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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Automatic Facial Expression Recognition Using Modified Wavelet-Based Salient Points and Gabor-Wavelet Filters
verfasst von : Nooshin NabiZadeh, Nigel John
Erschienen in: HCI International 2013 - Posters’ Extended Abstracts
Verlag: Springer Berlin Heidelberg
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In this paper, we present an automated approach for recognizing seven facial expressions including the neutral expression. The approach is based upon efficient feature extraction, feature compression, and an artificial neural network (ANN) classification. In the proposed method, the basic components of face, eyes, eyebrow, and mouth, are first segmented from the whole face using modified Wavelet based salient points. Then, the features of the eye and the mouth are extracted using Gabor-wavelet filters. Afterwards, the dimension of the features is reduced using principal component analysis (PCA). Finally a multi layer perceptron neural network is used to classify the facial expressions. The simulated results show high recognition rate as well as the low computational complexity that makes the proposed algorithm remarkable for accurate and fast facial expression recognition.