Texture descriptors based affective states recognition- frontal face thermal image

Recognition of human affective states could be achieved through affective computing via various modalities; speech, facial expression, body language, physiological signals etc. In this paper, we present a noninvasive approach for affective states recognition based on frontal face (periorbital, supra...

Full description

Bibliographic Details
Main Authors:	Latif, M. Hafiz, Md Yusof, Hazlina, Sidek, Shahrul Na'im, Rusli, Nazreen
Format:	Conference or Workshop Item
Language:	English English
Published:	Institute of Electrical and Electronics Engineers Inc. 2016
Subjects:	T61 Technical education. Technical schools
Online Access:	http://irep.iium.edu.my/59674/ http://irep.iium.edu.my/59674/ http://irep.iium.edu.my/59674/ http://irep.iium.edu.my/59674/1/59674_Texture%20Descriptors%20Based%20Affective%20States.pdf http://irep.iium.edu.my/59674/2/59674_Texture%20Descriptors%20Based%20Affective%20States_SCOPUS.pdf

id	iium-59674
recordtype	eprints
spelling	iium-596742019-01-10T04:54:37Z http://irep.iium.edu.my/59674/ Texture descriptors based affective states recognition- frontal face thermal image Latif, M. Hafiz Md Yusof, Hazlina Sidek, Shahrul Na'im Rusli, Nazreen T61 Technical education. Technical schools Recognition of human affective states could be achieved through affective computing via various modalities; speech, facial expression, body language, physiological signals etc. In this paper, we present a noninvasive approach for affective states recognition based on frontal face (periorbital, supraorbital, maxillary/nose and mouth region) thermal images. The GLCM features derived from the PCA of the four level decomposition of 2D-DWT (Daubechies-4 Mother wavelet) and LBP features are exploited to provide useful information related to the affective states. The mean classification accuracy of 98.6% was achieved (SVM-Gaussian kernel). The findings of this study endorse the earlier findings; thermal imaging ability to quantify Autonomous Nervous System (ANS) parameters through contactless, nonintrusive and noninvasive manner for affect detection. Institute of Electrical and Electronics Engineers Inc. 2016-12-04 Conference or Workshop Item PeerReviewed application/pdf en http://irep.iium.edu.my/59674/1/59674_Texture%20Descriptors%20Based%20Affective%20States.pdf application/pdf en http://irep.iium.edu.my/59674/2/59674_Texture%20Descriptors%20Based%20Affective%20States_SCOPUS.pdf Latif, M. Hafiz and Md Yusof, Hazlina and Sidek, Shahrul Na'im and Rusli, Nazreen (2016) Texture descriptors based affective states recognition- frontal face thermal image. In: 2016 IEEE-EMBS Conference on Biomedical Engineering and Sciences, IECBES 2016 (IECBES), 4th-8th December 2016, Kuala Lumpur. http://ieeexplore.ieee.org/abstract/document/7843419/ 10.1109/IECBES.2016.7843419
repository_type	Digital Repository
institution_category	Local University
institution	International Islamic University Malaysia
building	IIUM Repository
collection	Online Access
language	English English
topic	T61 Technical education. Technical schools
spellingShingle	T61 Technical education. Technical schools Latif, M. Hafiz Md Yusof, Hazlina Sidek, Shahrul Na'im Rusli, Nazreen Texture descriptors based affective states recognition- frontal face thermal image
description	Recognition of human affective states could be achieved through affective computing via various modalities; speech, facial expression, body language, physiological signals etc. In this paper, we present a noninvasive approach for affective states recognition based on frontal face (periorbital, supraorbital, maxillary/nose and mouth region) thermal images. The GLCM features derived from the PCA of the four level decomposition of 2D-DWT (Daubechies-4 Mother wavelet) and LBP features are exploited to provide useful information related to the affective states. The mean classification accuracy of 98.6% was achieved (SVM-Gaussian kernel). The findings of this study endorse the earlier findings; thermal imaging ability to quantify Autonomous Nervous System (ANS) parameters through contactless, nonintrusive and noninvasive manner for affect detection.
format	Conference or Workshop Item
author	Latif, M. Hafiz Md Yusof, Hazlina Sidek, Shahrul Na'im Rusli, Nazreen
author_facet	Latif, M. Hafiz Md Yusof, Hazlina Sidek, Shahrul Na'im Rusli, Nazreen
author_sort	Latif, M. Hafiz
title	Texture descriptors based affective states recognition- frontal face thermal image
title_short	Texture descriptors based affective states recognition- frontal face thermal image
title_full	Texture descriptors based affective states recognition- frontal face thermal image
title_fullStr	Texture descriptors based affective states recognition- frontal face thermal image
title_full_unstemmed	Texture descriptors based affective states recognition- frontal face thermal image
title_sort	texture descriptors based affective states recognition- frontal face thermal image
publisher	Institute of Electrical and Electronics Engineers Inc.
publishDate	2016
url	http://irep.iium.edu.my/59674/ http://irep.iium.edu.my/59674/ http://irep.iium.edu.my/59674/ http://irep.iium.edu.my/59674/1/59674_Texture%20Descriptors%20Based%20Affective%20States.pdf http://irep.iium.edu.my/59674/2/59674_Texture%20Descriptors%20Based%20Affective%20States_SCOPUS.pdf
first_indexed	2023-09-18T21:24:32Z
last_indexed	2023-09-18T21:24:32Z
_version_	1777412103668236288

Texture descriptors based affective states recognition- frontal face thermal image

Similar Items