Engineering

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Bibliographic Details
Main Author: Hasimah, Ali
Other Authors: Hariharan, Muthusamy, Dr.
Format: Thesis
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2016
Subjects:
Facial expression
Emotion recognition
Pattern recognition systems
Human-computer interaction
Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/77199
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spelling my.unimap-771992022-11-25T01:12:04Z Investigation of nonlinear feature extraction techniques for facial emotion recognition Hasimah, Ali Hariharan, Muthusamy, Dr. Facial expression Emotion recognition Pattern recognition systems Human-computer interaction Doctor of Philosophy in Mechatronic Engineering Over the last decades, facial emotion recognition has received a significant interest among researchers in areas of computer vision, pattern recognition and its related field. The increasing applications of facial emotion recognition have shown a sizeable impact in many areas ranging from psychology to human-computer interaction (HCI). Although facial emotion recognition has achieved a certain level of success, however its performance is far from human perception. Many approaches have been constantly proposed in the literature. In fact, the ability of facial emotion recognition to operate in fully automated with high accuracy remains challenging due to various problems such as intra-class variations, inter-class similarities and subtle changes of facial features. The adhered problem is further hampered as physiognomies of faces with respect to age, ethnicity and gender, thus increase the difficulties of recognizing the facial emotion. In order to resolve this problem, this thesis aims to develop nonlinear features extraction techniques of using Higher Order Spectra (HOS) and Empirical Mode Decomposition (EMD) separately in recognizing the seven facial emotions (anger, disgust, fear, happiness, neutral, sadness and surprise) from static images. A pre-processing step of isolating face region from different background was first employed by means of face detection. The 2-D facial image was then projected into 1-D facial signal by successive projection via Radon transform. Radon transform is translation and rotation invariant, hence preserves the variations in pixel intensities. The facial signal that describes the expression was extracted using HOS and EMD to obtain a set of significant features. In HOS framework, the third order statistic or bispectrum that captures contour (shape) and texture information was applied on facial signal. In this work, a new set of bispectral features was used to characterize the distinctive features of seven classes of emotion. While, in EMD framework, the facial signal was decomposed using EMD to produce a small set of intrinsic mode functions (IMFs) via sifting process. The IMF features which exhibit the unique pattern were used to differentiate the facial emotions. 2016 2022-11-25T01:10:29Z 2022-11-25T01:10:29Z Thesis http://dspace.unimap.edu.my:80/xmlui/handle/123456789/77199 en Universiti Malaysia Perlis (UniMAP) Universiti Malaysia Perlis (UniMAP) School of Mechatronic Engineering
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 Facial expression
Emotion recognition
Pattern recognition systems
Human-computer interaction
spellingShingle Facial expression
Emotion recognition
Pattern recognition systems
Human-computer interaction
Hasimah, Ali
Investigation of nonlinear feature extraction techniques for facial emotion recognition
description Doctor of Philosophy in Mechatronic Engineering
author2 Hariharan, Muthusamy, Dr.
author_facet Hariharan, Muthusamy, Dr.
Hasimah, Ali
format Thesis
author Hasimah, Ali
author_sort Hasimah, Ali
title Investigation of nonlinear feature extraction techniques for facial emotion recognition
title_short Investigation of nonlinear feature extraction techniques for facial emotion recognition
title_full Investigation of nonlinear feature extraction techniques for facial emotion recognition
title_fullStr Investigation of nonlinear feature extraction techniques for facial emotion recognition
title_full_unstemmed Investigation of nonlinear feature extraction techniques for facial emotion recognition
title_sort investigation of nonlinear feature extraction techniques for facial emotion recognition
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2016
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/77199
_version_ 1753972993789263872
score 13.214268

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