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• W766657370 abstract "Facial expression recognition is to determine the emotional state of the face regardless of its identity. Deriving an effective facial representation from original face images is a vital step for successful facial expression recognition. This paper presents a biological vision-based facial description, called Perceived Facial Images “PFI” applied to facial expression recognition. For the classification step, Scale Invariant Feature Transform “SIFT” is used to extract a local feature in images. Then, a matching computation is processed between a testing image and all train images for recognizing facial expression. To evaluate, the proposed approach is tested on the GEMEP FERA 2011 database and the Cohn-Kanade Facial Expression database. To compare, the developed algorithm achieves better experimental results than the other approaches in the literature." @default.
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• W766657370 date "2013-01-01" @default.
• W766657370 modified "2023-09-27" @default.
• W766657370 title "Facial Expression Recognition Based on Perceived Facial Images and Local Feature Matching" @default.
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• W766657370 doi "https://doi.org/10.1007/978-3-642-41184-7_60" @default.
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