A method and device for accurately evaluating the degree of facial paralysis based on facial feature points

A technology of facial features and evaluation methods, applied in neural learning methods, instruments, biological neural network models, etc., can solve the problems of low evaluation efficiency and large errors

Active Publication Date: 2021-03-09
SHENZHEN DJ INNOVATION IND CO LTD
View PDF11 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In order to solve the technical problems of large errors and low evaluation efficiency in the existing facial paralysis degree evaluation method, the present invention provides a precise facial paralysis degree evaluation method and device based on facial feature points

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 and device for accurately evaluating the degree of facial paralysis based on facial feature points
  • A method and device for accurately evaluating the degree of facial paralysis based on facial feature points
  • A method and device for accurately evaluating the degree of facial paralysis based on facial feature points

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0075] see figure 1 , the present embodiment provides a method for accurately evaluating the degree of facial paralysis based on facial feature points, which can be applied to facial paralysis detection equipment as a detection method for medical equipment to detect the degree of facial paralysis of patients with facial paralysis, and can be large-scale, Extensive industrial application, for example, it can be used as an independent program in the mobile terminal and client terminal, which can be used for correction and inspection of patients with facial paralysis during the non-treatment period, and can also be used as a preventive method for patients without facial paralysis. Wherein, the accurate facial paralysis evaluation method includes the following steps.

[0076] Step (1): Establish a facial paralysis key point detection model. In this embodiment, the method for establishing the facial paralysis key point detection model includes the following steps, namely steps (1....

Embodiment 2

[0102] see image 3 , this embodiment provides a method for accurately evaluating the degree of facial paralysis based on facial feature points, which is similar to that of Embodiment 1, except that the depth fully convolutional network model of this embodiment is different. The specific structure of the deep full convolutional network model in this embodiment can be designed separately according to the specific requirements of users. For the convenience of further introduction, an example of the structure of a deep full convolutional network model is now designed. image 3 shown. The number of downsampling and upsampling layers of the deep full convolutional network model is 3 layers, and the downsampling adopts maxpooling maximum pooling method. The size of the pooling layer is 2×2 and the step size is 2. The upsampling adopts The dconv deconvolution method, the size of the deconvolution layer is 2×2 and the step size is 2. Each adjacent upsampling or downsampling is separa...

Embodiment 3

[0104] This embodiment provides a device for evaluating the degree of accurate facial paralysis based on facial feature points, which uses the method for evaluating the degree of accurate facial paralysis based on facial feature points in Embodiment 1 or Embodiment 2. Among them, the precise facial paralysis degree evaluation device includes a detection model building module, a data acquisition module, a data processing module and a facial paralysis comprehensive evaluation module. The data acquisition module and the data processing module can form a data acquisition and processing module to be detected. These modules can be used as computer program modules or hardware modules, which can execute the relevant steps described in Embodiment 1 or Embodiment 2.

[0105] The detection model building module is used to set up a facial paralysis key point detection model, which is actually used to implement step (1) in Embodiment 1. In the facial paralysis key point detection model, de...

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 an accurate facial paralysis degree evaluation method and device based on facial feature points. The method includes: establishing a facial paralysis key point detection model; acquiring data to be detected and processing the data to be detected; inputting the expressionless natural state static image, sequence image 1, sequence image 2, sequence image 3 and sequence image 4 in sequence to the facial paralysis key In the point detection model, the corresponding multiple sets of face shapes are output, and multiple sets of face shapes are updated; the degree of facial paralysis of the user to be detected is evaluated: calculate θ 1 , θ 2 , θ 3 , θ 4 , θ 5 , θ 6 , θ 7 , θ 8 , θ 9 , θ 10 And compare with their thresholds respectively; judge the degree of facial paralysis of the user to be detected by comparing the results, and calculate the facial paralysis index. The invention can make the detection model have higher detection and positioning accuracy, greatly improve the comprehensive evaluation and detection accuracy and accuracy of the facial paralysis degree of the user to be detected, and provide strong support for the prevention, discovery and treatment of facial paralysis patients.

Description

technical field [0001] The present invention relates to a method for evaluating the degree of accurate facial paralysis in the technical field of facial paralysis recognition, in particular to a method for evaluating the degree of accurate facial paralysis based on facial feature points, and also to a device for evaluating the degree of accurate facial paralysis based on facial feature points using the method. Background technique [0002] Facial paralysis is a common disease in which the motor function of facial muscles is hindered. Patients often have difficulty in completing basic facial movements such as closing eyes, raising eyebrows, puffing cheeks, wrinkling nose or opening mouth, and it is an area with a high incidence in my country. Facial paralysis is generally called facial paralysis. The general symptom is that the mouth and eyes are crooked. Patients often cannot even complete the most basic movements such as raising eyebrows, closing eyes, and puffing the mouth....

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): G06K9/00G06K9/62G06N3/04G06N3/08
CPCG06N3/084G06V40/161G06V40/168G06N3/045G06F18/214
Inventor 冯少华李伟中李健金波邓利平冼上轩
Owner SHENZHEN DJ INNOVATION IND 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
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