Three-dimensional face recognition method and three-dimensional face recognition system

Abstract

The invention discloses a three-dimensional face recognition method and system. Including: collecting the image data of the target face to be recognized, and calibrating the key points of the face, wherein the image data of the face includes the depth image of the face and the color image of the face; performing three-dimensional face reconstruction on the depth image of the face to obtain a three-dimensional face reconstruction model; calculating the surface distances between a preset number of key points in the three-dimensional face reconstruction model to generate a surface distance matrix; The surface distance matrix is ​​converted into a face standard type; the feature vector to be identified is extracted from the face standard type; the feature vector to be identified is compared with the existing feature vector in the preset face feature database to realize three-dimensional face recognition. The three-dimensional face recognition method of the invention has high recognition accuracy and fast recognition speed.

Description

technical field [0001] The invention relates to the technical field of face recognition, in particular to a three-dimensional face recognition method and a three-dimensional face recognition system. Background technique [0002] Today, face recognition technology has become a widely used intelligent biometric technology. From toilet paper, red light capture, entry-exit security check, financial payment and other fields, face recognition technology can be found everywhere. [0003] Existing face recognition technologies are mainly divided into two categories: two-dimensional face recognition and three-dimensional face recognition. The two-dimensional face recognition algorithm usually recognizes the RGB image captured by the color camera. After the target face is detected from the image, it is input into the most popular deep learning model through a series of processing operations such as calibration and alignment. (mainly convolutional neural network), and output a vector ...

AI Technical Summary

Problems solved by technology

[0006] In the current face recognition algorithm, the two-dimensional face recognition algorithm performs face recognition based on RGB color images. When the head rotation angle is too large, the accuracy of the algorithm will be greatly reduced. In addition, the two-dimensional Recognition algorithms are hard to resist deceptive attacks from photos and videos

Although the existing 3D face recognition algorithm can use the depth image collected by the depth-of-field camera to simulate and model the face, and then recognize it, it solves the problems of large-angle head rotation and living body detection, but usually runs at a slow speed. Difficult to apply

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