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

Localized face recognition method

A face recognition and boundary recognition technology, applied in the field of face recognition, can solve problems such as unrealistic, no unified theory of methods, long support vector machine training time, etc., and achieve the effect of simple and easy to implement algorithm

Inactive Publication Date: 2018-09-11
四川意高汇智科技有限公司
View PDF3 Cites 5 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The usual experimental results show that SVM has a better recognition rate, but it requires a large number of training samples (300 per class), which is often unrealistic in practical applications
Moreover, the support vector machine takes a long time to train, and the method is complicated to implement. There is no unified theory for the method of this function.

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
  • Localized face recognition method
  • Localized face recognition method
  • Localized face recognition method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0023] Localized facial recognition method of the present invention comprises the following steps:

[0024] 1. To read the face image data of a person, first, multiple cameras from multiple angles are used to capture the face image of the person;

[0025] 2. Detect the face, and extract the face image of the person by confirming the face attribute of the detected object from the complex background image captured above;

[0026] Extracting the face image of the person includes calculating and identifying its boundary, which includes the following calculation process:

[0027]

[0028] Among them, k mn Represents the gray value of the image pixel (m,n), K=max(k mn ), θ mn ∈[0,1]

[0029] Use the Tr formula to transform the image:

[0030] θ' mn =T r (θ mn ) = T 1 (T r-1 (θ mn )), r=1,2,...

[0031] in

[0032]

[0033] where θ c is the boundary recognition threshold, which is determined by the face boundary recognition experiment, and then the following calcu...

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 provides a localized face recognition method to reduce the complexity of face recognition. According to the method, processing of face recognition data and feature extraction of face texture information can be accurately realized, various defects in the prior art are overcome, and the algorithm is relatively simple and easy to realize.

Description

technical field [0001] The invention belongs to the technical field of face recognition, and in particular relates to a localized face recognition method. Background technique [0002] Face recognition refers specifically to computer technology that uses analysis and comparison. Face recognition is a popular computer technology research field, face tracking detection, automatic adjustment of image magnification, night infrared detection, automatic adjustment of exposure intensity; ) to distinguish individual organisms by their own biological characteristics. [0003] Face recognition technology is based on the facial features of a person, and the input face image or video stream is processed. First judge whether there is a human face, if there is a human face, then further give the position, size and position information of each major facial organ of each face. Based on this information, the identity features contained in each face are further extracted, and compared with...

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): G06K9/00
CPCG06V40/165G06V40/172G06V40/168
Inventor 张悠陈熹
Owner 四川意高汇智科技有限公司
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