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Face identification method based on multi-sample expansion cooperation expression classification

A technology of collaborative representation and face recognition, applied in the field of image processing, can solve the problems of heavy workload and complex operation, and achieve the effect of improving the effect and improving the face recognition rate.

Active Publication Date: 2018-01-09
NANJING UNIV OF INFORMATION SCI & TECH
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  • Claims
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Problems solved by technology

However, since the sparse recognition method is a recognition method based on the L_1 norm, the process of face recognition using the traditional sparse recognition method is complex and requires a lot of work.

Method used

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  • Face identification method based on multi-sample expansion cooperation expression classification
  • Face identification method based on multi-sample expansion cooperation expression classification
  • Face identification method based on multi-sample expansion cooperation expression classification

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Embodiment Construction

[0028] The specific implementation of the face recognition method based on multi-sample extended cooperative representation classification provided by the present invention will be described in detail below in conjunction with the accompanying drawings.

[0029] This specific embodiment provides a face recognition method based on multi-sample extended collaborative representation classification, with figure 1 It is a flow chart of a face recognition method based on multi-sample extended cooperative representation classification according to a specific embodiment of the present invention. Such as figure 1 As shown, the face recognition method based on multi-sample extended collaborative representation classification provided in this specific embodiment includes the following steps:

[0030] Step 1: The mirror image method utilizes the symmetry of the image to obtain a mirror image; if the face database has t classes, each class has n training samples, and the total number of t...

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Abstract

The invention provides a face identification method based on multi-sample expansion cooperation expression classification; the method comprises the following steps: creating a mirror image face imageon the image mirror surface property basis; preparing two random original samples and mirror image samples of the same type, and using smooth median samples of said samples so as to build a novel virtual sample; using the European style distance to select training samples approaching to test samples. The method can carry out parameter weight fusing for training samples formed in different paths, can identify faces according to a classification method based on cooperation expressions, can create various virtual training samples, and can simplify the operation complexity, thus improving the faceidentification effect.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a face recognition method based on multi-sample extended cooperative representation classification. Background technique [0002] With the rapid development of artificial intelligence technology, face recognition technology has matured in the fields of identity confirmation, identification, security monitoring, and human-computer interaction, and has been widely used in production and life. And as online shopping is increasingly integrated into people's lives, face recognition payment technology will have broad application prospects. [0003] Limited face samples cannot meet the needs of face recognition in real life. Some scholars have used the symmetry and noise of images to construct new virtual samples. However, in real life, human faces are often affected by uncertain factors such as lighting, showing complex and diverse characteristics, so the constructed virtual ...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06K9/62
Inventor 周先春许瑞周陈栋仁
Owner NANJING UNIV OF INFORMATION SCI & TECH
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