CN110569742A - Micro-expression analysis and study judging system - Google Patents

Micro-expression analysis and study judging system Download PDF

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Publication number
CN110569742A
CN110569742A CN201910762116.1A CN201910762116A CN110569742A CN 110569742 A CN110569742 A CN 110569742A CN 201910762116 A CN201910762116 A CN 201910762116A CN 110569742 A CN110569742 A CN 110569742A
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training
micro
expression
expression analysis
testing
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Chinese (zh)
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丁晓进
洪涛
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Kunshan Qiao Intelligent Technology Co Ltd
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Kunshan Qiao Intelligent Technology Co Ltd
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    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/04Architecture, e.g. interconnection topology
    • G06N3/045Combinations of networks
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computing arrangements based on biological models
    • G06N3/02Neural networks
    • G06N3/08Learning methods
    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06VIMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V40/00Recognition of biometric, human-related or animal-related patterns in image or video data
    • G06V40/10Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
    • G06V40/16Human faces, e.g. facial parts, sketches or expressions
    • G06V40/174Facial expression recognition

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  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Health & Medical Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • General Physics & Mathematics (AREA)
  • Biomedical Technology (AREA)
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  • Evolutionary Computation (AREA)
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  • Life Sciences & Earth Sciences (AREA)
  • Oral & Maxillofacial Surgery (AREA)
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Abstract

The invention discloses a micro-expression analysis, study and judgment system, which comprises a training unit and a testing unit; the micro-expression analysis of the training unit comprises the following steps: (1) starting training; (2) training face detection and cutting; (3) extracting human face micro-expression characteristics by adopting a multilayer heterogeneous neural network for training; (4) training facial expression analysis; (5) finishing the training; the micro-expression analysis and study and judgment system carries out a large amount of training and testing through the training steps and the testing steps of the training unit and the testing unit, can accurately give the emotion result of the tested person under stimulation in real time and timely and effectively give reference information to an investigator, and the investigator can further obtain more clues around the stimulation corresponding to the expression, thereby improving the investigation quality.

Description

Micro-expression analysis and study judging system
Technical Field
The invention relates to the field of computer vision analysis, in particular to a micro-expression analysis and study and judgment system.
Background
the human facial expression is an effective expression mode for human information communication, and is used as a key technology in an emotion calculation system to enable the human facial expression to become a basis of human-computer interaction, so that the research on the human facial expression not only conforms to the development of artificial intelligence, but also conforms to the trend of era development, is beneficial to promoting the development of science and technology, and is bound to become a trend of the science and technology industry in the near future.
The facial expression of the human face has wide application, especially, in various large factories and enterprises, the safety protection problem in the working process is more and more emphasized, for example, accidents such as mines, building sites, heavy industrial areas and the like are frequent, the safety protection problem is serious, and the facial expression of the human face can provide much information for the safety protection problem. For example, in the aspect of medical monitoring, an expression monitoring system is developed, psychological changes and physiological states of a patient at the moment are analyzed by monitoring changes of the expression of the patient in real time, and if the patient is found to have pain or bad emotion, medical staff can be informed to carry out treatment in time; in the production process of a coal mine, the low emotion of underground miners, fatigue or distraction in the working process can influence the working efficiency of the underground miners, even cause accidents, and if the face expression recognition can be realized through a computer, the emotion state of the underground miners can be better mastered, so that problems can be found in time, and accident potential can be eliminated; in the driving process, the fatigue driving condition can often appear, and if the expression state of the driver can be observed in real time at the moment, the driver can be reminded in time when the fatigue expression appears on the face of the driver, so that the driver can be prevented from getting in the bud, and the traffic accident can be prevented.
disclosure of Invention
In order to overcome the above problems, the present invention provides a micro-expression analysis and judgment system.
the technical scheme of the invention is to provide a micro-expression analysis and study system which is characterized by comprising a training unit and a testing unit; the micro-expression analysis of the training unit comprises the following steps:
(1) starting training;
(2) Training face detection and cutting;
(3) Extracting human face micro-expression characteristics by adopting a multilayer heterogeneous neural network for training;
(4) training facial expression analysis;
(5) finishing the training;
The micro-expression analysis of the test unit comprises the following steps:
(1) starting the test;
(2) testing face detection and cutting;
(3) Extracting human face micro-expression characteristics by adopting a multilayer heterogeneous neural network for testing;
(4) training facial expression analysis;
(5) and finishing the training.
furthermore, the system also comprises an expression database which comprises a data information base consisting of various representative expressions, and the training unit and the testing unit are connected with the expression database.
Furthermore, the expression database is connected with a facial expression feature extraction module, the facial expression feature extraction module comprises a multilayer heterogeneous neural network, and the system can learn essential features representing the micro expressions from sample data autonomously by adopting the heterogeneous neural network to extract facial micro expression features.
the invention has the beneficial effects that: the micro-expression analysis and study and judgment system carries out a large amount of training and testing through the training steps and the testing steps of the training unit and the testing unit, can accurately give the emotion result of the tested person under stimulation in real time and timely and effectively give reference information to an investigator, and the investigator can further obtain more clues around the stimulation corresponding to the expression, thereby improving the investigation quality.
Drawings
FIG. 1 is a schematic diagram of a micro-expression analysis and judgment system according to the present invention.
Detailed Description
In order to make the technical means, the creation characteristics, the achievement purposes and the effects of the invention easy to understand, the invention is further described with the specific embodiments.
as shown in FIG. 1, the system for analyzing and judging micro-expression of the present invention is characterized in that it comprises a training unit and a testing unit; the micro-expression analysis of the training unit comprises the following steps:
(1) starting training;
(2) Training face detection and cutting;
(3) Extracting human face micro-expression characteristics by adopting a multilayer heterogeneous neural network for training;
(4) training facial expression analysis;
(5) finishing the training;
the micro-expression analysis of the test unit comprises the following steps:
(1) starting the test;
(2) testing face detection and cutting;
(3) extracting human face micro-expression characteristics by adopting a multilayer heterogeneous neural network for testing;
(4) Training facial expression analysis;
(5) and finishing the training.
furthermore, the system also comprises an expression database which comprises a data information base consisting of various representative expressions, and the training unit and the testing unit are connected with the expression database.
furthermore, the expression database is connected with a facial expression feature extraction module, the facial expression feature extraction module comprises a multilayer heterogeneous neural network, and the system can learn essential features representing the micro expressions from sample data autonomously by adopting the heterogeneous neural network to extract facial micro expression features.
the micro-expression analysis and study and judgment system carries out a large amount of training and testing through the training steps and the testing steps of the training unit and the testing unit, can accurately give the emotion result of the tested person under stimulation in real time and timely and effectively give reference information to an investigator, and the investigator can further obtain more clues around the stimulation corresponding to the expression, thereby improving the investigation quality.
the above embodiment is only one embodiment of the present invention, and the description thereof is specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.

Claims (3)

1. A micro-expression analysis, study and judgment system is characterized by comprising a training unit and a testing unit; the micro-expression analysis of the training unit comprises the following steps:
(1) starting training;
(2) Training face detection and cutting;
(3) Extracting human face micro-expression characteristics by adopting a multilayer heterogeneous neural network for training;
(4) training facial expression analysis;
(5) Finishing the training;
The micro-expression analysis of the test unit comprises the following steps:
(1) starting the test;
(2) testing face detection and cutting;
(3) Extracting human face micro-expression characteristics by adopting a multilayer heterogeneous neural network for testing;
(4) training facial expression analysis;
(5) and finishing the training.
2. The micro-expression analysis and judgment system according to claim 1, wherein: the system also comprises an expression database which comprises a data information base consisting of various representative expressions, and the training unit and the testing unit are connected with the expression database.
3. The micro-expression analysis and judgment system according to claim 2, wherein: the expression database is connected with a facial expression feature extraction module, the facial expression feature extraction module comprises a multilayer heterogeneous neural network, and the system can learn essential features representing the micro expressions from sample data autonomously by adopting the heterogeneous neural network to extract facial micro expression features.
CN201910762116.1A 2019-08-19 2019-08-19 Micro-expression analysis and study judging system Pending CN110569742A (en)

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Application Number Priority Date Filing Date Title
CN201910762116.1A CN110569742A (en) 2019-08-19 2019-08-19 Micro-expression analysis and study judging system

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Application Number Priority Date Filing Date Title
CN201910762116.1A CN110569742A (en) 2019-08-19 2019-08-19 Micro-expression analysis and study judging system

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CN110569742A true CN110569742A (en) 2019-12-13

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Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103488974A (en) * 2013-09-13 2014-01-01 南京华图信息技术有限公司 Facial expression recognition method and system based on simulated biological vision neural network
CN104318221A (en) * 2014-11-05 2015-01-28 中南大学 Facial expression recognition method based on ELM
CN106529494A (en) * 2016-11-24 2017-03-22 深圳市永达电子信息股份有限公司 Human face recognition method based on multi-camera model
CN106599800A (en) * 2016-11-25 2017-04-26 哈尔滨工程大学 Face micro-expression recognition method based on deep learning
US20170357847A1 (en) * 2016-06-10 2017-12-14 Marwan Jabri Biologically inspired apparatus and methods for pattern recognition
CN107679526A (en) * 2017-11-14 2018-02-09 北京科技大学 A kind of micro- expression recognition method of face
CN107679580A (en) * 2017-10-21 2018-02-09 桂林电子科技大学 A kind of isomery shift image feeling polarities analysis method based on the potential association of multi-modal depth
CN108073910A (en) * 2017-12-29 2018-05-25 百度在线网络技术(北京)有限公司 For generating the method and apparatus of face characteristic
CN109376692A (en) * 2018-11-22 2019-02-22 河海大学常州校区 Migration convolution neural network method towards facial expression recognition

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103488974A (en) * 2013-09-13 2014-01-01 南京华图信息技术有限公司 Facial expression recognition method and system based on simulated biological vision neural network
CN104318221A (en) * 2014-11-05 2015-01-28 中南大学 Facial expression recognition method based on ELM
US20170357847A1 (en) * 2016-06-10 2017-12-14 Marwan Jabri Biologically inspired apparatus and methods for pattern recognition
CN106529494A (en) * 2016-11-24 2017-03-22 深圳市永达电子信息股份有限公司 Human face recognition method based on multi-camera model
CN106599800A (en) * 2016-11-25 2017-04-26 哈尔滨工程大学 Face micro-expression recognition method based on deep learning
CN107679580A (en) * 2017-10-21 2018-02-09 桂林电子科技大学 A kind of isomery shift image feeling polarities analysis method based on the potential association of multi-modal depth
CN107679526A (en) * 2017-11-14 2018-02-09 北京科技大学 A kind of micro- expression recognition method of face
CN108073910A (en) * 2017-12-29 2018-05-25 百度在线网络技术(北京)有限公司 For generating the method and apparatus of face characteristic
CN109376692A (en) * 2018-11-22 2019-02-22 河海大学常州校区 Migration convolution neural network method towards facial expression recognition

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
付晓峰等: "小数据样本深度迁移网络自发表情分类", 《中国图象图形学报》 *
李文书等: "微表情识别方法综述", 《人类工效学》 *
胡继胜等: "基于BP神经网络的人脸表情识别", 《微型机与应用》 *

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