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

A real-time blink detection method based on multi-scale time-series images

A detection method and multi-scale technology, applied in the acquisition/recognition of eyes, instruments, calculations, etc., can solve problems such as poor stability and low accuracy

Active Publication Date: 2021-08-20
HUAZHONG UNIV OF SCI & TECH
View PDF3 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This solves the technical problems of low accuracy and poor stability in the prior art

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 real-time blink detection method based on multi-scale time-series images
  • A real-time blink detection method based on multi-scale time-series images
  • A real-time blink detection method based on multi-scale time-series images

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0050] Step 1, use the video database containing human eyes to establish a database containing time-series images of human eyes, and use the face alignment algorithm to locate the first frame of images in the database in time-series images to obtain the positions of the eyes, including the following steps:

[0051] (1-1) Establish a video database containing human eyes under natural conditions. The video database contains more than 200 time-series images containing human eyes with different frame lengths, and is established using the video database containing human eyes. figure 2 Timing images with blinking behavior shown in (a) and figure 2 (b) Timing images of the blink-free behavior shown;

[0052] In the embodiment of the present invention, the video database containing human eyes is used to establish more than 370 time-series images containing human eyes under natural conditions and about 400 indoors;

[0053] (1-2) If image 3 As shown, the database image is a time-s...

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 real-time blink detection method based on multi-scale time-series images, comprising: positioning the first frame of images in the time-series images to obtain the positions of both eyes; using it to extract human eye images from the first frame of images to obtain human eye Template; use the human eye template to initialize the human eye tracker, use the updated human eye tracker to track the time-series images, obtain the time-series human eye images, and update the human eye tracker to extract the artificial descriptors of the processed time-series human eye images, Then extract the differ feature of the artificial descriptor, and concatenate it with the artificial descriptor to obtain the human eye feature. Encode the human eye features into a blink behavior feature heat map according to the time sequence; then input the blink behavior feature heat map into the LSTM network line by line to obtain multiple hidden states; finally, multiple hidden states are concatenated to obtain multi-scale time series features. Blink detection, to determine whether the time-series images contain blinking behavior. The invention improves the accuracy and stability of blink detection under unconstrained conditions.

Description

technical field [0001] The invention belongs to the technical field of digital image recognition, and more specifically relates to a real-time blink detection method based on multi-scale time-series images. Background technique [0002] With the popularization of various intelligent application devices, it should become a good way of human interaction to reflect the current state of the target by observing the blinking behavior of people, so whether it is living body verification, fatigue driving detection, polygraph detection, etc. There is a great demand. [0003] The current main blink detection algorithms are mainly divided into the following two types: one is to extract the traditional features of a single frame (LBP, HOG, etc.), and then use the classifier (SVM, Adboost, etc.) state; the other is to perform blink detection based on some heuristic rules, such as hough transform to detect pupils, etc. [0004] The above method has the following shortcomings. For the fi...

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
CPCG06V40/193
Inventor 肖阳胡桂雷曹治国孟璐斌熊拂张博深姜文祥王焱乘
Owner HUAZHONG UNIV OF SCI & TECH
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