Three-dimensional human face recognition method based on human face full-automatic positioning

Abstract

The present invention discloses a three-dimensional human face identifying method based on human face full-automatic positioning and belongs to the computer vision and mode identifying field. A human face virtual image generating method comprises the steps as follows: a two-dimensional human face shape model and a partial veins model are established; a two-dimensional human face image is positioned exactly; the two-dimensional human face image is processed for three-dimensional reconstruction according to the positioning result to obtain a three-dimensional human face image; the three-dimensional human face image is processed for illumination model treatment to obtain a virtual image with changeable gestures and illumination. The method comprises the steps as follows: characteristics are picked up from the human face image to be identified and compressed; the human face is identified according to the compressed and processed characteristics. The present invention embodiment generates the virtual image by the three-dimension reconstructing of the two-dimensional human face image and by processing the illumination model, thereby increasing the sample space of the gesture and the illumination change of the image; at the same time, the three-dimension reconstructing speed is improved greatly, thereby ensuring that human face image identification has higher efficiency and recognition rate.

Description

technical field [0001] The invention relates to the fields of computer vision and pattern recognition, in particular to a three-dimensional face recognition method based on full-automatic face positioning. Background technique [0002] The face recognition system takes face recognition technology as the core. It is an emerging biometric technology and a high-tech technology in the international scientific and technological field. Face recognition system has a wide range of applications due to its non-reproducibility, convenient collection, and no need for the cooperation of the person being photographed. [0003] Although face recognition has been studied for decades, it remains a challenging problem in the field of pattern recognition even today. There are still a series of difficult problems in the face recognition method. For example, when the face posture, expression and ambient lighting (PIE, Pose Illumination Expression) change greatly, the recognition rate will drop ...

AI Technical Summary

Problems solved by technology

[0007] However, there are also many shortcomings in the existing technology. The main disadvantage of the attitude-invariant feature extraction method is that it is difficult to extract the attitude-invariant features; Absolutely divided, and the wrong pose estimation will reduce the performance of face recognition; while the method based on the 3D model of the face, although it can solve the pose problem better, there are still many difficulties, such as large amount of calculation, slow speed and recovery accuracy Poor, and requires manual positioning of feature points for initialization

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