Cluster Analytic Detection of Disgust-Arousal
Automated detection of disgust-arousal could have applications in diagnosing and treating obsessive-compulsive disorder and Huntington’s disease. For achieving this ability, experimental data was used first to examine the thermal response of “facial muscles of disgust” to other common negative and p...
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| Format: | Conference Paper |
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IEEE Computer Society
2009
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| Online Access: | http://hdl.handle.net/20.500.11937/16573 |
| _version_ | 1848749215535071232 |
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| author | Khan, Masood Mehmood |
| author2 | TBC |
| author_facet | TBC Khan, Masood Mehmood |
| author_sort | Khan, Masood Mehmood |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Automated detection of disgust-arousal could have applications in diagnosing and treating obsessive-compulsive disorder and Huntington’s disease. For achieving this ability, experimental data was used first to examine the thermal response of “facial muscles of disgust” to other common negative and positive expressions of emotive states. An attempt was then made to detect disgust-arousal through classification of affect-educed thermal variations measured along the facial muscles. Initial results suggest (i) muscles of disgust experience different levels of thermal variations under the influence of various emotive state and (ii) emotion-educed facial thermal patterns can be modeled as stochastically independent clusters to be separated as linear spaces and making automated detection of disgust-arousal possible. |
| first_indexed | 2025-11-14T07:17:24Z |
| format | Conference Paper |
| id | curtin-20.500.11937-16573 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:17:24Z |
| publishDate | 2009 |
| publisher | IEEE Computer Society |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-165732017-09-13T15:43:06Z Cluster Analytic Detection of Disgust-Arousal Khan, Masood Mehmood TBC Psycho-Physiological Information Processing Emotion Assessment Affective Computing Thermal Image Processing Pattern Recognition Automated detection of disgust-arousal could have applications in diagnosing and treating obsessive-compulsive disorder and Huntington’s disease. For achieving this ability, experimental data was used first to examine the thermal response of “facial muscles of disgust” to other common negative and positive expressions of emotive states. An attempt was then made to detect disgust-arousal through classification of affect-educed thermal variations measured along the facial muscles. Initial results suggest (i) muscles of disgust experience different levels of thermal variations under the influence of various emotive state and (ii) emotion-educed facial thermal patterns can be modeled as stochastically independent clusters to be separated as linear spaces and making automated detection of disgust-arousal possible. 2009 Conference Paper http://hdl.handle.net/20.500.11937/16573 10.1109/ISDA.2009.91 IEEE Computer Society restricted |
| spellingShingle | Psycho-Physiological Information Processing Emotion Assessment Affective Computing Thermal Image Processing Pattern Recognition Khan, Masood Mehmood Cluster Analytic Detection of Disgust-Arousal |
| title | Cluster Analytic Detection of Disgust-Arousal |
| title_full | Cluster Analytic Detection of Disgust-Arousal |
| title_fullStr | Cluster Analytic Detection of Disgust-Arousal |
| title_full_unstemmed | Cluster Analytic Detection of Disgust-Arousal |
| title_short | Cluster Analytic Detection of Disgust-Arousal |
| title_sort | cluster analytic detection of disgust-arousal |
| topic | Psycho-Physiological Information Processing Emotion Assessment Affective Computing Thermal Image Processing Pattern Recognition |
| url | http://hdl.handle.net/20.500.11937/16573 |