A Survey of Data Uncertainty in Face Recognition
نویسنده
چکیده
The face images are obtained from different pose, facial expression and illumination, hence the a single image of the face occurred the high uncertainty for the face representation. The images of face should not be the fully accurate representation of the face and it is an observation of the face images. To reducing the uncertainty for representation of the face and improving the accuracy of face recognition, more observation of the same person face images is required in the face recognition. In the real world face recognition system the uncertainty highly occurred because the limited number of available face images of subject and due to this there is high uncertainty is occurred. In this paper we develop the model which is to improve the accuracy in the face recognition by reducing the data uncertainty. The model is to reduce the uncertainty of face images representation by synthesizing the virtual training samples. Here we select the useful training samples that are similar to the test sample from the set of all the original training samples and synthesized virtual training sample. Keywords—Computer vision; face recognition; machine learning; uncertainty; face images.
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