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...
| Main Authors: | , , , |
|---|---|
| Format: | Proceeding Paper |
| Language: | English English |
| Published: |
Institute of Electrical and Electronics Engineers Inc.
2016
|
| Subjects: | |
| Online Access: | 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 |
| _version_ | 1848785351343079424 |
|---|---|
| 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 |
| building | IIUM Repository |
| collection | Online Access |
| 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. |
| first_indexed | 2025-11-14T16:51:46Z |
| format | Proceeding Paper |
| id | iium-59674 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T16:51:46Z |
| publishDate | 2016 |
| publisher | Institute of Electrical and Electronics Engineers Inc. |
| recordtype | eprints |
| repository_type | Digital Repository |
| 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 Proceeding Paper 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 |
| 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 |
| title | 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_short | Texture descriptors based affective states recognition- frontal face thermal image |
| title_sort | texture descriptors based affective states recognition- frontal face thermal image |
| topic | T61 Technical education. Technical schools |
| 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 |