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
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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