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dc.contributor.authorSong, Kai-Taien_US
dc.contributor.authorLin, Chao-Yuen_US
dc.date.accessioned2017-04-21T06:48:36Z-
dc.date.available2017-04-21T06:48:36Z-
dc.date.issued2014en_US
dc.identifier.isbn978-89-93215-06-9en_US
dc.identifier.issn2093-7121en_US
dc.identifier.urihttp://hdl.handle.net/11536/135282-
dc.description.abstractIn this paper, a temporal-reinforced approach to enhancing emotion recognition from facial images is presented. Shape and texture models of facial images are computed by using active appearance model (AAM), from which facial feature points and geometrical feature values are extracted. The extracted features are used by relevance vector machine (RVM) to recognize emotional states. We propose a temporal analysis approach to recognizing likelihood of emotional categories, such that more subtle emotion, such as degree and ratio of basic emotional states can be obtained. Furthermore, a method is developed to map the recognition result to the arousal-valence plane (A-V Plane). Experimental results verify that the performance of emotion recognition is enhanced by the proposed method.en_US
dc.language.isoen_USen_US
dc.subjectFacial expression recognitionen_US
dc.subjectimage processingen_US
dc.subjectpattern recognitionen_US
dc.titleRobust Facial Emotion Recognition Using a Temporal-Reinforced Approachen_US
dc.typeProceedings Paperen_US
dc.identifier.journal2014 14TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION AND SYSTEMS (ICCAS 2014)en_US
dc.citation.spage804en_US
dc.citation.epage807en_US
dc.contributor.department電控工程研究所zh_TW
dc.contributor.departmentInstitute of Electrical and Control Engineeringen_US
dc.identifier.wosnumberWOS:000392834400160en_US
dc.citation.woscount0en_US
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