Face state recognition method and device based on deep learning

A state recognition, deep learning technology, applied in character and pattern recognition, acquisition/recognition of facial features, instruments, etc., can solve the problem of not extracting feature points

Active Publication Date: 2019-11-19
HOHAI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Most of the fatigue monitoring methods based on image processing only obtain the position below the driver's eyes, and do not further extract feature points for local feature information such as the human eyes.

Method used

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  • Face state recognition method and device based on deep learning
  • Face state recognition method and device based on deep learning
  • Face state recognition method and device based on deep learning

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Embodiment Construction

[0105] The invention relates to a deep learning technology, which uses a deep neural network and a facial feature point processing model information comprehensive discrimination to realize the analysis of the face information of the identified person, thereby identifying the seven emotions of the identified person and the fatigue status of the identified person. Based on this information, we can play appropriate music to adjust the mood and fatigue of the identified person. The method includes collecting the image of the identified person and recording the collection time; using a face recognition algorithm to process and output the face recognition result; inputting the face recognition result to a deep neural network and a feature point processing model for processing to obtain expression and fatigue Recognition results; the expression and fatigue recognition results and the corresponding collection time are sequentially recorded as expression data in the expression and fatig...

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Abstract

The invention discloses a face state recognition method and a face state recognition device based on deep learning. The method comprises the steps: collecting a face image of a recognized person, recording the collection time, carrying out the processing of the image of the recognized person through a face recognition algorithm, and outputting a face recognition result. Inputting the face recognition result into a pre-trained deep neural network and a face feature point model for processing to obtain an expression recognition result and a fatigue recognition result; wherein the expression recognition result comprises an expression type and a predicted value thereof; taking the expression recognition result and the corresponding acquisition time as expression data, and sequentially recording the expression data into an expression database; and recording the fatigue data into the fatigue database according to time; acquiring a plurality of data from the expression and fatigue database and analyzing the data to obtain a state recognition result of the recognized person. The emotion and fatigue degree of the recognized person can be efficiently sensed and analyzed. The method and the device can be widely applied to the automation fields of fatigue driving detection, robots and the like.

Description

technical field [0001] The invention belongs to the technical field of image recognition processing, and relates to a face state recognition method and device based on deep learning. Background technique [0002] Emotion recognition refers to the study of an automatic, efficient, and accurate system to recognize the state of human facial expressions, and then understand people's emotional states, such as happiness, sadness, surprise, anger, etc., through facial expression information. This research has important application value in human-computer interaction, artificial intelligence, etc., and is one of the important topics in the fields of computer vision, pattern recognition, and affective computing. [0003] In the field of technology that requires human-computer interaction, especially robotics, it is usually necessary to be able to analyze human emotions in order to conduct effective human-computer interaction and bring sensory improvements to the user's interactive ex...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00
CPCG06V40/168G06V40/174G06V40/172G06V20/597
Inventor 胡鹤轩周全朱宇航彭守恒刘航朱映恺谭国平冯芸
Owner HOHAI UNIV
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