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A face recognition method and system based on multi-view canonical correlation analysis

A typical correlation analysis and face recognition technology, applied in the field of face recognition, can solve problems such as poor application effect, unsatisfactory face recognition effect, and unfavorable discovery of multi-view data structure information, etc., to achieve good recognition effect, The effect of reducing the amount of recognition calculation and improving the recognition accuracy

Active Publication Date: 2019-04-12
CHINA UNIV OF PETROLEUM (EAST CHINA)
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Problems solved by technology

[0004] However, the above two methods are still deficient in reflecting finer local structures, which is not conducive to discovering structural information hidden in multi-view data, resulting in unsatisfactory face recognition results and poor practical application results

Method used

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  • A face recognition method and system based on multi-view canonical correlation analysis
  • A face recognition method and system based on multi-view canonical correlation analysis
  • A face recognition method and system based on multi-view canonical correlation analysis

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Embodiment 1

[0048] Embodiment 1. The present invention proposes a face recognition method based on multi-view canonical correlation analysis. Refer to figure 1 , including the following steps:

[0049] S1. Preprocessing the face image used for training to obtain low-dimensional multi-view face image information;

[0050] S2. For the preprocessed face image information, calculate the Hessian matrix of each perspective and the Hessian matrix between any two perspectives; wherein, the Hessian matrix contains local information between multi-view data that is finer than the Laplacian matrix Correlation information is more conducive to discovering structural information hidden in multi-view data;

[0051]S3. Based on the above-mentioned Hessian matrix, calculate the covariance matrix of each viewing angle and between two viewing angles respectively, so that the covariance matrix contains the required local correlation information;

[0052] S4. Construct a projective space model on the basis o...

Embodiment 2

[0067] Embodiment 2. A face recognition system based on multi-view canonical correlation analysis, such as Figure 5 shown, including:

[0068] Image storage module: to obtain face image information, said face image information includes face images for training and face images to be identified;

[0069] Image processing module: use feature vectors to represent the acquired face images;

[0070] Model building module: preprocess the face image used for training in vector representation to obtain low-dimensional multi-view face image information, and then analyze the face image according to the multi-view face image information to obtain the projection space;

[0071] Classification and recognition module: project the multi-view face image information in the obtained projection space, and then classify and recognize the face image to be recognized

[0072] First, the face image information is input to the image storage module, and the face image information includes a face ima...

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Abstract

The present invention relates to a face recognition method and system based on multi-view canonical correlation analysis, which obtains low-frequency subimages by performing low-pass filtering on face images used for training, and uses K-L transform to perform denoising data Dimensionality reduction processing; then calculate the Hessian matrix between each viewing angle and two viewing angles for the preprocessed face image data, generate a multi-view projection space by training the sample image, and perform face recognition by projecting in the space. The present invention obtains multi-view face image information through dimensionality reduction, reduces the amount of recognition calculation, improves recognition accuracy, and the Hessian matrix adopts a higher second-order gradient, which can reflect a finer local structure and is more conducive to discovering hidden The structural information in the multi-view data improves the face recognition effect of the present invention and has high practical application value.

Description

technical field [0001] The invention relates to the technical field of face recognition, in particular to a face recognition method and system based on multi-view canonical correlation analysis. Background technique [0002] With the rapid development of science and technology, and people's constant pursuit of efficient and convenient lifestyles, fast and effective identity verification technology has also received extensive attention, such as in bank monitoring, access control systems, immigration inspection, criminal investigation and many other fields. widely used. There are various biometric features used in identity verification, such as: face recognition, retinal recognition, fingerprint recognition, etc. Among them, face recognition technology has the advantages of low cost, strong concealment, and user-friendliness, and plays an irreplaceable role in identity verification. [0003] The most classic existing multi-view face recognition method is the face recognition...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00
CPCG06V40/172
Inventor 刘伟锋杨兴浩
Owner CHINA UNIV OF PETROLEUM (EAST CHINA)
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