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Texture descriptors based affective states recognition- frontal face thermal image

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.

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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.

Item Type: Conference or Workshop Item (Other)
Additional Information: 4487/59674
Uncontrolled Keywords: frontal face; thermal image; affective states; emotion.
Subjects: T Technology > T Technology (General) > T61 Technical education. Technical schools
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering > Department of Mechatronics Engineering
Depositing User: Dr. Shahrul Naim Sidek
Date Deposited: 29 Nov 2017 16:32
Last Modified: 10 Jan 2019 12:54
URI: http://irep.iium.edu.my/id/eprint/59674

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