CN106652605A - Remote emotion teaching method - Google Patents
Remote emotion teaching method Download PDFInfo
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- CN106652605A CN106652605A CN201710130161.6A CN201710130161A CN106652605A CN 106652605 A CN106652605 A CN 106652605A CN 201710130161 A CN201710130161 A CN 201710130161A CN 106652605 A CN106652605 A CN 106652605A
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- 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
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- 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
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30196—Human being; Person
- G06T2207/30201—Face
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30244—Camera pose
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- Educational Technology (AREA)
- Business, Economics & Management (AREA)
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Abstract
The invention provides a remote emotion teaching method. The method captures a learner through a software system, processes and analyzes an image with the help of a network server, and establishes a human face model to analyze the micro-expression changes and behavior dynamics of the learner so as to determine emotion change of the learner and to promote a teacher to achieve emotional teaching. The method provided by the invention has advantages of intelligent analysis and emotion-assisted teaching.
Description
Technical field
The invention belongs to information-based remote teaching technical field, more particularly to a kind of long-range Emotional Teaching method.
Background technology
Emotional ability is the important symbol of human intelligence, the disappearance of emotion can affect the quality of instruction of network distance education and
The results of learning of learner.Affection computation machine technology is harmonious man-machine interaction and research direction new in artificial intelligence field.
Using affection computation theory and technology in Remote Education System Based On Internet, can further optimize the function of network distance education, help
The emotion change of assiatant teacher's monitoring Distance Learners, adjustment instructional strategies and method, give in real time the feedback of learner's emotion, make
Quality of instruction reaches most preferably.
Recognition of face, is a kind of biological identification technology that identification is carried out based on the facial feature information of people.With shooting
Machine or camera image of the collection containing face or video flowing, 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, do 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 contrary mood sometimes." micro- table
Feelings " flash across, and the people and observer that typically even clear-headed work is expressed one's feelings is detectable.In experiment, only 10% people examines
Feel.Compared with it is intended to knowing the expression made, " micro- expression " can more embody people really impression and motivation.
People face identification 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 to analyze the emotion of object.
The content of the invention
The problems referred to above are had based on prior art, the present invention provides a kind of long-range Emotional Teaching method, and it passes through software system
System shoots to learner, and carries out Treatment Analysis to image by webserver auxiliary, sets up people's surface model analytics
Micro- expression shape change of habit person and behavior dynamic, so as to the emotion for judging learner changes and sends prompting to teacher, realize emotion
Teaching.The method that the present invention is provided has the advantages that intelligent analysis, emotion aided education.
A kind of long-range Emotional Teaching method, it is comprised the following steps：
Step S10 is put into several classes management, and the registration information, number, the content of study according to student is put into several classes to student and arranged right
The teacher for answering is imparted knowledge to students, the client connection of pairing teaching both sides；
Step S20 careful preparation, teacher passes through teacher's client upload resources material and data of preparing lessons, when student previews to proposition
Produced problem；
Step S30 is attended class, and Faculty and Students log in respectively correspondence client, and control picture pick-up device shoots to portrait, will clap
The image taken the photograph is delivered to color analysis module, and computer adjusts shooting angle, Jiao Shihe according to color analysis module feedback at any time
Student carries out education activities simultaneously；
Step S40 color of image is analyzed, and the image information for collecting is analyzed, the color change of analysis of the image, distinguishes people
Face region and background area, and determine people face position, according to the position adjustment shooting angle in people face, make one face and be in image
Between；
Step S50 pixels statisticses are analyzed, and pixelation is carried out to image, then pixels statisticses point are carried out to the people face region in image
Analysis, to people face careful identification is carried out；
Step S60 marker characteristic point, compares with reference to the careful recognition result in people face and biological information, marks people face in image
Characteristic point；
Step S70 sets up people's surface model, and people's surface model is set up to analyzing object according to characteristic point and people's surface information, and simulation people face is special
Levy a mutation analysis；
Step S80 mood is analyzed, and is combined biological emotion-directed behavior information comparison according to the change in people face and is drawn the instantaneous of analysis object
Mood, and mood analysis result is sent to into teacher's client, remind teacher's adjustment teaching method.
Wherein, described step S30 IMAQ can be divided into the collection of step S31 still image and step S32 Dynamic Graph
As collection, execution step S40 color analysis after the collection of step S31 still image, shooting angle is adjusted；Step S32 dynamic image
Execution step S50 after collection, to people face region pixels statisticses analysis is carried out.
Wherein, the biological emotion-directed behavior information in described step S80 includes that the micro- expression information in people face and artificial action are believed
Breath.
Wherein, described step S50 pixels statisticses analysis also includes step S51, and connection interconnected server is aided in image
Carry out pixels statisticses analytical calculation.
Wherein, described analysis method also includes that step S90 big data analyzes updating maintenance, to dividing after execution step S80
Analysis result carries out big data analysis and reaffirms analysis result with reference to internet data, and according to analysis result to biological Information Number
Maintenance is updated according to storehouse.
Specific embodiment
With reference to specific embodiment, the invention will be further described.
A kind of long-range Emotional Teaching method, it is comprised the following steps：
Step S10 is put into several classes management, and the registration information, number, the content of study according to student is put into several classes to student and arranged right
The teacher for answering is imparted knowledge to students, the client connection of pairing teaching both sides；
Step S20 careful preparation, teacher passes through teacher's client upload resources material and data of preparing lessons, when student previews to proposition
Produced problem；
Step S30 is attended class, and Faculty and Students log in respectively correspondence client, and control picture pick-up device shoots to portrait, will clap
The image taken the photograph is delivered to color analysis module, and computer adjusts shooting angle, Jiao Shihe according to color analysis module feedback at any time
Student carries out education activities simultaneously；
Step S40 color of image is analyzed, and the image information for collecting is analyzed, the color change of analysis of the image, distinguishes people
Face region and background area, and determine people face position, according to the position adjustment shooting angle in people face, make one face and be in image
Between；
Step S50 pixels statisticses are analyzed, and pixelation is carried out to image, then pixels statisticses point are carried out to the people face region in image
Analysis, to people face careful identification is carried out；
Step S60 marker characteristic point, compares with reference to the careful recognition result in people face and biological information, marks people face in image
Characteristic point；
Step S70 sets up people's surface model, and people's surface model is set up to analyzing object according to characteristic point and people's surface information, and simulation people face is special
Levy a mutation analysis；
Step S80 mood is analyzed, and is combined biological emotion-directed behavior information comparison according to the change in people face and is drawn the instantaneous of analysis object
Mood, and mood analysis result is sent to into teacher's client, remind teacher's adjustment teaching method.
As the presently preferred embodiments, described step S30 IMAQ can be divided into the collection of step S31 still image and step
S32 dynamic image acquisitions, execution step S40 color analysis after the collection of step S31 still image, adjust shooting angle；Step S32
Execution step S50 after dynamic image acquisition, to people face region pixels statisticses analysis is carried out.
As the presently preferred embodiments, the biological emotion-directed behavior information in described step S80 include the micro- expression information in people face and
Artificial action message.
As the presently preferred embodiments, described step S50 pixels statisticses analysis also includes step S51, connects interconnected server
Auxiliary carries out pixels statisticses analytical calculation to image.
As the presently preferred embodiments, described analysis method also includes that step S90 big data analyzes updating maintenance, execution step
Big data analysis is carried out with reference to internet data to analysis result after S80 and reaffirms analysis result, and according to analysis result pair
Biomolecule information database is updated maintenance.
Embodiment described above only expresses one embodiment of the present invention, and its description is more concrete and detailed, but and
Therefore the restriction 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, some deformations and improvement can also be made, these belong to the guarantor of the present invention
Shield scope.Therefore, the protection domain of patent of the present invention should be defined by claims.
Claims (5)
1. a kind of long-range Emotional Teaching method, it is characterised in that it is comprised the following steps：
Step S10 is put into several classes management, and the registration information, number, the content of study according to student is put into several classes to student and arranged right
The teacher for answering is imparted knowledge to students, the client connection of pairing teaching both sides；
Step S20 careful preparation, teacher passes through teacher's client upload resources material and data of preparing lessons, when student previews to proposition
Produced problem；
Step S30 is attended class, and Faculty and Students log in respectively correspondence client, and control picture pick-up device shoots to portrait, will clap
The image taken the photograph is delivered to color analysis module, and computer adjusts shooting angle, Jiao Shihe according to color analysis module feedback at any time
Student carries out education activities simultaneously；
Step S40 color of image is analyzed, and the image information for collecting is analyzed, the color change of analysis of the image, distinguishes people
Face region and background area, and determine people face position, according to the position adjustment shooting angle in people face, make one face and be in image
Between；
Step S50 pixels statisticses are analyzed, and pixelation is carried out to image, then pixels statisticses point are carried out to the people face region in image
Analysis, to people face careful identification is carried out；
Step S60 marker characteristic point, compares with reference to the careful recognition result in people face and biological information, marks people face in image
Characteristic point；
Step S70 sets up people's surface model, and people's surface model is set up to analyzing object according to characteristic point and people's surface information, and simulation people face is special
Levy a mutation analysis；
Step S80 mood is analyzed, and is combined biological emotion-directed behavior information comparison according to the change in people face and is drawn the instantaneous of analysis object
Mood, and mood analysis result is sent to into teacher's client, remind teacher's adjustment teaching method.
2. a kind of long-range Emotional Teaching method according to claim 1, it is characterised in that described step S30 image is adopted
Collection can be divided into the collection of step S31 still image and step S32 dynamic image acquisition, perform after the collection of step S31 still image
Step S40 color analysis, adjust shooting angle；Execution step S50 after step S32 dynamic image acquisition, is carried out to people face region
Pixels statisticses are analyzed.
3. a kind of long-range Emotional Teaching method according to claim 1, it is characterised in that the life in described step S80
Principle thread behavioural information includes the micro- expression information in people face and artificial action message.
4. a kind of long-range Emotional Teaching method according to claim 1, it is characterised in that described step S50 pixel system
Meter analysis also includes step S51, and connection interconnected server auxiliary carries out pixels statisticses analytical calculation to image.
5. a kind of long-range Emotional Teaching method according to claim 1, it is characterised in that described analysis method also includes
Step S90 big data analyzes updating maintenance, and big data analysis is carried out with reference to internet data to analysis result after execution step S80
Analysis result is reaffirmed, and maintenance is updated to biomolecule information database according to analysis result.
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Cited By (5)
| 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 |
| CN108876676A (en) * | 2018-06-15 | 2018-11-23 | 四川文理学院 | A kind of robot teaching's method and system based on scene |
| CN110312098A (en) * | 2018-03-20 | 2019-10-08 | 麦奇数位股份有限公司 | Immediately monitoring method for interactive online teaching |
| CN112380261A (en) * | 2020-10-10 | 2021-02-19 | 杭州翔毅科技有限公司 | Remote tutoring method, device and system based on 5G technology and storage medium |
| CN114973957A (en) * | 2022-06-02 | 2022-08-30 | 清华大学 | Intelligent photo frame and intelligent photo frame control method |
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 CN201710130161.6A patent/CN106652605A/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 (8)
| 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 |
| 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 |
| 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 |
| CN110312098A (en) * | 2018-03-20 | 2019-10-08 | 麦奇数位股份有限公司 | Immediately monitoring method for interactive online teaching |
| CN108876676A (en) * | 2018-06-15 | 2018-11-23 | 四川文理学院 | A kind of robot teaching's method and system based on scene |
| CN112380261A (en) * | 2020-10-10 | 2021-02-19 | 杭州翔毅科技有限公司 | Remote tutoring method, device and system based on 5G technology and storage medium |
| CN114973957A (en) * | 2022-06-02 | 2022-08-30 | 清华大学 | Intelligent photo frame and intelligent photo frame control method |
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Application publication date: 20170510 |