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Face identification method on basis of duplex multi-kernel discriminant analysis of color features

A technology of identification analysis and face recognition, applied in the field of face recognition, can solve the problems of difficult to fully adapt to the nonlinear characteristics of face images and difficult to ensure the recognition effect.

Inactive Publication Date: 2015-06-03
北京大为远达科技发展有限公司
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Problems solved by technology

[0005] CDDA is based on linear technology, it is difficult to fully adapt to the complex nonlinear characteristics of face images (for example, illumination changes, expression changes, posture changes, etc.), so it is difficult to guarantee the recognition effect

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  • Face identification method on basis of duplex multi-kernel discriminant analysis of color features
  • Face identification method on basis of duplex multi-kernel discriminant analysis of color features
  • Face identification method on basis of duplex multi-kernel discriminant analysis of color features

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Embodiment Construction

[0049] Below in conjunction with accompanying drawing and specific embodiment the technical solution of the present invention is described in further detail:

[0050] Nonlinear kernel subspace learning technology can change the distribution of samples through nonlinear kernel mapping, so that samples that are difficult to separate in linear space can be separated in nonlinear kernel space. In addition, considering that there are three color components (which can also be regarded as three spectra) in color face images, in order to cope with the different characteristics of different color components, the multi-kernel subspace learning technology is applied to the dual discriminant analysis of color face features, Three different nonlinear kernel maps are used for the three color components respectively, and then the double discriminant analysis of the feature layer is performed; for the features obtained by the dual multi-kernel discriminant analysis, the nearest neighbor classi...

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Abstract

The invention discloses a face identification method on the basis of duplex multi-kernel discriminant analysis of color features. A multi-kernel subspace learning technology is applied to duplex discriminant analysis of the color face features; three different nonlinear kernel mappings are respectively used for three color components and then feature layer duplex discriminant analysis is carried out. For features acquired by duplex multi-kernel discriminant analysis, a nearest neighbor classifier on the basis of the Euclidean distance measurement is used for classification and identification. According to the face identification method, an identification effect is better and after the features of three color namely R (red), G (green) and B (blue) components are subjected to duplex multi-kernel discriminant analysis, classification capacity of the identifying features is obviously reinforced.

Description

technical field [0001] The invention relates to a face recognition method based on dual multi-core discrimination analysis of color features, belonging to the technical field of face recognition. Background technique [0002] The existing face recognition method (CDDA) (publication number CN103116758A) based on dual discrimination analysis of RGB color features applies linear discrimination analysis technology to the interior of the three color components of R, G, and B and between the three color components. The double discriminant analysis of feature layer based on Euclidean distance is realized within color components and between different color components. The specific method is as follows: [0003] max w R , w G , w B Σ ...

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Application Information

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IPC IPC(8): G06K9/00
Inventor 刘茜
Owner 北京大为远达科技发展有限公司
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