CN106846949A - A kind of long-range Emotional Teaching system - Google Patents
A kind of long-range Emotional Teaching system Download PDFInfo
- Publication number
- CN106846949A CN106846949A CN201710130155.0A CN201710130155A CN106846949A CN 106846949 A CN106846949 A CN 106846949A CN 201710130155 A CN201710130155 A CN 201710130155A CN 106846949 A CN106846949 A CN 106846949A
- Authority
- CN
- China
- Prior art keywords
- module
- client
- teacher
- analysis module
- student
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G09—EDUCATION; CRYPTOGRAPHY; DISPLAY; ADVERTISING; SEALS
- G09B—EDUCATIONAL OR DEMONSTRATION APPLIANCES; APPLIANCES FOR TEACHING, OR COMMUNICATING WITH, THE BLIND, DEAF OR MUTE; MODELS; PLANETARIA; GLOBES; MAPS; DIAGRAMS
- G09B5/00—Electrically-operated educational appliances
- G09B5/08—Electrically-operated educational appliances providing for individual presentation of information to a plurality of student stations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V40/00—Recognition of biometric, human-related or animal-related patterns in image or video data
- G06V40/10—Human or animal bodies, e.g. vehicle occupants or pedestrians; Body parts, e.g. hands
- G06V40/16—Human faces, e.g. facial parts, sketches or expressions
- G06V40/174—Facial expression recognition
Abstract
The present invention provides a kind of long-range Emotional Teaching system, it includes image capture module, color analysis module, pixels statisticses module, characteristic point analysis module, MBM, database, mood analysis module, big data processing module, teacher's client, student client, tutor auxiliary platform module, learner is shot by software systems, and aid in carrying out Treatment Analysis to image by the webserver, set up micro- expression shape change and behavior dynamic of people surface model analytic learning person, so as to the emotion for judging learner changes and sends prompting to teacher, realize Emotional Teaching.The system that the present invention is provided has the advantages that intelligent analysis, emotion aided education.
Description
Technical field
The invention belongs to information-based remote teaching technical field, more particularly to a kind of long-range Emotional Teaching system.
Background technology
Emotional ability is the important symbol of human intelligence, the missing of emotion can influence network distance education quality of instruction and
The results of learning of learner.Affection computation machine technology is harmonious man-machine interaction and research direction new in artificial intelligence field.
Application affection computation theory and technology, can further optimize the function of network distance education in Remote Education System Based On Internet, help
The emotion change of assiatant teacher's monitoring Distance Learners, adjusts instructional strategies and method, and the feedback of learner's emotion is given in real time, makes
Quality of instruction reaches most preferably.
Recognition of face, is that the facial feature information based on people carries out a kind of biological identification technology of identification.With shooting
Machine or camera image or video flowing of the collection containing face, and automatic detect and track face in the picture, and then to detection
To face carry out a series of correlation techniques of face, generally also referred to as Identification of Images, face recognition.
Micro- expression, is psychology noun.People see heart impression expression to other side by doing some expressions, are done in people
Different expressions between, or in certain expression, face's meeting " leakage " goes out other information." micro- expression " is most short by sustainable 1/25
Second, although a subconscious expression may be only lasted in a flash, but this characteristic, it is easy to expose mood.When face is doing
During certain expression, these duration extremely short expression can flash across suddenly, and express opposite mood sometimes." micro- table
Feelings " flash across, and the people and observer that typically even clear-headed work is expressed one's feelings are detectable.In experiment, only 10% people examines
Feel.Compared with it is intended to know the expression made, " micro- expression " can more embody people really impression and motivation.
People face recognize on the basis of enter pedestrian's surface analysis in conjunction with " micro- expression ", using computer high speed catch and
Computing capability can preferably recognize and analyze micro- expression shape change of people, such that it is able to judge the emotion of analysis object.
The content of the invention
Above mentioned problem is had based on prior art, the present invention provides a kind of long-range Emotional Teaching system, and it includes that image is adopted
Collection module, color analysis module, pixels statisticses module, characteristic point analysis module, MBM, database, mood analysis module,
Big data processing module, teacher's client, student client, tutor auxiliary platform module, are clapped learner by software systems
Take the photograph, and aid in carrying out Treatment Analysis to image by the webserver, set up micro- expression shape change of people surface model analytic learning person
With behavior dynamic, so as to judge the emotion change of learner and send prompting to teacher, Emotional Teaching is realized.What the present invention was provided
System has the advantages that intelligent analysis, emotion aided education.
A kind of long-range Emotional Teaching system, it includes image capture module, color analysis module, pixels statisticses module, spy
Levy point analysis module, MBM, database, mood analysis module, big data processing module, teacher's client, student client
End, tutor auxiliary platform module;
Image capture module is connected to the capture apparatus of teacher's client and student client, and portrait is carried out by capture apparatus
Shoot, and shooting angle and shooting focal length are adjusted according to the information feedback control capture apparatus of color analysis module, to shoot most
Good image;
Color analysis module receives the image that is collected of image capture module, analyzes the color parameter of image, according to image face
Color change judges the scope in people face, people face position is fed back into image analysis module and people face positional information is sent into pixel system
Meter module;
Pixelation is carried out after the positional information of pixels statisticses module recipient face to people face location drawing picture, with reference to database people's region feature
Data carry out the identification of pixels statisticses people face to image pixel;
Characteristic point analysis module is divided according to micro- expressive features in the people face result combination database of pixels statisticses module analysis
Analysis, definition people's region feature point;
The analysis result of pixels statisticses module and characteristic point analysis module is combined generation people's surface model by MBM, and in model
Upper feature point for calibration, according to the real-time analysis and regulation characteristic point position of characteristic point analysis module, recording feature point change in location position
Move;
Mood analysis module more changes displacement according to the characteristic point position on people's surface model, call micro- expressive features in database and
Psychological behavioral Characteristic analyzes the change of personage's mood and mood, and the emotional state of student is reacted into teacher's client, reminds
Teacher's adjustment teaching;
Big data processing module is connected to Internet Server, gathers internet data and assists color analysis module, pixel to unite
Meter module and characteristic point analysis module carry out corresponding big data analytical calculation, and storehouse information is updated the data according to analysis result;
Teacher's client is connected to supplementary module of preparing lessons, sentiment analysis module, and real-time recording instructional video simultaneously arrives video transmission
Student client, and the state of teacher student is reminded according to the analysis result of sentiment analysis module;
Student client is connected to teacher's client, plays the video of teacher's client recording, and records the study video of student,
Transmission of video to sentiment analysis module and teacher's client will be learnt;When student question by problem be sent to teacher's client and
Student client of the same class;
Tutor auxiliary platform module includes archive of student, by course distribution student class, stores the content of preparing lessons of teacher.
Wherein, described mood analysis module include micro- Expression analysis module and behavioural analysis module, with reference to it is micro- expression and
Behavior act judges student's state.
Wherein, described database includes people's region feature database, micro- expressive features database and Psychological behavioral Characteristic number
According to storehouse.
Wherein, described image capture module includes still image acquisition module and dynamic image acquisition module, static map
As the still image in acquisition module collection people face, the dynamic image in dynamic image acquisition module collection people face.
Wherein, described database includes local data base and internet data storehouse.
Wherein, described student client can be by the video storage of teacher's client recording in student's personal computer
In.
Specific embodiment
With reference to specific embodiment, the invention will be further described.
A kind of long-range Emotional Teaching system, it includes image capture module, color analysis module, pixels statisticses module, spy
Levy point analysis module, MBM, database, mood analysis module, big data processing module, teacher's client, student client
End, tutor auxiliary platform module;
Image capture module is connected to the capture apparatus of teacher's client and student client, and portrait is carried out by capture apparatus
Shoot, and shooting angle and shooting focal length are adjusted according to the information feedback control capture apparatus of color analysis module, to shoot most
Good image;
Color analysis module receives the image that is collected of image capture module, analyzes the color parameter of image, according to image face
Color change judges the scope in people face, people face position is fed back into image analysis module and people face positional information is sent into pixel system
Meter module;
Pixelation is carried out after the positional information of pixels statisticses module recipient face to people face location drawing picture, with reference to database people's region feature
Data carry out the identification of pixels statisticses people face to image pixel;
Characteristic point analysis module is divided according to micro- expressive features in the people face result combination database of pixels statisticses module analysis
Analysis, definition people's region feature point;
The analysis result of pixels statisticses module and characteristic point analysis module is combined generation people's surface model by MBM, and in model
Upper feature point for calibration, according to the real-time analysis and regulation characteristic point position of characteristic point analysis module, recording feature point change in location position
Move;
Mood analysis module more changes displacement according to the characteristic point position on people's surface model, call micro- expressive features in database and
Psychological behavioral Characteristic analyzes the change of personage's mood and mood, and the emotional state of student is reacted into teacher's client, reminds
Teacher's adjustment teaching;
Big data processing module is connected to Internet Server, gathers internet data and assists color analysis module, pixel to unite
Meter module and characteristic point analysis module carry out corresponding big data analytical calculation, and storehouse information is updated the data according to analysis result;
Teacher's client is connected to supplementary module of preparing lessons, sentiment analysis module, and real-time recording instructional video simultaneously arrives video transmission
Student client, and the state of teacher student is reminded according to the analysis result of sentiment analysis module;
Student client is connected to teacher's client, plays the video of teacher's client recording, and records the study video of student,
Transmission of video to sentiment analysis module and teacher's client will be learnt;When student question by problem be sent to teacher's client and
Student client of the same class;
Tutor auxiliary platform module includes archive of student, by course distribution student class, stores the content of preparing lessons of teacher.
Used as embodiment is selected, described mood analysis module includes micro- Expression analysis module and behavioural analysis module, with reference to
Micro- expression and behavior act judge student's state.
Used as embodiment is selected, described database includes people's region feature database, micro- expressive features database and psychological row
It is characterized database.
Used as embodiment is selected, described image capture module includes still image acquisition module and dynamic image acquisition mould
Block, the still image in still image acquisition module collection people face, the dynamic image in dynamic image acquisition module collection people face.
Used as embodiment is selected, described database includes local data base and internet data storehouse.
Used as embodiment is selected, described student client can be personal in student by the video storage of teacher's client recording
In computer.
Embodiment described above only expresses one embodiment of the present invention, and its description is more specific and detailed, but simultaneously
Therefore the limitation to the scope of the claims of the present invention can not be interpreted as.It should be pointed out that for one of ordinary skill in the art
For, without departing from the inventive concept of the premise, various modifications and improvements can be made, these belong to guarantor of the invention
Shield scope.Therefore, the protection domain of patent of the present invention should be determined by the appended claims.
Claims (6)
1. a kind of long-range Emotional Teaching system, it includes image capture module, color analysis module, pixels statisticses module, feature
Point analysis module, MBM, database, mood analysis module, big data processing module, teacher's client, student client,
Tutor auxiliary platform module;
Image capture module is connected to the capture apparatus of teacher's client and student client, and portrait is carried out by capture apparatus
Shoot, and shooting angle and shooting focal length are adjusted according to the information feedback control capture apparatus of color analysis module, to shoot most
Good image;
Color analysis module receives the image that is collected of image capture module, analyzes the color parameter of image, according to image face
Color change judges the scope in people face, people face position is fed back into image analysis module and people face positional information is sent into pixel system
Meter module;
Pixelation is carried out after the positional information of pixels statisticses module recipient face to people face location drawing picture, with reference to database people's region feature
Data carry out the identification of pixels statisticses people face to image pixel;
Characteristic point analysis module is divided according to micro- expressive features in the people face result combination database of pixels statisticses module analysis
Analysis, definition people's region feature point;
The analysis result of pixels statisticses module and characteristic point analysis module is combined generation people's surface model by MBM, and in model
Upper feature point for calibration, according to the real-time analysis and regulation characteristic point position of characteristic point analysis module, recording feature point change in location position
Move;
Mood analysis module more changes displacement according to the characteristic point position on people's surface model, call micro- expressive features in database and
Psychological behavioral Characteristic analyzes the change of personage's mood and mood, and the emotional state of student is reacted into teacher's client, reminds
Teacher's adjustment teaching;
Big data processing module is connected to Internet Server, gathers internet data and assists color analysis module, pixel to unite
Meter module and characteristic point analysis module carry out corresponding big data analytical calculation, and storehouse information is updated the data according to analysis result;
Teacher's client is connected to supplementary module of preparing lessons, sentiment analysis module, and real-time recording instructional video simultaneously arrives video transmission
Student client, and the state of teacher student is reminded according to the analysis result of sentiment analysis module;
Student client is connected to teacher's client, plays the video of teacher's client recording, and records the study video of student,
Transmission of video to sentiment analysis module and teacher's client will be learnt;When student question by problem be sent to teacher's client and
Student client of the same class;
Tutor auxiliary platform module includes archive of student, by course distribution student class, stores the content of preparing lessons of teacher.
2. long-range Emotional Teaching system according to claim 1, it is characterised in that described mood analysis module includes micro-
Expression analysis module and behavioural analysis module, student's state is judged with reference to micro- expression and behavior act.
3. long-range Emotional Teaching system according to claim 1, it is characterised in that described database includes people's region feature
Database, micro- expressive features database and Psychological behavioral Characteristic database.
4. long-range Emotional Teaching system according to claim 1, it is characterised in that described image capture module includes quiet
State image capture module and dynamic image acquisition module, the still image in still image acquisition module collection people face, dynamic image
The dynamic image in acquisition module collection people face.
5. long-range Emotional Teaching system according to claim 1, it is characterised in that described database includes local data
Storehouse and internet data storehouse.
6. long-range Emotional Teaching system according to claim 1, it is characterised in that described student client will can teach
The video storage of teacher's client recording is in student's personal computer.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201710130155.0A CN106846949A (en) | 2017-03-07 | 2017-03-07 | A kind of long-range Emotional Teaching system |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201710130155.0A CN106846949A (en) | 2017-03-07 | 2017-03-07 | A kind of long-range Emotional Teaching system |
Publications (1)
Publication Number | Publication Date |
---|---|
CN106846949A true CN106846949A (en) | 2017-06-13 |
Family
ID=59138219
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201710130155.0A Pending CN106846949A (en) | 2017-03-07 | 2017-03-07 | A kind of long-range Emotional Teaching system |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN106846949A (en) |
Cited By (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN107292271A (en) * | 2017-06-23 | 2017-10-24 | 北京易真学思教育科技有限公司 | Learning-memory behavior method, device and electronic equipment |
CN107492056A (en) * | 2017-08-25 | 2017-12-19 | 宁波纷享软件科技有限公司 | The mobile terminal and implementation method of special teaching |
CN107844762A (en) * | 2017-10-25 | 2018-03-27 | 大连三增上学教育科技有限公司 | Information processing method and system |
CN109101933A (en) * | 2018-08-21 | 2018-12-28 | 重庆乐教科技有限公司 | A kind of emotion-directed behavior visual analysis method based on artificial intelligence |
CN109523852A (en) * | 2018-11-21 | 2019-03-26 | 合肥虹慧达科技有限公司 | The study interactive system and its exchange method of view-based access control model monitoring |
CN110059614A (en) * | 2019-04-16 | 2019-07-26 | 广州大学 | A kind of intelligent assistant teaching method and system based on face Emotion identification |
CN110428678A (en) * | 2019-08-12 | 2019-11-08 | 重庆工业职业技术学院 | A kind of computer online teaching management system |
CN111803097A (en) * | 2020-08-15 | 2020-10-23 | 吉林医药学院附属医院 | Patient psychological state detection system based on big data |
CN114998975A (en) * | 2022-07-15 | 2022-09-02 | 电子科技大学成都学院 | Foreign language teaching method and device based on big data |
Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR20010083866A (en) * | 2001-04-12 | 2001-09-03 | 조인형 | Monitortop Typed Simulation System and Method for Studying Based on Internet |
KR20060121679A (en) * | 2005-05-25 | 2006-11-29 | 오끼 덴끼 고오교 가부시끼가이샤 | Picture composing apparatus, commnunication terminal and picture communication system using the apparatus, and chatting server in the system |
CN101604382A (en) * | 2009-06-26 | 2009-12-16 | 华中师范大学 | A kind of learning fatigue recognition interference method based on human facial expression recognition |
CN102945624A (en) * | 2012-11-14 | 2013-02-27 | 南京航空航天大学 | Intelligent video teaching system based on cloud calculation model and expression information feedback |
CN203706473U (en) * | 2013-12-11 | 2014-07-09 | 上海远驰专修学院 | A remote network teaching system |
CN104299178A (en) * | 2014-07-11 | 2015-01-21 | 北京神州智联科技有限公司 | Facial-recognition-based network teaching method and system |
CN104464406A (en) * | 2013-09-12 | 2015-03-25 | 郑州学生宝电子科技有限公司 | Real-time interactive online learning platform |
CN106127139A (en) * | 2016-06-21 | 2016-11-16 | 东北大学 | A kind of dynamic identifying method of MOOC course middle school student's facial expression |
CN106372614A (en) * | 2016-09-13 | 2017-02-01 | 南宁市远才教育咨询有限公司 | Class discipline monitoring prompt auxiliary apparatus |
-
2017
- 2017-03-07 CN CN201710130155.0A patent/CN106846949A/en active Pending
Patent Citations (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR20010083866A (en) * | 2001-04-12 | 2001-09-03 | 조인형 | Monitortop Typed Simulation System and Method for Studying Based on Internet |
KR20060121679A (en) * | 2005-05-25 | 2006-11-29 | 오끼 덴끼 고오교 가부시끼가이샤 | Picture composing apparatus, commnunication terminal and picture communication system using the apparatus, and chatting server in the system |
CN101604382A (en) * | 2009-06-26 | 2009-12-16 | 华中师范大学 | A kind of learning fatigue recognition interference method based on human facial expression recognition |
CN102945624A (en) * | 2012-11-14 | 2013-02-27 | 南京航空航天大学 | Intelligent video teaching system based on cloud calculation model and expression information feedback |
CN104464406A (en) * | 2013-09-12 | 2015-03-25 | 郑州学生宝电子科技有限公司 | Real-time interactive online learning platform |
CN203706473U (en) * | 2013-12-11 | 2014-07-09 | 上海远驰专修学院 | A remote network teaching system |
CN104299178A (en) * | 2014-07-11 | 2015-01-21 | 北京神州智联科技有限公司 | Facial-recognition-based network teaching method and system |
CN106127139A (en) * | 2016-06-21 | 2016-11-16 | 东北大学 | A kind of dynamic identifying method of MOOC course middle school student's facial expression |
CN106372614A (en) * | 2016-09-13 | 2017-02-01 | 南宁市远才教育咨询有限公司 | Class discipline monitoring prompt auxiliary apparatus |
Cited By (14)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2018233398A1 (en) * | 2017-06-23 | 2018-12-27 | 北京易真学思教育科技有限公司 | Method, device, and electronic apparatus for monitoring learning |
CN107292271A (en) * | 2017-06-23 | 2017-10-24 | 北京易真学思教育科技有限公司 | Learning-memory behavior method, device and electronic equipment |
CN107292271B (en) * | 2017-06-23 | 2020-02-14 | 北京易真学思教育科技有限公司 | Learning monitoring method and device and electronic equipment |
US10891873B2 (en) | 2017-06-23 | 2021-01-12 | Beijing Yizhen Xuesi Education Technology Co., Ltd. | Method and apparatus for monitoring learning and electronic device |
CN107492056B (en) * | 2017-08-25 | 2020-11-06 | 福州华博立乐新材料科技有限公司 | Mobile terminal for special teaching and implementation method |
CN107492056A (en) * | 2017-08-25 | 2017-12-19 | 宁波纷享软件科技有限公司 | The mobile terminal and implementation method of special teaching |
CN107844762A (en) * | 2017-10-25 | 2018-03-27 | 大连三增上学教育科技有限公司 | Information processing method and system |
CN109101933A (en) * | 2018-08-21 | 2018-12-28 | 重庆乐教科技有限公司 | A kind of emotion-directed behavior visual analysis method based on artificial intelligence |
CN109101933B (en) * | 2018-08-21 | 2021-05-28 | 重庆乐教科技有限公司 | Emotional behavior visualization analysis method based on artificial intelligence |
CN109523852A (en) * | 2018-11-21 | 2019-03-26 | 合肥虹慧达科技有限公司 | The study interactive system and its exchange method of view-based access control model monitoring |
CN110059614A (en) * | 2019-04-16 | 2019-07-26 | 广州大学 | A kind of intelligent assistant teaching method and system based on face Emotion identification |
CN110428678A (en) * | 2019-08-12 | 2019-11-08 | 重庆工业职业技术学院 | A kind of computer online teaching management system |
CN111803097A (en) * | 2020-08-15 | 2020-10-23 | 吉林医药学院附属医院 | Patient psychological state detection system based on big data |
CN114998975A (en) * | 2022-07-15 | 2022-09-02 | 电子科技大学成都学院 | Foreign language teaching method and device based on big data |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN106846949A (en) | A kind of long-range Emotional Teaching system | |
Dewan et al. | A deep learning approach to detecting engagement of online learners | |
Littlewort et al. | Automated measurement of children's facial expressions during problem solving tasks | |
CN107292271A (en) | Learning-memory behavior method, device and electronic equipment | |
Murshed et al. | Engagement detection in e-learning environments using convolutional neural networks | |
CN106919922A (en) | A kind of anti-cheating Distant Evaluation System | |
CN110175534A (en) | Teaching assisting system based on multitask concatenated convolutional neural network | |
KR20120065111A (en) | Flow estimation base personalized e-learning method and system | |
CN106652605A (en) | Remote emotion teaching method | |
Banda et al. | Multimodal affect recognition in intelligent tutoring systems | |
Butko et al. | Automated facial affect analysis for one-on-one tutoring applications | |
CN106919924A (en) | A kind of mood analysis system based on the identification of people face | |
Ma et al. | A deep learning approach for online learning emotion recognition | |
CN110742404A (en) | Device and method for protecting eyesight of students during learning | |
Sidhu et al. | Deep learning based emotion detection in an online class | |
Ashwin et al. | Unobtrusive students' engagement analysis in computer science laboratory using deep learning techniques | |
Villegas-Ch et al. | Identification of emotions from facial gestures in a teaching environment with the use of machine learning techniques | |
CN106920194A (en) | A kind of anti-cheating remote test method | |
Dharmawansa et al. | Introducing and Evaluating the Behavior of Non-Verbal Features in the Virtual Learning. | |
Rathi et al. | Embedding Affect Awareness into Online Learning Environment using Deep Neural Network | |
Ning et al. | Application of psychological analysis of micro-expression recognition in teaching evaluation | |
Chen et al. | Intelligent Recognition of Physical Education Teachers' Behaviors Using Kinect Sensors and Machine Learning. | |
Wu et al. | Application of emotional recognition in intelligent tutoring system | |
Hwang et al. | Attentiveness assessment in learning based on fuzzy logic analysis | |
Llanda | Video tutoring system with automatic facial expression recognition: an enhancing approach to e-learning environment |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
WD01 | Invention patent application deemed withdrawn after publication | ||
WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20170613 |