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Sparse representation face identification method based on constrained sampling

A technology of face recognition and sparse representation, which is applied in the field of face recognition, can solve problems such as high requirements for image registration, and achieve the effect of high face recognition rate

Inactive Publication Date: 2012-01-11
JIANGSU TSINGDA VISION TECH
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  • Abstract
  • Description
  • Claims
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Problems solved by technology

[0021] This method is robust to changes in facial illumination and expression, but has high requirements for image registration

Method used

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  • Sparse representation face identification method based on constrained sampling
  • Sparse representation face identification method based on constrained sampling
  • Sparse representation face identification method based on constrained sampling

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Embodiment Construction

[0039] The sparse representation face recognition method based on constrained sampling proposed by the present invention is described in detail in conjunction with the embodiments as follows: the method of this embodiment includes the following steps:

[0040] 1) Feature extraction is performed on all face images in the training set respectively to obtain the feature vectors of the face images in the training set, and the feature vectors of all the face images in the training set are arranged to form a feature matrix A, and one or more rows in the feature matrix As a category of the training set, one category corresponds to multiple face images of a person in the training set;

[0041] 2) Feature extraction is performed on the face image of the person to be recognized to obtain the feature vector y of the image to be recognized;

[0042] 3) the eigenvector of the image to be identified is linearly represented with the eigenvector of the training set image, and the coefficient ...

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Abstract

The invention relates to a sparse representation face identification method based on constrained sampling, belonging to the filed of image processing. The method comprises the following steps: respectively sampling and extracting the features of face images in a training set based on constrained regions to obtain a characteristic matrix one category of which corresponds to a plurality of face images of one person in the training set; sampling and extracting the features of face images of a person to be identified according to the constrained regions to obtain the feature vector of the images to be identified; utilizing the feature vector of the face images in the training set to linearly express the feature vector of the images to be identified; calculating a residual error corresponding to each category in the training set; and utilizing the category of the training set corresponding to the minimum residual error value as the identification result of the person to be identified. The method can sample the constrained regions to ensure higher face identification rate.

Description

technical field [0001] The invention belongs to the technical fields of image processing, computer vision and pattern recognition, and in particular relates to a face recognition method. Background technique [0002] Biometric feature recognition technology is an effective technology for identification, and the fastest growing recently is face recognition technology and biometric feature recognition technology integrated with face recognition technology. [0003] Currently existing face recognition methods mainly recognize the entire face, and among many recognition methods, principal component analysis (PCA-Principal Component Analysis), elastic matching, neural network, geometric features and other methods are mainly used. [0004] At the same time, the difficulty of face recognition lies in: [0005] (1) Face plastic deformation caused by expression [0006] (2) Face diversity caused by posture [0007] (3) Face changes caused by age [0008] (4) The multiplicity of f...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/00G06K9/66G06K9/46
Inventor 苏光大王晶熊英
Owner JIANGSU TSINGDA VISION TECH
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