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dc.contributor.authorNor Surayahani, B. S.
dc.contributor.authorHermila, M. A.
dc.date.accessioned2010-08-12T03:36:01Z
dc.date.available2010-08-12T03:36:01Z
dc.date.issued2009-06-20
dc.identifier.citationp.1-4en_US
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/8609
dc.descriptionMUCEET 2009 is organized by Malaysian Technical Universities Network (MTUN) comprising of Universiti Malaysia Perlis (UniMAP), Universiti Tun Hussein Onn (UTHM), Universiti Teknikal Melaka (UTeM) and Universiti Malaysia Pahang (UMP), 20th - 22nd June 2009 at M. S. Garden Hotel, Kuantan, Pahang.en_US
dc.description.abstractThis paper describes the emotion recognition to determine the driver’s conditions. The emotion recognition could be envisioned to sense the driver emotions automatically through a camera. Therefore, facial images were analyzed to extract the features to characterize the variations between facial emotions images. The features extraction techniques apply was Principal Component Analysis (PCA), this algorithm finds the principle components of the covariance matrix of a set of face images. Then, the eigenvalues component will be used as an input to the KNearest Neighbor (KNN) classifier. The facial expression recognition used to investigate the emotion and thus carry out an awareness system for drivers to perform an appropriate intervention system.en_US
dc.language.isoenen_US
dc.publisherUniversiti Malaysia Pahang (UMP)en_US
dc.relation.ispartofseriesProceedings of the Malaysian Technical Universities Conference on Engineering and Technology (MUCEET) 2009en_US
dc.subjectEmotions recognitionen_US
dc.subjectPrincipal Component Analysis (PCA)en_US
dc.subjectMalaysian Technical Universities Conference on Engineering and Technology (MUCEET)en_US
dc.titleClassifying driver facial emotionsen_US
dc.typeWorking Paperen_US


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