Classification of Facial Expression Using Transformed Features
Keywords:
Facial expression, classificationAbstract
Automatic identification of facial expressions
structures the elementary nature of a variety of next generation
computing devices together with sentimental computing
expertise, intellectual tutoring methods, and patient sketch
delicate wellness scrutinize methods etc. Therefore, we have
proposed a facial expression recognition system that has the
aptitude of incrementally learning and thus can learn all
possible patterns of expressions that may be generated in
feature. Proposed system consists of different phases including
face detection, features extraction and classification. First of all,
face detection has been performed by using Voila & Jones
method which is robust and then transformed features has been
extracted for classification using local window. Three types of
features have been extracted using Discrete Cosine Transform,
Haar Wavelet transform, and Gabor Wavelet. Then these
features have been fused and used for classification. The
results of proposed technique are compared using different
quantitative measures with some of the existing techniques
which show its performance.
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