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Method for recognizing human face based on typical correlation analysis spatial super-resolution

A canonical correlation analysis, super-resolution technology, applied in character and pattern recognition, instruments, computer parts, etc., can solve problems such as the complex learning process of objective function parameters, and achieve the effect of enhancing consistency

Inactive Publication Date: 2010-04-21
XI AN JIAOTONG UNIV
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Problems solved by technology

The regularized objective function model proposed by this method can clearly express the restrictions on the super-resolution reconstruction results and recognition results at the same time, but the learning process of the objective function parameters is relatively complicated

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  • Method for recognizing human face based on typical correlation analysis spatial super-resolution
  • Method for recognizing human face based on typical correlation analysis spatial super-resolution
  • Method for recognizing human face based on typical correlation analysis spatial super-resolution

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[0027] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with the accompanying drawings and specific examples. These examples are illustrative only and not restrictive of the invention.

[0028] The face image super-resolution recognition problem can be described as: two corresponding high and low resolution face image training sets I H and I L Or two training sets X of corresponding face image recognition features H and x L , input a low-resolution face image I l , find the recognition feature c of the corresponding high-resolution face image h .

[0029]The theory of manifold learning assumes that the face subspace is an embedded manifold structure, that is, a low-dimensional manifold embedded in a high-dimensional Euclidean space. This indicates that the high-dimensional structure of the face dataset is topologically homeomorphic to a low-dimen...

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Abstract

The invention discloses a method for recognizing human face based on typical correlation analysis spatial super-resolution. Aiming at the problem of the low recognition efficiency of a low-resolution face image, the invention provides a method for obtaining the recognition feature of the low-resolution face image in a high-resolution space by using the super-resolution reconstruction of a recognition feature. Based on a manifold learning theory, the recognition features of the high-resolution and low-resolution face images are considered to be generated by a common internal structure, so the method comprises the following steps: enhancing the consistency of neighborhood relationships of the recognition features of the high-resolution and low-resolution face images by using typical correlation analysis so as to better meet the hypothesis on a neighborhood reconstruction concept; and utilizing neighborhood reconstruction to obtain the recognition feature of the high-resolution face image corresponding to the tested low-resolution face image in a related subspace obtained by the transformation of the typical correlation analysis, and finally utilizing the feature to recognize a face. Experiments show that a recognition rate obtained by the method is less influenced by the resolution of the face image and is relatively higher.

Description

technical field [0001] The invention relates to the field of face recognition, in particular to a low-resolution face recognition method based on canonical correlation analysis space. Background technique [0002] Face recognition technology is of great significance in the security system of today's society. As one of the main research directions in the field of pattern recognition and machine learning, a large number of face recognition algorithms have been proposed. However, due to the limitations of distance and hardware conditions, the resolution of the face images of interest captured in the large-scene video surveillance system is often relatively low, which reduces the performance of face recognition. How to improve the recognition effect under low-resolution conditions is a problem that needs to be solved in face recognition in recent years. [0003] Image super-resolution (Super-resolution, SR) refers to the use of an algorithm to obtain one or a series of high-re...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/46G06K9/62
Inventor 黄华何惠婷
Owner XI AN JIAOTONG UNIV
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