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Acquisition method and detection method of living body face detection head posture regression device

A head posture and face detection technology, applied in the field of image recognition, can solve the problems of non-interactive, unpublished regressor for posture regression, poor anti-attack ability, etc., to improve the accuracy and scientificity, and increase the success rate , the effect of improving speed and accuracy

Inactive Publication Date: 2019-12-03
HUAIBEI NORMAL UNIVERSITY
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  • Summary
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Moreover, most face detection schemes are based on direct extraction of face image information, without interactivity, and poor anti-attack capabilities, such as photos, videos, and model camouflage, which put forward requirements for live face detection. There are mature human face detection methods, and the regressor for posture regression in face recognition has not been disclosed. Therefore, the present invention proposes a method for obtaining and detecting a head posture regressor for live human face detection to solve the current problem. There are deficiencies in the technology

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  • Acquisition method and detection method of living body face detection head posture regression device
  • Acquisition method and detection method of living body face detection head posture regression device
  • Acquisition method and detection method of living body face detection head posture regression device

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Embodiment 1

[0047] according to figure 1 , 2 As shown, the present embodiment proposes a method for obtaining a head pose regressor for live face detection, including the following steps:

[0048] A. Obtain face two-dimensional model data, face three-dimensional model data and iris data, and then perform screening processing on the acquired face two-dimensional model data, face three-dimensional model data and iris data, and remove the face two-dimensional model data , The low resolution and repeated data in the face 3D model data, remove the damaged data in the iris data;

[0049] B. Select a certain number of feature points in the two-dimensional model data of the face, then select the same feature points in the three-dimensional model data of the face, and map the feature points, and then form the three-dimensional model data of the face with composite standardization, and then Normalize the face three-dimensional model data with compound standardization, take the distance and direct...

Embodiment 2

[0062] according to image 3 As shown, a kind of live human face detection method based on the head pose regressor of the present embodiment comprises the following steps:

[0063] H. Obtain the image of the head posture made by the user according to the instructions issued by the terminal, including two-dimensional images and three-dimensional images, and then use the iris data collected by the iris collection device;

[0064] 1, according to described two-dimensional image and three-dimensional image and iris data, obtain face frame by adaboost algorithm;

[0065] G, locate the face feature point coordinates in the face frame by a supervised gradient descent method;

[0066] K, carry out centralization and normalization process with described face feature point;

[0067] L. According to the processed feature point data, the head angle is obtained by the head posture regressor; when it is judged that the obtained head angle value is within the preset threshold, the recognit...

Embodiment 3

[0082] according to Figure 4 As shown, a kind of live face detection method of the present embodiment comprises the following steps:

[0083] M. Acquiring two-dimensional images and three-dimensional images of facial expressions made by users according to terminal instructions, as well as iris data collected by iris collection equipment;

[0084] N, according to described two-dimensional image, three-dimensional image and iris data, obtain face frame by adaboost algorithm;

[0085] O, locate the facial feature point coordinates in the described human face frame by a supervised gradient descent method;

[0086] P. Perform linear transformation on the located feature points; when it is judged that the feature information value of the linearly transformed feature points is within the preset feature threshold range, the recognition is successful.

[0087] The beneficial effects of the present invention are: by constructing a high-precision head posture regressor, and by adoptin...

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Abstract

The invention discloses an acquisition method and detection method of living body face detection head posture regression device, and the method comprises the steps: obtaining face data, and forming face three-dimensional model data with composite standardization; obtaining a training sample set; acquiring a corresponding Euler angle and a rotation matrix containing a corresponding relationship between each two-dimensional coordinate plane and the corresponding Euler angle by using the acquired two-dimensional coordinate plane set formed by the two-dimensional coordinates of the feature points;obtaining a head posture regression device. According to the invention, a high-precision head posture regression device is constructed. Corresponding earlier-stage processing is carried out on the human face two-dimensional model data, the human face three-dimensional model data and the iris data. The invention has the following beneficial effects: human faces are effectively recognized, therebymaking data more accurate and robust; and the success rate of face living body detection is improved.

Description

technical field [0001] The invention relates to image recognition technology, in particular to an acquisition method and a detection method of a head pose regressor for detection of living human faces. Background technique [0002] With the advent of the era of big data, the problem of personal information security has become increasingly severe, and face recognition and detection technology based on image processing has been widely used. However, the current face detection technology is aimed at a small number of face images. With the deepening of the concept of big data, image big data processing will put forward higher requirements for face detection technology. Moreover, most face detection schemes are based on direct extraction of face image information, without interactivity, and poor anti-attack capabilities, such as photos, videos, and model camouflage, which put forward requirements for live face detection. There are mature human face detection methods, and the reg...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/32G06K9/62G06T3/60
CPCG06T3/60G06V20/64G06V40/166G06V40/168G06V40/18G06V40/45G06V10/25G06F18/285G06F18/214
Inventor 张琪
Owner HUAIBEI NORMAL UNIVERSITY
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