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

Abstract

The invention discloses a three-dimensional face recognition method and system. The method includes: image data of a to-be-identified target face are collected and a face key point is calibrated, wherein the image data of the face include a depth image of the face and a color image of the face; according to the calibrated depth image of the face, three-dimensional face reconstruction is carried out to obtain a three-dimensional face reconstruction model; surface distances between a preset number of key points in the three-dimensional face reconstruction model are calculated and a surface distance matrix is generated; the surface distance matrix is transformed into a face standard model; a to-be-identified feature vector is extracted from the face standard model; and the to-be-identified feature vector is compared with existing feature vectors in the preset face feature database to realize three-dimensional face recognition. The three-dimensional face recognition method has advantages of 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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