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Identification of Facial Gestures using Principal Component Analysis and Minimum Distance Classifier

recognition has been one of the most active fields of research for the last couple of decades and vision enthusiasts have proposed many ways to identify and recognize correctly a person from the image of his face. Here we propose an algorithm which not only detects the person's face but also identifies the expression or gesture on his face. The method at first detects the face region from a 2-dimensional image of a given person and then are projected on the "Face Space" which is the feature space containing the Eigen Vectors of the face images. The face template that has the minimum distance from the test image is evaluated as the best match and the expression label it possesses is therefore taken as the required expression of the test image.