Texture descriptors based affective states recognition-frontal face thermal image
| Autor: | Shahrul Na'im Sidek, Md. H. Yusof, M. H. Latif, Nazreen Rusli |
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| Rok vydání: | 2016 |
| Předmět: |
Facial expression
Speech recognition 02 engineering and technology Affect (psychology) Body language Wavelet Kernel (image processing) 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Mouth region Autonomous nervous system Psychology Affective computing |
| Zdroj: | 2016 IEEE EMBS Conference on Biomedical Engineering and Sciences (IECBES). |
| DOI: | 10.1109/iecbes.2016.7843419 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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