Feature Extraction Techniques For Facial Micro-Expression Recognition

Feature extraction techniques play a signiﬁcant role in many computer vision tasks such as detection and recognition. To be able to effectively describe targets, a suitable feature extraction method has to be applied. In this research work, the main goal is to design or formulate the feature extract...

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Main Author:	Oh, Yee Hui
Format:	Thesis
Published:	2016
Subjects:	TA1501-1820 Applied optics Photonics
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id	my-mmu-ep.7169
record_format	uketd_dc
spelling	my-mmu-ep.71692018-07-06T13:04:37Z Feature Extraction Techniques For Facial Micro-Expression Recognition 2016-05 Oh, Yee Hui TA1501-1820 Applied optics. Photonics Feature extraction techniques play a signiﬁcant role in many computer vision tasks such as detection and recognition. To be able to effectively describe targets, a suitable feature extraction method has to be applied. In this research work, the main goal is to design or formulate the feature extraction techniques for facial micro-expression recognition. Subtle emotions possess distinct characteristics compared to the normal facial expressions in a few aspects: elapsed duration and motion intensity. For facial micro-expressions, they are subtle (i.e. less intensive or obvious facial motion changes) and short elapsed duration. Thus, to capture subtle emotions, the designed features have to be able to: (1) contain both spatial and temporal information and (2) preserve the locality information (as facial micro-expressions usually occur at one part of a face). This dissertation introduces three proposed spatio-temporal feature extraction techniques for facial micro-expression recognition based on videos. 2016-05 Thesis http://shdl.mmu.edu.my/7169/ http://library.mmu.edu.my/diglib/onlinedb/dig_lib.php masters Multimedia University Faculty of Engineering
institution	Multimedia University
collection	MMU Institutional Repository
topic	TA1501-1820 Applied optics Photonics
spellingShingle	TA1501-1820 Applied optics Photonics Oh, Yee Hui Feature Extraction Techniques For Facial Micro-Expression Recognition
description	Feature extraction techniques play a signiﬁcant role in many computer vision tasks such as detection and recognition. To be able to effectively describe targets, a suitable feature extraction method has to be applied. In this research work, the main goal is to design or formulate the feature extraction techniques for facial micro-expression recognition. Subtle emotions possess distinct characteristics compared to the normal facial expressions in a few aspects: elapsed duration and motion intensity. For facial micro-expressions, they are subtle (i.e. less intensive or obvious facial motion changes) and short elapsed duration. Thus, to capture subtle emotions, the designed features have to be able to: (1) contain both spatial and temporal information and (2) preserve the locality information (as facial micro-expressions usually occur at one part of a face). This dissertation introduces three proposed spatio-temporal feature extraction techniques for facial micro-expression recognition based on videos.
format	Thesis
qualification_level	Master's degree
author	Oh, Yee Hui
author_facet	Oh, Yee Hui
author_sort	Oh, Yee Hui
title	Feature Extraction Techniques For Facial Micro-Expression Recognition
title_short	Feature Extraction Techniques For Facial Micro-Expression Recognition
title_full	Feature Extraction Techniques For Facial Micro-Expression Recognition
title_fullStr	Feature Extraction Techniques For Facial Micro-Expression Recognition
title_full_unstemmed	Feature Extraction Techniques For Facial Micro-Expression Recognition
title_sort	feature extraction techniques for facial micro-expression recognition
granting_institution	Multimedia University
granting_department	Faculty of Engineering
publishDate	2016
_version_	1747829658725908480

Feature Extraction Techniques For Facial Micro-Expression Recognition

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