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Face recognition method based on 3D imaging and terminal
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A face recognition and 3D technology, which is applied in the face recognition and terminal field based on 3D imaging, can solve the problems of poor face recognition accuracy and narrow application fields, and achieve accurate identity, multiple application environments, and various types Effect
Inactive Publication Date: 2018-06-22
UNRE SHANGHAI INFORMATION TECH CO LTD
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[0005] The technical problem to be solved by the present invention is to overcome the defects of poor recognition accuracy and narrow application field of face recognition in the prior art, and provide a more accurate 3D-based recognition image with more types of recognition images and a wider recognition surface. Imaging face recognition method and terminal
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Embodiment 1
[0047] This embodiment provides a face recognition terminal, and the face recognition terminal may be a mobile phone, an access controlsystem, or a computer connected to monitoring.
[0048] Through the face recognition terminal, the user can identify the identity of the avatar in the target image, or judge whether the avatar is a legal person, etc.
[0049] The face recognition terminal includes an acquisition module, a generation module, a recognition module, a processing module, a comparison module, a judgment module, a projection module, a calculation module and a coverage module.
[0050] The obtaining module is used to obtain the 3D model of the avatar.
[0051] The generation module is used to obtain three-dimensional feature points on the 3D model.
[0052] The three-dimensional feature points include feature points on the ear contour, nose feature points, eye feature points, mouth feature points, head contour feature points and hairline contour feature points.
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Embodiment 2
[0079] This embodiment is basically the same as Embodiment 1, the only difference is:
[0080] The target feature points are three-dimensional feature points, and the face recognition terminal further includes an execution module,
[0081] The execution module is used to connect the 3D model and the three-dimensional feature points of the target image in pairs to obtain the connection line;
[0082] The comparison module is used to compare the length ratio and angle formed by adjacent connecting lines of the 3D model with the length ratios and angles formed by corresponding adjacent connecting lines in the target image to obtain the similarity value.
[0083] see figure 2 , the face recognition method of this embodiment replaces step 104 of Embodiment 1 with:
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Abstract
The invention discloses a face recognition method based on 3D imaging and a terminal. The face recognition method comprises the steps that a 3D model of an icon is acquired; three-dimensional featurepoints are acquired from the 3D model; a skin and hair area is recognized on the icon of a target image; target feature points corresponding to the three-dimensional feature points in position are acquired from the skin and hair area; the three-dimensional feature points and the target feature points are compared to acquire a similarity value of the icon in the target image; and the identity of the icon in the target image is judged according to the similarity value. Through the face recognition method and the terminal, recognition of the identity in the image is more accurate, more types of recognition images are available, the recognition range is wider, and more application environments are available for identity recognition.
Description
technical field [0001] The invention relates to a face recognition method and terminal based on 3D imaging. Background technique [0002] Face recognition is a biometric technology for identification based on human facial feature information. A series of related technologies that use a video camera or camera to collect images or video streams containing human faces, automatically detect and track human faces in the images, and then perform facial recognition on the detected faces, usually also called portrait recognition and facial recognition. [0003] The research on the face recognition system began in the 1960s. After the 1980s, it was improved with the development of computer technology and optical imaging technology, and it really entered the primary application stage in the late 1990s. Technology implementation is the main focus; the key to the success of the face recognition system is whether it has a cutting-edge core algorithm, and the recognition result has a pra...
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