Publication | Closed Access
Human emotion recognition from facial thermal image based on fused statistical feature and multi-class SVM
46
Citations
17
References
2015
Year
Unknown Venue
EngineeringBiometricsFacial Thermal ImageSocial SciencesFace DetectionSupport Vector MachineFacial Recognition SystemImage AnalysisData SciencePattern RecognitionAffective ComputingThermal ImageComputer ScienceStatistical Pattern RecognitionHuman Emotion RecognitionComputer VisionFused Statistical FeatureFacial Expression RecognitionEmotionEmotion Recognition
Affective computing has become a growing field of research activities due to its wide use of application in human computer interface. Emotion recognition is one of the state-of-the-art techniques in determining current psychological state of human being. Human emotions are very overlapping in nature and thus it needs an efficient feature-extractor and classifier assembly. This paper reports a novel non-invasive technique to classify human emotion through thermal images of face. Hu's moment invariants of different patches have been fused with histogram statistical feature and used as robust features in multiclass support vector machine based classification. It is found that emotions from thermal image can be classified by the proposed method with a satisfactory performance.
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