On the false rejection ratio of face recognition based on automatic detected feature points
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The authors propose a new face recognition system with an evaluation function using feature points. The feature points are detected automatically by Milborrow’s Stasm software. Before recognition, rotation compensation and size normalization are applied to the feature points. The main method is to calculate the squared error between the registered face and the input face as to length of a characteristic pair of feature points on face. The False Rejection Rate (FRR) for the registered and input face of the same person, and the False Acceptance Rate (FAR) for the registered face and a different person’s input face are evaluated. The input is a video sequence. Stable recognition is obtained with small FRR and FAR for the video of a period of 0.5 s.
Keywordsface recognition feature points normalization rotation compensation individual characteristics
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