A unified framework for improving the accuracy of all holistic face identification algorithms
Artificial Intelligence Review
Subspace-based holistic registration for low-resolution facial images
EURASIP Journal on Advances in Signal Processing
Discriminant phase component for face recognition
Journal of Electrical and Computer Engineering
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Face recognition accuracy is affected by many factors. This paper studies one of the factors, and provides a reliable image alignment for face recognition. For this purpose, a performance metric is extracted from an analysis of face recognition similarity scores. The metric varies with face alignment, and has a relationship with the actual recognition accuracy. Our method adjusts face alignment online by selecting an alignment candidate corresponding to the largest performance metric. The experimental results show that the presented method can improve the accuracy and robustness of current face recognition systems.