Face identification method based on JSM (joint sparsity model) and sparsity preserving projection

A joint sparse and face recognition technology, applied in the field of pattern recognition and biometrics technology, can solve the problem of low recognition rate

Active Publication Date: 2013-08-14
全景智联(武汉)科技有限公司
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Problems solved by technology

[0006] The purpose of the present invention is to provide a face recognition method based on a joint spa

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  • Face identification method based on JSM (joint sparsity model) and sparsity preserving projection
  • Face identification method based on JSM (joint sparsity model) and sparsity preserving projection
  • Face identification method based on JSM (joint sparsity model) and sparsity preserving projection

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Embodiment Construction

[0077] figure 1 The flow chart of the face recognition method based on joint sparse model and sparse preserving mapping proposed by the present invention. The whole process is divided into a training module and a recognition module. The training module mainly preprocesses the training image, and then extracts the public part and the private part of each type of training image, and reconstructs the training sample to make it consistent with the original training sample. When the error reaches the minimum, the dimensionality reduction matrix is ​​calculated; the recognition module preprocesses the unknown test image, and then reconstructs it with the public and private features of each class. The class with the smallest reconstruction error is the class to which the test image belongs.

[0078] combine figure 1 The implementation process of the present invention is described in detail. The embodiments of the present invention are carried out on the premise of the technical sol...

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Abstract

The invention relates to a face identification method based on JSM (joint sparsity models) and sparsity preserving projection. According to the method, a transformation base formed by all training images substitutes a common random matrix in the JSM algorithm; public parts and privacy parts of each type of training face images are extracted by utilizing the JSM algorithm; images in a face database are classified as per people; all images of one person are grouped into the same class; the public parts indicate common face characteristics of each type of face images; the privacy parts indicate detail changes on expressions of faces, illumination and the like; images reconstructed by utilizing sparse public and privacy parts are approximate to original training images; and a dimensionality reduction matrix is obtained through solving the most optimized problem with the smallest reconstruction error. The dimensionality reduction matrix obtained finally performs dimensionality reduction treatment on testing images, the public parts and the privacy parts of each type of training images subjected to dimensionality reduction are used for reconstructing the testing images, and the testing images belong to the class of training images with the smallest reconstruction error.

Description

technical field [0001] The invention belongs to the technical fields of biometric identification technology and pattern recognition, and in particular relates to a method of sparse-preserving mapping and joint sparse model. Background technique [0002] With the development of society, the requirements for fast and effective automatic identity verification in various fields are becoming increasingly urgent, and identity recognition and verification have important application value in the fields of national security, public safety and military security. Due to its strong self-stability and individual differences, biometric identification technology has become the most ideal basis in the field of biometric identification. [0003] In recent years, face recognition as a computer security technology has developed rapidly around the world, and face recognition technology has attracted more and more attention. The application background of face recognition technology is very exte...

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
Inventor 杨新武牛文杰赵晓
Owner 全景智联(武汉)科技有限公司
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