Quick human face recognition method based on binocular vision measurement technology

A binocular vision measurement and face recognition technology, applied in the field of face recognition, can solve the problems of slow face recognition and low accuracy

Active Publication Date: 2015-09-16
NORTHEASTERN UNIV
View PDF5 Cites 17 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a fast face recognition method based on binocular vision measurement tec

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
  • Quick human face recognition method based on binocular vision measurement technology
  • Quick human face recognition method based on binocular vision measurement technology
  • Quick human face recognition method based on binocular vision measurement technology

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0064] Embodiment 1 of the present invention: a kind of fast face recognition method based on binocular vision measurement technology, such as figure 1 , figure 2 As shown, it specifically includes the following steps:

[0065] (1) Use a binocular camera to collect face images, and use the Adaboost machine learning algorithm based on haar-like features for face detection to divide the face area;

[0066] (2) Carry out human eye positioning on the face area to obtain the center coordinates of the pupils of the left and right eyes; specifically include: transform the face area to grayscale space, and use the Adaboost machine learning algorithm based on haar-like features to detect the human eye area; Then project the detected human eye area to the X axis and the Y axis respectively, and locate the center coordinates of the left and right eye pupils in the left eye image (x 11 ,y 11 ), (x 12 ,y 12 ), locate the center coordinates of the left and right eye pupils in the righ...

Embodiment 2

[0103] Embodiment 2: a kind of fast face recognition method based on binocular vision measurement technology, such as figure 1 , figure 2 shown, including the following steps:

[0104] (1) Collect the binocular face image and divide the face area;

[0105] (2) Perform human eye positioning on the face area, and obtain the center coordinates of the pupils of the left and right eyes;

[0106] (3) According to the center coordinates of the pupils of the left and right eyes, perform rotation correction on the tilted face image, and obtain the vertical coordinate y′ of the left and right eyes after rotation correction 1 ;

[0107] (4) vertically project the corrected face image, and locate the left and right boundaries of the face;

[0108] (5) Horizontally project the corrected face image, locate the position of the mouth, and obtain the vertical coordinate y′ of the mouth 2 ;

[0109] (6) The vertical coordinate y′ of the left and right eyes after rotation correction accor...

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 quick human face recognition method based on binocular vision measurement technology, which comprises the following steps: effective human face features are extracted in a binocular image, and effective human face regions are divided; the binocular vision measurement technology is then used for carrying out size measurement on extracted human face regions; according to the calculated human face region size, a human face database is divided into multiple human face sub databases; and finally, in a recognition stage, the actually-calculated human face regions are compared with the human face sub databases. Through carrying out comparison recognition on the actually-calculated human face regions and the human face sub databases, the times for comparison recognition are reduced, and the human face recognition speed is greatly enhanced; the actual size of the human face is used for carrying out comparison recognition on the human face sub databases, recognition errors are small, and the human face recognition accuracy rate is effectively improved; and in addition, the human face recognition method also has good universality.

Description

technical field [0001] The invention relates to a fast face recognition method based on binocular vision measurement technology, belonging to the technical field of face recognition. Background technique [0002] Biometric identification has developed rapidly in recent decades. As an inherent attribute of human beings, biological characteristics have strong self-stability and individual differences. Existing biometric technologies include: fingerprint recognition, iris recognition, retina recognition, gait recognition, vein recognition and face recognition, etc. Among them, face recognition has been widely used because of its direct, friendly and convenient features, and is easy to be accepted by users, especially in criminal investigation, security verification system and human-computer interaction, etc., involving computer vision, pattern Recognition, artificial intelligence, digital image processing, neural network, psychology, physiology, mathematics and many other rese...

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
CPCG06V40/162G06V40/169
Inventor 刘志刚赵嘉均
Owner NORTHEASTERN UNIV
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