Face recognizing and aligning method based on shared convolutional characteristic
A technology of face detection and convolution, applied in the field of computer vision, can solve the problems of large amount of calculation of convolutional neural network, non-robustness of abnormal feature points and posture changes, and degradation of face recognition performance, so as to achieve performance improvement , strong robustness, and the effect of avoiding information loss
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[0035] figure 1 The overall processing flow of the face detection and alignment method based on shared convolution features is given, and the present invention is further described below in conjunction with other drawings and specific implementation methods.
[0036] The present invention provides a face detection and alignment method based on shared convolution features. The main steps are as follows:
[0037] 1. Offline training steps
[0038] 1) Face detection
[0039] The first step is to train the face detection part first, and use the stochastic gradient descent method to figure 2The model shown is trained, the initial learning rate α is set to 0.01, and the total number of iterations is 80,000. After 50,000 iterations, the learning rate α is adjusted to 0.1 times the original value every 10,000 iterations. This method of gradually adjusting the learning rate is beneficial to the model. converge to a better solution.
[0040] 2) Facial feature localization
[0041...
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