Face authentication method and device

A face and face image technology, applied in the field of face authentication, can solve the problems of insufficient feature processing and understanding at all levels, insufficient description of images, gradient dispersion of deep networks, etc., to make up for the insufficient description of high-level features. Image defects, avoid gradient dispersion problems, and increase the effect of image feature richness

Active Publication Date: 2015-12-09
BEIJING EYECOOL TECH CO LTD +1
View PDF6 Cites 34 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The method of feature extraction is: manually design a feature vector, and extract the specified feature vector through various algorithms, such as face authentication methods based on geometric features, face authentication methods based on subspace, and face authentication methods based on signal processing. etc., but this method is extremely susceptible to the influence of lighting, expression and other factors on the results, and has poor anti-interference

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Face authentication method and device
  • Face authentication method and device
  • Face authentication method and device

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0034] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will describe in detail with reference to the drawings and specific embodiments.

[0035] On the one hand, the present invention is a method for face authentication, such as figure 1 shown, including:

[0036] Step S101: Using the multi-level deep convolutional network that has been jointly trained by the multi-layer classification network in advance to extract the feature vectors of multiple levels sequentially from the face image and the face image template to be authenticated;

[0037] The multi-level deep convolutional network includes more than two convolutional networks, and each convolutional network includes convolution, activation, and downsampling operations. The order and number of these operations are not fixed and are determined according to actual conditions; each volume of the present invention Each product network extr...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses face authentication method and device, and belongs to the field of biological recognition. The method comprises the following steps: sequentially extracting multiple levels of feature vectors from a to-be-authenticated face image and a face image template with a multi-level depth convolutional network which is subjected to multi-layer classified network joint training in advance; sequentially mapping the multiple levels of feature vectors into unified dimension feature vectors through a unified dimension linear mapping matrix; connecting the unified dimension feature vectors into joint feature vectors in series; carrying out dimension-reducing mapping on the joint feature vectors through a linear dimension-reducing mapping matrix; and normalizing cosine values with absolute values through linear discriminant analysis, and carrying out comparison and authentication on the obtained comprehensive feature vectors of the to-be-authenticated face image and comprehensive feature vectors of the face image template. Compared with the prior art, the face authentication method disclosed by the invention is high in anti-jamming capability, good in expandability and high in authentication accuracy rate.

Description

technical field [0001] The invention relates to the field of biometric identification, in particular to a method and device for face authentication. Background technique [0002] Face authentication is a form of biometric identification. By effectively characterizing the face, the features of two face pictures are obtained, and a classification algorithm is used to determine whether the two pictures are the same person. Generally, a face image is pre-stored in the face recognition device as a face image template; during authentication, a face image is taken as a face image to be authenticated, the features of the two images are extracted, and classification algorithms are used to Determine if the two photos are of the same person. [0003] The method of feature extraction is: manually design a feature vector, and extract the specified feature vector through various algorithms, such as face authentication methods based on geometric features, face authentication methods based...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06K9/00
CPCG06V40/16
Inventor 郇淑雯毛秀萍张伟琳朱和贵
Owner BEIJING EYECOOL TECH CO LTD
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap