Emotion detection from thermal facial imprint based on GLCM features

Social intelligence in robots has been demonstrated and recognized in numerous contemporary studies especially for Human Robot Interaction (HRI). However, it has become increasingly apparent that social and interactive skills are prerequisites in any application areas and contexts where robots nee...

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Main Authors:	Latif, M. H., Md. Yusof, Hazlina, Sidek, Shahrul Na'im, Rusli, Nazreen, Fatai, Sado
Format:	Article
Language:	English English
Published:	Asian Research Publishing Network (ARPN) 2016
Subjects:	T Technology (General)
Online Access:	http://irep.iium.edu.my/49956/ http://irep.iium.edu.my/49956/ http://irep.iium.edu.my/49956/1/jeas_0116_3343.pdf http://irep.iium.edu.my/49956/4/49956_Emotion%20detection%20from%20thermal%20facial%20imprint_scopus.pdf

id	iium-49956
recordtype	eprints
spelling	iium-499562017-10-10T06:24:54Z http://irep.iium.edu.my/49956/ Emotion detection from thermal facial imprint based on GLCM features Latif, M. H. Md. Yusof, Hazlina Sidek, Shahrul Na'im Rusli, Nazreen Fatai, Sado T Technology (General) Social intelligence in robots has been demonstrated and recognized in numerous contemporary studies especially for Human Robot Interaction (HRI). However, it has become increasingly apparent that social and interactive skills are prerequisites in any application areas and contexts where robots need to interact and collaborate with other robots or humans. The main focus now shifted on how the robots should perceive human affective states and manifest it through action. Recognition of human affective states could be achieved through affective computing by using numerous modalities such as speech, facial expression, body language, physiological signals etc. There are two approaches to access the affective states; invasive and noninvasive. Decades of researches and findings were mostly focussed on the invasive approach; Electroencephalogram (EEG), heart rate, blood flow, Galvanic Skin Response (GSR) etc. When it comes to affect recognition using noninvasive approach, very few numbers of publications have been done to date. In this paper, we presented an efficient method for thermal image feature extraction using the Gray Level Co-occurrence Matrix (GLCM) technique. By analysing the heat pattern on the facial skin, this work attempts to investigate the suitability of the thermal imaging technique for affect detection. The findings of this study indicate thermal imaging as a contactless and noninvasive method for appraising human emotional states. Asian Research Publishing Network (ARPN) 2016-01 Article PeerReviewed application/pdf en http://irep.iium.edu.my/49956/1/jeas_0116_3343.pdf application/pdf en http://irep.iium.edu.my/49956/4/49956_Emotion%20detection%20from%20thermal%20facial%20imprint_scopus.pdf Latif, M. H. and Md. Yusof, Hazlina and Sidek, Shahrul Na'im and Rusli, Nazreen and Fatai, Sado (2016) Emotion detection from thermal facial imprint based on GLCM features. ARPN Journal of Engineering and Applied Sciences, 11 (1). pp. 345-350. ISSN 1819-6608 http://www.arpnjournals.org/jeas/research_papers/rp_2016/jeas_0116_3343.pdf
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	T Technology (General)
spellingShingle	T Technology (General) Latif, M. H. Md. Yusof, Hazlina Sidek, Shahrul Na'im Rusli, Nazreen Fatai, Sado Emotion detection from thermal facial imprint based on GLCM features
description	Social intelligence in robots has been demonstrated and recognized in numerous contemporary studies especially for Human Robot Interaction (HRI). However, it has become increasingly apparent that social and interactive skills are prerequisites in any application areas and contexts where robots need to interact and collaborate with other robots or humans. The main focus now shifted on how the robots should perceive human affective states and manifest it through action. Recognition of human affective states could be achieved through affective computing by using numerous modalities such as speech, facial expression, body language, physiological signals etc. There are two approaches to access the affective states; invasive and noninvasive. Decades of researches and findings were mostly focussed on the invasive approach; Electroencephalogram (EEG), heart rate, blood flow, Galvanic Skin Response (GSR) etc. When it comes to affect recognition using noninvasive approach, very few numbers of publications have been done to date. In this paper, we presented an efficient method for thermal image feature extraction using the Gray Level Co-occurrence Matrix (GLCM) technique. By analysing the heat pattern on the facial skin, this work attempts to investigate the suitability of the thermal imaging technique for affect detection. The findings of this study indicate thermal imaging as a contactless and noninvasive method for appraising human emotional states.
format	Article
author	Latif, M. H. Md. Yusof, Hazlina Sidek, Shahrul Na'im Rusli, Nazreen Fatai, Sado
author_facet	Latif, M. H. Md. Yusof, Hazlina Sidek, Shahrul Na'im Rusli, Nazreen Fatai, Sado
author_sort	Latif, M. H.
title	Emotion detection from thermal facial imprint based on GLCM features
title_short	Emotion detection from thermal facial imprint based on GLCM features
title_full	Emotion detection from thermal facial imprint based on GLCM features
title_fullStr	Emotion detection from thermal facial imprint based on GLCM features
title_full_unstemmed	Emotion detection from thermal facial imprint based on GLCM features
title_sort	emotion detection from thermal facial imprint based on glcm features
publisher	Asian Research Publishing Network (ARPN)
publishDate	2016
url	http://irep.iium.edu.my/49956/ http://irep.iium.edu.my/49956/ http://irep.iium.edu.my/49956/1/jeas_0116_3343.pdf http://irep.iium.edu.my/49956/4/49956_Emotion%20detection%20from%20thermal%20facial%20imprint_scopus.pdf
first_indexed	2023-09-18T21:10:36Z
last_indexed	2023-09-18T21:10:36Z
_version_	1777411226330988544

Emotion detection from thermal facial imprint based on GLCM features

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