Eureka AIR delivers breakthrough ideas for toughest innovation challenges, trusted by R&D personnel around the world.

A method for automatically updating data of a training image library for face recognition

A technology for training images and face recognition, applied in the field of face recognition, it can solve the problems that the model prediction accuracy and prediction speed cannot be maximized, and achieve data security problems, recognition speed and accuracy guarantee, and efficacy. high effect

Active Publication Date: 2018-12-11
NANJING KIWI NETWORK TECH CO LTD
View PDF3 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to the above limitations of these data, the existing models cannot be maximized in terms of prediction accuracy and prediction speed.

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
  • A method for automatically updating data of a training image library for face recognition
  • A method for automatically updating data of a training image library for face recognition
  • A method for automatically updating data of a training image library for face recognition

Examples

Experimental program
Comparison scheme
Effect test

Embodiment

[0026] The method for automatically updating data of the training image library for face recognition of the present embodiment comprises the following steps:

[0027] Step 1. Get image data

[0028] Use crawler technology to automatically obtain facial image data on the Internet according to preset rules. Crawler technology is an existing technology, which is a program or script that automatically obtains information on the Internet according to certain rules. The principle is to obtain the source code field information of the part we need by intercepting the source code on the web page. In this embodiment, the face picture is the information we need, we find the feature code corresponding to the picture in the source code of the web page, such as the line containing the words 'image' and 'face', as the object we need, intercept it. Of course, other feature codes can also be selected.

[0029] Step 2. Filter face image data

[0030] In the new image data obtained by the c...

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 relates to a method for automatically updating data of a training image library for face recognition. The method comprises the following steps: step 1, acquiring face picture data by using crawler technology; step 2, judging that face angle in the picture by using the three-dimensional pose angle, and filtering out the picture with too large deviation from the positive face; step 3,extracting five feature points in the picture by using the MTCNN technology, and carrying out affine transformation between the five feature points and the initially set five feature points, so as toachieve the effect of face alignment; step 4, automatically adding the face aligned picture data to the training image library. The method improves the richness and accuracy of the training data in the face recognition training process, ensures the training accuracy and training speed of the deep neural network model, and shortens the training period of the deep neural network model.

Description

technical field [0001] The invention relates to a method for automatically updating data of a training image library for face recognition, belonging to the technical field of face recognition. Background technique [0002] In the face recognition technology based on the deep neural network model, the acquisition of image data plays a decisive role in the model training. For our existing high-accuracy and efficient models, a batch of high-quality data is required as input to maximize the effectiveness of the model. At the same time, we also need the database itself to have strong anti-interference capabilities, as well as automatic update and filtering capabilities, to cope with the current explosion of data and information in the field of artificial intelligence. [0003] The data used for face recognition in the prior art basically comes from online public data sets or existing data, and these data cannot be automatically updated after acquisition. In addition, most of th...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06T7/00G06K9/00G06F17/30
CPCG06T7/0002G06T2207/30168G06T2207/30201G06V40/168G06V40/50
Inventor 杨通彭若波杜曦
Owner NANJING KIWI NETWORK 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
Eureka Blog
Learn More
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com