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Color face recognition method based on typical correlation multi-kernel learning

A color face, multi-core learning technology, applied in character and pattern recognition, instruments, computer parts and other directions, can solve the problem of difficult to ensure the recognition effect, difficult to fully adapt to the nonlinear characteristics of face images and so on

Active Publication Date: 2017-02-22
NANJING UNIV OF INFORMATION SCI & TECH
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Problems solved by technology

[0007] This method is based on linear canonical correlation analysis technology, and 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

Method used

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  • Color face recognition method based on typical correlation multi-kernel learning
  • Color face recognition method based on typical correlation multi-kernel learning
  • Color face recognition method based on typical correlation multi-kernel learning

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Embodiment Construction

[0034] The technical solution of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0035] The Face Recognition Grand Challenge (FRGC) version 2Experiment4 color face database (P.J.Phillips, P.J.Flynn, T.Scruggs, K.Bowyer, J.Chang, K.Hoffman, J.Marques, J.Min, and W. Worek, "Overview of the Face Recognition Grand Challenge", IEEE Conf. Computer Vision and Pattern Recognition, vol. 1, pp. 947-954, 2005). The database has a large scale and includes three sub-databases: training, target, and query. The training sub-database contains 12,776 pictures of 222 individuals, the target sub-database contains 16,028 pictures of 466 people, and the query sub-database contains 8,014 pictures of 466 people. The experiment selected 222 people from the training sub-library, each with 36 images. All selected original images have been rectified (to make the two eyes in a horizontal position), scaled and cropped, and only a 60×60 size face an...

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Abstract

The invention discloses a color face recognition method based on typical correlation multi-kernel learning, and the method comprises the steps: enabling the multi-kernel learning technology to be used in typical correlation analysis of a color face image, respectively employing three different kernel mapping modes for three color components, and then respectively carrying out the nonlinear feature extraction of the three color components through the typical correlation multi-kernel learning; and carrying out the classification and recognition of the extracted features through employing a nearest neighbor classifier based on the cosine distance. The method is higher in recognition effect, and remarkably improves the classification capability of color face features through the typical correlation multi-kernel learning.

Description

technical field [0001] The invention belongs to the technical field of image processing and pattern recognition, and in particular relates to a color face recognition method based on typical correlation multi-kernel learning. Background technique [0002] Existing "Face Recognition Method Based on Color Image Canonical Correlation Analysis" (CICCA, X.Y.Jing, S.Li, C.Lan, D.Zhang, J.Y.Yang, and Q.Liu, "Color Image Canonical Correlation Analysis for Face Feature Extraction and Recognition", Signal Processing, vol.91, no.8, pp.2132-2140, 2011) by solving the following optimization problem to make the three color component face image data sets canonically correlated: [0003] [0004] [0005] Among them, X, Y, and Z respectively represent three color component face image datasets of R, G, and B, Represent the projection vectors of the three color component face image datasets of R, G, and B respectively. This problem can be transformed into the following three generali...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
CPCG06V40/172
Inventor 刘茜荆晓远
Owner NANJING UNIV OF INFORMATION SCI & TECH
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