Face identification method and system

A face recognition and similarity technology, applied in the field of biometrics, can solve the problems of increased computational complexity and difficulty of similarity learning, and high sample complexity of the difference space method, so as to reduce the sample complexity and improve the face recognition rate , algorithm fast effect

Inactive Publication Date: 2012-09-12
SUZHOU UNIV
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[0005] In view of this, the present invention provides a method and system for face recognition to overcome the problem of increased computat

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  • Face identification method and system
  • Face identification method and system

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[0033] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0034] The invention discloses a method for face recognition. By randomly reducing the dimensionality of test samples and training samples, and generating similarity learning training sets and test sets, selecting regular parameters and Gaussian kernel functions of support vector machines, the similarity The training set of similarity learning is input into the regular parameters and Gaussian kernel function to obtain the classifier model, and then the test set...

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Abstract

The invention discloses a face identification method, which comprises the following steps of: obtaining a classifier model by carrying out random dimension reduction on testing samples and training samples, generating a training set and a testing set of the similarity learning, selecting a regular parameter and a Gaussian kernel function of a support vector machine and inputting the training set of the similarity learning into the regular parameter and the Gaussian kernel function; then inputting the testing set of the similarity learning into the classifier model to obtain classification results; obtaining a sum of the classification results, using the quotient of the sum and the sample number of a certain type of samples as a value of the similarity probability of the type, obtaining the maximum value and outputting the maximum value to obtain the value of the similarity probability so as to obtain the most accurate face identification result. By dimension reduction of the samples, the complexity of the samples is reduced, so that an algorithm of learning the similarity between face images on the basis of the SVM (Support Vector Machine) is rapid; and moreover, by an algorithm of carrying out processing on each type, the face identification rate is correspondingly improved.

Description

technical field [0001] The present invention relates to the technical field of biometric identification, and more specifically, relates to a face recognition method and system. Background technique [0002] In the past few decades, face recognition has developed into a very popular research topic in computer vision, and it is also one of the most successful applications in the field of image analysis. Today, the research on face recognition has great practical significance. Once the research is successful and put into application, it will produce huge social and economic benefits. In the research algorithm of face recognition, it is mainly divided into two categories. One is an image-based face recognition algorithm, and the other is an image-based face recognition algorithm. The image-based face recognition algorithm started earlier, and the technology is relatively mature; the image-based face recognition algorithm is more difficult than the image-based face recognition ...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
Inventor 张莉夏佩佩冷亦琴何书萍王邦军李凡长杨季文
Owner SUZHOU UNIV
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