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Precise facial paralysis degree evaluation method and device based on semantic segmentation

A technology of semantic segmentation and evaluation methods, applied in neural learning methods, acquisition/recognition of facial features, instruments, etc., can solve problems such as large errors and low evaluation efficiency

Pending Publication Date: 2020-09-18
SHENZHEN DJ INNOVATION IND CO LTD
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  • 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 semantic segmentation

Method used

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  • Precise facial paralysis degree evaluation method and device based on semantic segmentation
  • Precise facial paralysis degree evaluation method and device based on semantic segmentation
  • Precise facial paralysis degree evaluation method and device based on semantic segmentation

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Embodiment 1

[0081] see figure 1, this embodiment provides a method for evaluating the degree of facial paralysis based on semantic segmentation. For industrial application, for example, it can be used as an independent program in mobile phones and clients, 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, this accurate facial paralysis degree evaluation method comprises following these steps, i.e. steps (1)-(3).

[0082] Step (1): Establish a facial paralysis semantic segmentation model. In the present embodiment, the establishment method of the facial paralysis semantic segmentation model includes the following steps, namely steps (1.1)-(1.4). see figure 2 , in the facial paralysis semantic segmentation model, in the facial paralysis semantic segmentation model, the two eyebrow regions are s 1 , s 2 , located in the eyebrow reg...

Embodiment 2

[0123] see image 3 , this embodiment provides a semantic segmentation-based accurate facial paralysis evaluation method, which is similar to that of Embodiment 1, the difference being 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 as image 3 shown. The downsampling and upsampling layers of the deep full convolutional network model are both 3 layers, and the downsampling adopts the 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 separated by ...

Embodiment 3

[0125] The present embodiment provides a kind of accurate facial paralysis degree assessment device based on semantic segmentation, and the accurate facial paralysis degree assessment method based on semantic segmentation of this device application embodiment 1 or embodiment 2. Wherein, the precise facial paralysis degree evaluation device includes a detection model building module, a data acquisition module, a data processing module and a comprehensive evaluation module for the degree of facial paralysis, and 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.

[0126] The detection model building module is used to set up the facial paralysis semantic segmentation model, which is actually used to perform the step (1) in Embodiment 1. In the facial para...

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Abstract

The invention discloses a precise facial paralysis degree evaluation method and device based on semantic segmentation. The method comprises the following steps: establishing a facial paralysis semantic segmentation model; acquiring to-be-detected data and processing the to-be-detected data; sequentially inputting the expression-free natural state static image, the sequence image I, the sequence image II, the sequence image III and the sequence image IV into the facial paralysis semantic segmentation model to output a plurality of corresponding groups of face shapes, and updating the pluralityof groups of face shapes; evaluating the facial paralysis degree of the user to be detected; calculating theta1, theta2, theta3, theta4, theta5, theta6, theta7, theta8, theta9, theta10, b1, b2, c1, c2, e1 and e2, and comparing the calculated values with the threshold values; and judging the facial paralysis degree of the to-be-detected user through the comparison result, and calculating a facial paralysis index. According to the invention, the detection model has high detection positioning precision, the precision and accuracy of comprehensive evaluation and detection of the facial paralysis degree of the to-be-detected user are greatly improved, and a powerful support is provided for 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 semantic segmentation, and also to a device for evaluating the degree of accurate facial paralysis based on semantic segmentation using the method. Background technique [0002] Facial paralysis is a common disease in which the motor function of facial muscles is hindered. It is often difficult for patients to complete basic facial movements such as closing eyes, raising eyebrows, bulging cheeks, wrinkling nose or opening mouth, and it is an area with a high incidence rate in my country. Facial paralysis is generally called facial nerve paralysis. The general symptom is crooked mouth and eyes. Patients often cannot even complete the most basic movements such as raising eyebrows, closing eyes, and puffing out the mo...

Claims

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Application Information

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IPC IPC(8): G06K9/00G06N3/04G06N3/08
CPCG06N3/084G06V40/165G06V40/171G06V40/174G06V40/172G06N3/045
Inventor 冯少华李伟中李健金波邓利平冼上轩
Owner SHENZHEN DJ INNOVATION IND CO LTD
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