3D-based multi-ethnic facial expression database and recognition system

Facial expression accounts for greater percentage of meanings in human interactions. Additionally, it conveniently and non-intrusively allows humans to convey their emotional state or social signs. Accurate recognition of facial expressions should therefore usher ways to the much dreamt human-compu...

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Main Author:	Rabiu, Habibu
Format:	Thesis
Language:	English
Published:	2013
Subjects:	Three-dimensional display systems Facial expression
Online Access:	http://psasir.upm.edu.my/id/eprint/38932/1/FK%202013%203R.pdf
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id	my-upm-ir.38932
record_format	uketd_dc
spelling	my-upm-ir.389322016-01-18T07:57:34Z 3D-based multi-ethnic facial expression database and recognition system 2013-03 Rabiu, Habibu Facial expression accounts for greater percentage of meanings in human interactions. Additionally, it conveniently and non-intrusively allows humans to convey their emotional state or social signs. Accurate recognition of facial expressions should therefore usher ways to the much dreamt human-computer interaction and smart environment. In such scenarios, computers are expected to communicate with human through a seamless and non-intrusive manner. Most researches on this subject were conducted on two dimensional imaging paradigms and have recorded a remarkable performance. However, changes in illumination and pose variations are two issues that impede the performance of such system and constrained them to a very tight acquisition condition. Three dimensional method on the other hand is invariant to both illumination and pose variations and has additional depth information associated with it. This thesis investigates a novel approach to expression recognition using the 3D method. A new Multi-ethnics 3Dbased facial expression database called (UPM-3DFE) is developed, which specifically addressed the issues of database ethnic distribution and subject outfit. Additionally,a novel method for automatic face detection and segmentation is also proposed. In this method, three salient points from each face image are robustly and automatically detected using face’s surface curvature map. The detected points are then used in selecting the appropriate sphere radius to segment the face. In the face alignment step, a new method is also proposed, that aligned the face images intrinsic coordinate system to the world coordinate system. The feature extraction was accomplished using both geometrical and appearance features;distances, angles and line directions are used as the geometrical features,while local binary pattern filter was used in extracting the appearance features. In the final step, Support Vector Machine is employed to classify the selected features into their appropriate groups: neutral, happy, sad, angry, fear, disgust and surprise. The system achieved average classification accuracy of 92.1% for the line direction features, 89.9% for the angle features, 86.5% for the distance features and 76.3% for the local binary pattern features. This system competes favourably with several existing approaches compared with, and the results obtained are promising. Three-dimensional display systems Facial expression 2013-03 Thesis http://psasir.upm.edu.my/id/eprint/38932/ http://psasir.upm.edu.my/id/eprint/38932/1/FK%202013%203R.pdf application/pdf en public phd doctoral Universiti Putra Malaysia Three-dimensional display systems Facial expression
institution	Universiti Putra Malaysia
collection	PSAS Institutional Repository
language	English
topic	Three-dimensional display systems Facial expression
spellingShingle	Three-dimensional display systems Facial expression Rabiu, Habibu 3D-based multi-ethnic facial expression database and recognition system
description	Facial expression accounts for greater percentage of meanings in human interactions. Additionally, it conveniently and non-intrusively allows humans to convey their emotional state or social signs. Accurate recognition of facial expressions should therefore usher ways to the much dreamt human-computer interaction and smart environment. In such scenarios, computers are expected to communicate with human through a seamless and non-intrusive manner. Most researches on this subject were conducted on two dimensional imaging paradigms and have recorded a remarkable performance. However, changes in illumination and pose variations are two issues that impede the performance of such system and constrained them to a very tight acquisition condition. Three dimensional method on the other hand is invariant to both illumination and pose variations and has additional depth information associated with it. This thesis investigates a novel approach to expression recognition using the 3D method. A new Multi-ethnics 3Dbased facial expression database called (UPM-3DFE) is developed, which specifically addressed the issues of database ethnic distribution and subject outfit. Additionally,a novel method for automatic face detection and segmentation is also proposed. In this method, three salient points from each face image are robustly and automatically detected using face’s surface curvature map. The detected points are then used in selecting the appropriate sphere radius to segment the face. In the face alignment step, a new method is also proposed, that aligned the face images intrinsic coordinate system to the world coordinate system. The feature extraction was accomplished using both geometrical and appearance features;distances, angles and line directions are used as the geometrical features,while local binary pattern filter was used in extracting the appearance features. In the final step, Support Vector Machine is employed to classify the selected features into their appropriate groups: neutral, happy, sad, angry, fear, disgust and surprise. The system achieved average classification accuracy of 92.1% for the line direction features, 89.9% for the angle features, 86.5% for the distance features and 76.3% for the local binary pattern features. This system competes favourably with several existing approaches compared with, and the results obtained are promising.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Rabiu, Habibu
author_facet	Rabiu, Habibu
author_sort	Rabiu, Habibu
title	3D-based multi-ethnic facial expression database and recognition system
title_short	3D-based multi-ethnic facial expression database and recognition system
title_full	3D-based multi-ethnic facial expression database and recognition system
title_fullStr	3D-based multi-ethnic facial expression database and recognition system
title_full_unstemmed	3D-based multi-ethnic facial expression database and recognition system
title_sort	3d-based multi-ethnic facial expression database and recognition system
granting_institution	Universiti Putra Malaysia
publishDate	2013
url	http://psasir.upm.edu.my/id/eprint/38932/1/FK%202013%203R.pdf
_version_	1747811766133325824

3D-based multi-ethnic facial expression database and recognition system

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