Abstract
Facial Recognition is having many challenges along with the application. One of such challenge is facial expression recognition. In this work, feature analysis based hybrid architecture is defined to perform facial expression recognition. The work is divided in two main stags. First to recognize the face itself and later on the recognition of facial expression is performed. In this paper, the feature analysis is performed based on Gabor filter analysis. Once the featured dataset is generated, the recognition is performed using probabilistic neural network and the KPCA approach. The Weighted Eigen distance threshold based analysis is performed to recognize the face as well as the expression. The obtained result shows the accurate detection of face and the expression.
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