Thermal imaging-based human emotion detection: GLCM feature extraction approach
Abstract—Recent studies in artificial intelligence and robotics had proved the ability of social intelligence in robots. However, it has become increasingly apparent that social and interactive skills are necessary requirements in any application areas and contexts where robots need to interact...
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University of Derby
2015
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Online Access: | http://irep.iium.edu.my/62247/1/IJRM%20Bali%20paper.pdf http://irep.iium.edu.my/62247/ http://ojs.unsysdigital.com/index.php/ijrm/article/view/879 |
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my.iium.irep.622472018-03-02T04:18:52Z http://irep.iium.edu.my/62247/ Thermal imaging-based human emotion detection: GLCM feature extraction approach Md Yusof, Hazlina T10.5 Communication of technical information Abstract—Recent studies in artificial intelligence and robotics had proved the ability of social intelligence in robots. However, it has become increasingly apparent that social and interactive skills are necessary requirements in any application areas and contexts where robots need to interact and collaborate with other robots or humans. In order to develop an emotionally intelligent robot, the issues on how to perceive human affective states and how to manifest the robot’s emotion should be addressed. 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 attempt to investigate the suitability of the thermal imaging technique for affect detection. The findings of this study indicate thermal imaging as an alternative, contactless and noninvasive method for appraising human emotional states. University of Derby 2015 Article REM application/pdf en http://irep.iium.edu.my/62247/1/IJRM%20Bali%20paper.pdf Md Yusof, Hazlina (2015) Thermal imaging-based human emotion detection: GLCM feature extraction approach. International Journal of Robotics and Mechatronics, 2 (3). pp. 1-7. ISSN 2508-4127 http://ojs.unsysdigital.com/index.php/ijrm/article/view/879 |
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T10.5 Communication of technical information Md Yusof, Hazlina Thermal imaging-based human emotion detection: GLCM feature extraction approach |
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Abstract—Recent studies in artificial intelligence and robotics had
proved the ability of social intelligence in robots. However, it has
become increasingly apparent that social and interactive skills are
necessary requirements in any application areas and contexts where
robots need to interact and collaborate with other robots or humans. In
order to develop an emotionally intelligent robot, the issues on how to
perceive human affective states and how to manifest the robot’s
emotion should be addressed. 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 attempt to investigate the
suitability of the thermal imaging technique for affect detection. The
findings of this study indicate thermal imaging as an alternative,
contactless and noninvasive method for appraising human emotional
states. |
format |
Article |
author |
Md Yusof, Hazlina |
author_facet |
Md Yusof, Hazlina |
author_sort |
Md Yusof, Hazlina |
title |
Thermal imaging-based human emotion detection: GLCM feature extraction approach |
title_short |
Thermal imaging-based human emotion detection: GLCM feature extraction approach |
title_full |
Thermal imaging-based human emotion detection: GLCM feature extraction approach |
title_fullStr |
Thermal imaging-based human emotion detection: GLCM feature extraction approach |
title_full_unstemmed |
Thermal imaging-based human emotion detection: GLCM feature extraction approach |
title_sort |
thermal imaging-based human emotion detection: glcm feature extraction approach |
publisher |
University of Derby |
publishDate |
2015 |
url |
http://irep.iium.edu.my/62247/1/IJRM%20Bali%20paper.pdf http://irep.iium.edu.my/62247/ http://ojs.unsysdigital.com/index.php/ijrm/article/view/879 |
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1643616137938731008 |
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13.211869 |