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Face recognition method and system

A technology for facial expression recognition and to-be-recognized, applied in the field of image recognition, can solve problems such as poor facial expression recognition effect

Active Publication Date: 2020-01-31
暗物智能科技(广州)有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Therefore, a kind of face recognition method and system provided by the present invention overcomes the defect in the prior art that the effect of face expression recognition on various data sets is poor.

Method used

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  • Face recognition method and system

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Experimental program
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Embodiment 1

[0034] The facial expression recognition method provided by the embodiment of the present invention can be applied to application fields that require facial expression recognition, such as smart medical care, intelligent transportation, etc., and the facial expression can be recognized after the terminal obtains the facial image. Such as figure 1 As shown, the facial expression recognition method comprises the following steps:

[0035] Step S1: Acquire a face image to be recognized, the face image includes a plurality of facial action units, and there are dependencies between the facial action units and expressions and between facial action units.

[0036]In the embodiment of the present invention, the facial expressions involved include: calm, happy, angry, sad, disgusted, surprised, afraid, etc.; the facial action unit is the movement of the muscles in a specific area of ​​the human face. The embodiment of the present invention involves 17 facial expressions Facial action u...

Embodiment 2

[0105] Embodiments of the present invention provide a method system for facial expression recognition, such as Figure 8 shown, including:

[0106] The face image acquisition module 1 is used to acquire a face image to be recognized, the face image includes a plurality of facial action units, and there is a dependency relationship between the facial action units and expressions and between the facial action units. This module executes the method described in step S1 in Embodiment 1, which will not be repeated here.

[0107] The first feature acquisition module 2 is used to acquire the first feature representing the global characteristics of the face image by using the backbone network of the neural network; this module executes the method described in step S2 in Embodiment 1, and details are not repeated here.

[0108] The second feature acquisition module 3, utilizes the local branch network of neural network according to the relationship between preset human face action uni...

Embodiment 3

[0113] An embodiment of the present invention provides a computer device, such as Figure 9 As shown, it includes: at least one processor 401 , such as a CPU (Central Processing Unit, central processing unit), at least one communication interface 403 , memory 404 , and at least one communication bus 402 . Wherein, the communication bus 402 is used to realize connection and communication between these components. Wherein, the communication interface 403 may include a display screen (Display) and a keyboard (Keyboard), and the optional communication interface 403 may also include a standard wired interface and a wireless interface. The memory 404 may be a high-speed RAM memory (Ramdom Access Memory, volatile random access memory), or a non-volatile memory (non-volatile memory), such as at least one disk memory. Optionally, the memory 404 may also be at least one storage device located away from the aforementioned processor 401 . Wherein, the processor 401 may execute the facia...

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Abstract

The invention discloses a face expression recognition method and system, and the method comprises the steps: obtaining a to-be-recognized face image which comprises a plurality of face action units, wherein there are dependence relationships between the face action units and expressions and between the face action units; utilizing a backbone network of the neural network to obtain a first featurerepresenting the global feature of the face image; extracting a second feature representing local features of the facial action unit on the basis of the first feature according to a preset relationship between the facial action unit and the expression; after the first feature and the second feature are fused, a third feature is obtained according to the dependency relationship between the facial action units; and splicing the third feature and the first feature to obtain a fourth feature, and performing facial expression prediction according to the fourth feature. According to the embodiment of the invention, the feature extraction is assisted by introducing the expression-action unit relationship and the action unit relationship and combining the expression and action unit knowledge interaction, so that more accurate recognition of the facial expression is realized.

Description

technical field [0001] The invention relates to the technical field of image recognition, in particular to a face recognition method and system. Background technique [0002] Facial expression is an important signal to convey human emotions. Automatic expression recognition can assist applications such as robot interaction, smart medical treatment, and user analysis. Therefore, there have been a lot of research work for a long time, mainly focusing on seven basic expressions in a controlled environment ( Calm, Happy, Angry, Sad, Disgusted, Surprised, Scared). Relatedly, action units define the movement of muscles in specific areas of the face, such as the muscles at the corners of the mouth rising and the jaw falling. According to the action unit coding system, each basic expression can be precisely defined as a combination of a series of action units, so action units also play an important role in automatic expression recognition. [0003] In recent years, large-scale dat...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/62
CPCG06V40/169G06V40/171G06V40/174G06F18/253
Inventor 谢圆陈添水蒲韬
Owner 暗物智能科技(广州)有限公司
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