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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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 |
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MMU Institutional Repository |
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TA1501-1820 Applied optics Photonics |
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TA1501-1820 Applied optics Photonics Oh, Yee Hui Feature Extraction Techniques For Facial Micro-Expression Recognition |
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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 |
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1747829658725908480 |