Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Face data enhancement method based on key point perturbation technology

A key point and key point position technology, applied in the field of face alignment, can solve the problem of insufficient training samples

Active Publication Date: 2018-11-16
SHANGHAI JIAO TONG UNIV
View PDF6 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, this patented technology still does not solve the above-mentioned problem of insufficient training samples

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 data enhancement method based on key point perturbation technology
  • Face data enhancement method based on key point perturbation technology
  • Face data enhancement method based on key point perturbation technology

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0048] The present invention will be described in detail below in conjunction with specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.

[0049] like figure 1 Shown, is the general flow chart of the method of an embodiment of the present invention:

[0050] The first step is to detect key points {P(x, y)} on the image I(x, y) n , and find out the positions of three important key points P 1 (x 1 ,y 1 ), P 2 (x 2 ,y 2 ), P 3 (x 3 ,y 3 ), the specific steps include:

[0051] 1.1) Convert the original color image into a grayscale image I(x, y);

[0052] 1.2) Use the face detection algorithm based on the Viola and Jones frame...

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 a face data enhancement method based on the key point perturbation technology. The method utilizes the face alignment method based on the key point technology of the face first, then disturbs the position of the key point, and then respectively uses linear transformation and affine Transformation, block affine transformation to get a new face picture. The face alignment method based on face key point technology in the present invention performs face alignment with linear transformation, affine transformation, and block affine transformation, and disturbs the position of key points, so that one face picture can generate multiple Pictures of faces. The invention is a method capable of solving the lack of data in the face recognition training process. A plurality of pictures are generated from one face picture, thereby increasing the amount of training and improving the accuracy of face recognition.

Description

technical field [0001] The present invention relates to a face alignment method in the technical field of face recognition, in particular to a face data enhancement method based on key point perturbation technology. Background technique [0002] Face recognition technology is an important branch of computer vision, which has always had high academic research value and broad market application prospects. A complete face recognition system includes the following four technologies: face detection, face alignment, face feature extraction, and face comparison. The face feature extraction is a very critical step in the face recognition system. Commonly used face feature extraction techniques include: single-layer artificial features, two-layer Encoding features, and hierarchical features learned by deep learning methods. Among them, the high-level features obtained by deep learning have stronger descriptive capabilities because they can express more advanced semantic information...

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 Patents(China)
IPC IPC(8): G06K9/00
CPCG06V40/171G06V40/16
Inventor 杨小康晏轶超潘岑蕙徐奕
Owner SHANGHAI JIAO TONG UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap 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