Face recognition method based on manifold self-adaptive kernel

A face recognition and self-adaptive technology, applied in the field of pattern recognition, can solve the problems of high computational complexity and low result accuracy.

Inactive Publication Date: 2014-07-16
INNER MONGOLIA UNIV OF SCI & TECH
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Problems solved by technology

[0004] The data processing algorithm in the above-mentioned face recognition process is a non-optimized method with high computational complexity and low accuracy of results

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  • Face recognition method based on manifold self-adaptive kernel
  • Face recognition method based on manifold self-adaptive kernel
  • Face recognition method based on manifold self-adaptive kernel

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Embodiment Construction

[0058] Hereinafter, the above-mentioned and other technical features and advantages of the present invention will be described in more detail.

[0059] The concrete process of the face recognition method based on manifold adaptive kernel of the present invention is:

[0060] In step a, the face image is expressed in a vector form by means of a shape-based representation method, that is, X=[x 1 , x 2 ,L,x n ], where x i Indicates the i-th face image;

[0061] Step b, calculate the graph Laplacian operator L;

[0062] Let G denote an undirected graph with n vertices, where i vertices represent face images x i , for each data point x i , find its p nearest neighbor point set N(x i ); if x i is x j p-nearest neighbors or x j is x i The p-nearest neighbors, then build an edge between them, and the edge weight is determined according to formula (1);

[0063] W ij = 1 ...

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Abstract

The invention relates to a face recognition method based on a manifold self-adaptive kernel. The method comprises the specific steps that a face image is represented in a vector mode through a representation method based on the appearance; the graph Laplacian is calculated; a non-parameter kernel matrix K is calculated; the graph Laplacian and the non-parameter kernel matrix K are calculated so that a manifold self-adaptive kernel function tightly related to the face data can be obtained; an optimized objective function of the kernel NMF is constructed, a Lagrange function is built, and a multiplicative updating rule is obtained; the kernel matrix calculation process is achieved through the low rank approximate technology of a Nystrom method; the optimized W and the optimized V are calculated, and for a new tested face image Ztest, low dimensional characteristic representation after the dimension reduction of the kernel NMF is obtained; an optimized objective function of an SVM is built; an optimized solution alpha is calculated. The face recognition accuracy of the manifold self-adaptive kernel is better than that of the existing algorithm, dimension reduction serves as the preprocessing algorithm, and then the performance of the face recognition algorithm is enhanced effectively.

Description

technical field [0001] The invention relates to the field of pattern recognition, in particular to a face recognition method based on a manifold adaptive kernel. Background technique [0002] In the prior art, methods based on global features or subspaces are usually used, the face area is regarded as a whole, and the face is regarded as a certain technical feature as a description feature. [0003] Chinese patent "Face Recognition Method and Face Recognition System", Publication No.: CN101763507A, the face sample image is divided into multiple overlapping sub-regions of different sizes, and the face sample image is preprocessed A face image with a fixed size; extracting the texture features of the sub-regions; selecting effective texture features from the texture features according to preset rules, and obtaining the projection feature values ​​of the effective texture features; according to the projection of each sub-region Eigenvalues ​​for face recognition. [0004] The...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
Inventor 刘新张宝华喻大华陈振华王艳超
Owner INNER MONGOLIA UNIV OF SCI & TECH
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