Emotion modeling
Human emotion is a very important part of human to human communication. To be able to incorporate emotions into a Human Computer Interaction (HCI) system would greatly improve the quality of the HCI.Much work has been done in the Emotion recognition field. Image filters, feature extraction, feature...
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sg-ntu-dr.10356-446422023-03-03T20:47:52Z Emotion modeling Ng, Glenn Hong Kiat. Quek Hiok Chai School of Computer Engineering Centre for Computational Intelligence DRNTU::Engineering::Computer science and engineering Human emotion is a very important part of human to human communication. To be able to incorporate emotions into a Human Computer Interaction (HCI) system would greatly improve the quality of the HCI.Much work has been done in the Emotion recognition field. Image filters, feature extraction, feature tracking, movement detection and much more has been studied for use in Facial Expression Recognition. Besides facial expressions, emotion recognition in speech and EEG signals has also been studied extensively. Different techniques for Facial Expression Recognition are explored in this project, including MLP-based and LDA-based classifiers. A Cascading approach to classification is also explored where classifying “easier” emotions first can help to simplify the problem of classifying the “harder” emotions later. The results from these classifiers are comparable with previous works and are viable alternatives to emotion classification. Bachelor of Engineering (Computer Science) 2011-06-02T09:19:23Z 2011-06-02T09:19:23Z 2011 2011 Final Year Project (FYP) http://hdl.handle.net/10356/44642 en Nanyang Technological University 62 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering Ng, Glenn Hong Kiat. Emotion modeling |
description |
Human emotion is a very important part of human to human communication. To be able to incorporate emotions into a Human Computer Interaction (HCI) system would greatly improve the quality of the HCI.Much work has been done in the Emotion recognition field. Image filters, feature extraction,
feature tracking, movement detection and much more has been studied for use in Facial
Expression Recognition. Besides facial expressions, emotion recognition in speech and EEG
signals has also been studied extensively.
Different techniques for Facial Expression Recognition are explored in this project, including
MLP-based and LDA-based classifiers. A Cascading approach to classification is also explored
where classifying “easier” emotions first can help to simplify the problem of classifying the
“harder” emotions later. The results from these classifiers are comparable with previous works
and are viable alternatives to emotion classification. |
author2 |
Quek Hiok Chai |
author_facet |
Quek Hiok Chai Ng, Glenn Hong Kiat. |
format |
Final Year Project |
author |
Ng, Glenn Hong Kiat. |
author_sort |
Ng, Glenn Hong Kiat. |
title |
Emotion modeling |
title_short |
Emotion modeling |
title_full |
Emotion modeling |
title_fullStr |
Emotion modeling |
title_full_unstemmed |
Emotion modeling |
title_sort |
emotion modeling |
publishDate |
2011 |
url |
http://hdl.handle.net/10356/44642 |
_version_ |
1759855272577204224 |