CN104408783A - Concentration degree checking system - Google Patents
Concentration degree checking system Download PDFInfo
- Publication number
- CN104408783A CN104408783A CN201410734791.0A CN201410734791A CN104408783A CN 104408783 A CN104408783 A CN 104408783A CN 201410734791 A CN201410734791 A CN 201410734791A CN 104408783 A CN104408783 A CN 104408783A
- Authority
- CN
- China
- Prior art keywords
- person
- eye
- face image
- focus
- module
- 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.)
- Granted
Links
Classifications
-
- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C1/00—Registering, indicating or recording the time of events or elapsed time, e.g. time-recorders for work people
- G07C1/10—Registering, indicating or recording the time of events or elapsed time, e.g. time-recorders for work people together with the recording, indicating or registering of other data, e.g. of signs of identity
- G07C1/12—Registering, indicating or recording the time of events or elapsed time, e.g. time-recorders for work people together with the recording, indicating or registering of other data, e.g. of signs of identity wherein the time is indicated in figures
Abstract
The invention provides a concentration degree checking system which is used in network teaching, internet-assisted teaching research, network self-determined learning and online cooperative learning. The system comprises a camera shooting module, a first sampling module, a second sampling module, an image recognition module, a checking degree analysis module and a table generation module. According to the system, a face image of a person to be checked is acquired, and whether the person is in an eye-closing state or not is judged; the acquisition frequency is increased so as to continuously acquire the face image of the person to be checked and judge when the person is to open the eyes when detecting that the person to be checked is in the eye-closing state, thereby obtaining the time that the person to be checked closes the eyes; and finally, the eye opening time sum is counted, and a corresponding concentration degree checking table is generated. By adopting the scheme, the eye-opening or eye-closing state of the person to be checked can be clearly understood, and the concentration degree of the person in teaching activity can be judged, so that the problem that the concentration degree of students in the conventional internet teaching cannot be easily judged is overcome.
Description
Technical field
The present invention relates to a kind of Web-based instruction field, mainly refer to the area of activities such as the Web-based instruction, Promoting Network Teaching Research, Web-based Self-regulated Learning, Online Cooperative Learning, particularly relate to a kind of focus attendance checking system.
Background technology
Network, intelligent recorded broadcast, software, let us does not carry out the Web-based instruction by space-time restriction, Promoting Network Teaching Research and Web-based Self-regulated Learning, Online Cooperative Learning are movable, really be very convenient, but how to being dispersed in the teacher of different physical address, to carry out work attendance be a large problem always for student, expert, this problem is also cause these business activities on network can not the normality main cause of carrying out.
In the Web-based instruction, Promoting Network Teaching Research and Web-based Self-regulated Learning, Online Cooperative Learning activity, the roles such as each teacher, each student, expert, organizer, be in different physical addresss respectively, use different computers or other-end, often kind of role everyone do not converge to and more do not converge to work attendance before or several attendance recorders together, it is more unrealistic that everyone joins a long-range attendance recorder.Even if joined, also cannot realize carrying out detecting to the learning state of student and adding up.
Now commercially network what is called " network attendance system ", front end (i.e. work attendance point) remains installation attendance recorder, and rear end is only core---and network attendance software, i.e. Web work attendance, also known as TCP/IP work attendance.Because adopting B/S frame, also claim B/S work attendance.This network attendance system, long-rangely can carry out the management of attendance data, inquiry and report generation by network.But this work attendance mode in fact still concentrates work attendance, each personnel accepting work attendance must stand each work attendance point attendance recorder before just can complete work attendance, cannot accomplish depart from attendance recorder and carry out network remote work attendance, the long-range work attendance problem of this people one location cannot be solved, more can not realize carrying out detecting to the learning state of student each in instructional process and adding up.
Therefore, to those skilled in the art, its necessary for existing network education activities cannot to student carry out science and effectively work attendance assessment situation improve.,
Summary of the invention
The shortcoming of prior art in view of the above, the object of the present invention is to provide a kind of focus attendance checking system, for solving the problem cannot carrying out effective work attendance examination in prior art to the learning state of student in network learning procedure.
For achieving the above object and other relevant objects, the invention provides following technical scheme:
A kind of focus attendance checking system, comprising: photographing module, for obtaining the face image treating work attendance person; First sampling module, treats the face image of work attendance person by the first predeterminated frequency collection; Second sampling module, treats the face image of work attendance person by the second predeterminated frequency collection; Picture recognition module, for identifying that the eye profile in described face image is closed-eye state or eyes-open state, and set very first time timing node when first time detects the face image of closed-eye state, and when first time detects the face image of eyes-open state after described very first time timing node, set the second time timing node; Work attendance degree analysis module, according to described very first time timing node and the second time timing node, calculates closed-eye time value and the focus for the treatment of work attendance person; Form generation module, according to described closed-eye time value focus, generates focus Attendance Sheet and is exported.
In sum, can be well understood to by such scheme and treat the eye opening of work attendance person or the state of eye closing, thus judge its focus situation in education activities, overcome the problem that cannot judge student's focus in existing network education activities easily with this.
Accompanying drawing explanation
Fig. 1 is shown as a kind of focus attendance checking system of the present invention schematic diagram in one embodiment.
Description of reference numerals:
10 photographing modules
20 second sampling modules
30 first sampling modules
40 picture recognition module
50 work attendance degree analysis modules
60 form generation modules
Embodiment
Below by way of specific instantiation, embodiments of the present invention are described, those skilled in the art the content disclosed by this instructions can understand other advantages of the present invention and effect easily.The present invention can also be implemented or be applied by embodiments different in addition, and the every details in this instructions also can based on different viewpoints and application, carries out various modification or change not deviating under spirit of the present invention.It should be noted that, when not conflicting, the feature in following examples and embodiment can combine mutually.
It should be noted that, the diagram provided in following examples only illustrates basic conception of the present invention in a schematic way, then only the assembly relevant with the present invention is shown in graphic but not component count, shape and size when implementing according to reality is drawn, it is actual when implementing, and the kenel of each assembly, quantity and ratio can be a kind of change arbitrarily, and its assembly layout kenel also may be more complicated.
In order to enable those skilled in the art understand technical scheme of the present invention better, below to some technology related in scheme for giving specific explanations explanation.
The first, focus, refers to and treats whether work attendance person's eye is absorbed on teaching scene or screen, generally can utilize and ask the ratio of open eyes T.T. and education activities T.T. to obtain.
The second, eyes-open state, namely refers to by processing image, to judge that whether eyes are wherein for opening state.In like manner, corresponding thereto also have closed-eye state, it is also by processing image, to judge that whether eyes are wherein for closing state.
Particularly, see Fig. 1, show a kind of focus attendance checking system of the present invention schematic diagram in one embodiment, as shown in the figure, described focus attendance checking system comprises: photographing module 10, for obtaining the face image treating work attendance person; First sampling mould 30 pieces, treats the face image of work attendance person by the first predeterminated frequency collection; Second sampling module 20, treats the face image of work attendance person by the second predeterminated frequency collection; Picture recognition module 40, for identifying that the eye profile in described face image is closed-eye state or eyes-open state, and set very first time timing node when first time detects the face image of closed-eye state, and when first time detects the face image of eyes-open state after described very first time timing node, set the second time timing node; Work attendance degree analysis module 50, according to described very first time timing node and the second time timing node, calculates closed-eye time value and the focus for the treatment of work attendance person; Form generation module 60, according to described closed-eye time value focus, generates focus Attendance Sheet and is exported.
Can be well understood to by such scheme and treat the eye opening of work attendance person or the state of eye closing, thus judge its focus situation in education activities, overcome the problem that cannot judge student's focus in existing network education activities easily with this.
Particularly, the first predeterminated frequency in such scheme should be less than the second predeterminated frequency, such as, the first predeterminated frequency be 1 minute once, and the second predeterminated frequency is 1 minute ten times or five times, such situation can avoiding occurring failing to judge or judging by accident.Such as, when the first predeterminated frequency and the second predeterminated frequency are all 1 minute one time, when until work attendance person's collected eye closing, it just maintains 30 seconds, and just in time closed one's eyes in the 60th second, now just in time be detected again, so treat that work attendance person will be considered to close one's eyes 60 seconds, and actual conditions be really not so.If therefore raising the second predeterminated frequency is also detected according to this, so will detect in the 30th second in 30 seconds and treat that work attendance person has opened eyes, thus avoid the situation of erroneous judgement.
Also the regular hour is needed, if the too high efficiency that also will influence the course of the frequency carrying out gathering, so usually the second predeterminated frequency to be set to 5 times to about 10 times of first and radio frequency owing to carrying out processing and identification to image.
In addition, be with being to be understood that, in above-mentioned focus attendance checking system, face image is identified, judge that eyes are in opening state or closed-eye state, be make use of existing image recognition technology, this can realize the identification of above-mentioned eye state to those skilled in the art without the need to paying creative work, its application just this image recognition technology and other creative technology combined, therefore repeat no more here.
Particularly, the method for eyes-open state and closed-eye state that judges is: the height value judging eye contour in image, if be greater than default eye contour height value, is eyes-open state; If be less than or equal to default eye contour height value, it is closed-eye state.
Those skilled in the art will be allowed below by way of example clearly to understand technical scheme of the present invention, particularly:
In Learning Activity, such as Promoting Network Teaching Research, Web-based Self-regulated Learning, in the active procedures such as Online Cooperative Learning, when education activities start, if the movable start time is A0, and gather in specific time interval once treat work attendance person face image (as collection per minute once, i.e. the first predeterminated frequency), the face image collected and the face image with eyes-open state when registering are contrasted, monitor its eye profile, if treat there is eyes closed phenomenon in work attendance person, record current point in time is A1, and automatically improve picture-taken frequency (as collection per minute once changed into every 5s collection once, namely the second pre-predeterminated frequency is adopted to gather), when capture open until work attendance person's eye time, recording current point in time is A2, calculating treats that work attendance person's eye closure time is T1=A2-A1, if T1 is less than or equal to a certain limit value (as 15s), then judge that this is as rationally closed, if T1 is greater than this limit value, then judge that this is as non-rationally closed, counted eye closure time, now according to the T.T. T=(A2-A0) that current active is carried out, calculate now that this treats that the eye focus of work attendance person is H1=1-T1/T.When again or repeatedly there is eye closing phenomenon until work attendance person, calculate according to above-mentioned focus attendance checking system and treat work attendance person's eye time T1 ', then now, this treats that work attendance person's head departs from the time and adds up to T2=T1+T1 ', the T.T. T ' that current active is carried out, calculates now that this treats the eye focus H1=1-T2/T ' of work attendance person.By that analogy, visible eye focus carries out real-time change along with activity, is in the end exported with the form of focus Attendance Sheet again.
In sum, the present invention identifies by treating work attendance person's eye state, thus judge its focus for teaching screen, effectively can treat work attendance person and exercise supervision and examine, avoid in existing network education activities the blind area of carry out imparting knowledge to students work attendance or examination.So the present invention effectively overcomes various shortcoming of the prior art and tool high industrial utilization.
Above-described embodiment is illustrative principle of the present invention and effect thereof only, but not for limiting the present invention.Any person skilled in the art scholar all without prejudice under spirit of the present invention and category, can modify above-described embodiment or changes.Therefore, such as have in art usually know the knowledgeable do not depart from complete under disclosed spirit and technological thought all equivalence modify or change, must be contained by claim of the present invention.
Claims (3)
1. a focus attendance checking system, is characterized in that, comprising:
Photographing module, for obtaining the face image treating work attendance person;
First sampling module, treats the face image of work attendance person by the first predeterminated frequency collection;
Second sampling module, treats the face image of work attendance person by the second predeterminated frequency collection;
Picture recognition module, for identifying that the eye profile in described face image is closed-eye state or eyes-open state, and set very first time timing node when first time detects the face image of closed-eye state, and when first time detects the face image of eyes-open state after described very first time timing node, set the second time timing node;
Work attendance degree analysis module, according to described very first time timing node and the second time timing node, calculates closed-eye time value and the focus for the treatment of work attendance person;
Form generation module, according to described closed-eye time value focus, generates focus Attendance Sheet and is exported.
2. focus attendance checking system according to claim 1, is characterized in that, the frequency values of the second predeterminated frequency that the frequency values of described first predeterminated frequency is less than.
3. focus attendance checking system according to claim 1 and 2, is characterized in that, described second predeterminated frequency is 5 to 10 times of described first predeterminated frequency.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201410734791.0A CN104408783B (en) | 2014-12-04 | 2014-12-04 | Concentration degree checking system |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN201410734791.0A CN104408783B (en) | 2014-12-04 | 2014-12-04 | Concentration degree checking system |
Publications (2)
Publication Number | Publication Date |
---|---|
CN104408783A true CN104408783A (en) | 2015-03-11 |
CN104408783B CN104408783B (en) | 2017-02-01 |
Family
ID=52646411
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN201410734791.0A Active CN104408783B (en) | 2014-12-04 | 2014-12-04 | Concentration degree checking system |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN104408783B (en) |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106128188A (en) * | 2016-08-31 | 2016-11-16 | 华南理工大学 | Desktop education focus analyzes system and the method for analysis thereof |
CN110443506A (en) * | 2019-08-07 | 2019-11-12 | 深圳市云企汇财税顾问有限公司 | A kind of enterprise tax risk monitoring analysis system based on big data |
Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2006023506A (en) * | 2004-07-07 | 2006-01-26 | Tokai Univ | Electronic teaching material learning support device, electronic teaching material learning support system, electronic teaching material learning support method, and electronic learning support program |
US20060190419A1 (en) * | 2005-02-22 | 2006-08-24 | Bunn Frank E | Video surveillance data analysis algorithms, with local and network-shared communications for facial, physical condition, and intoxication recognition, fuzzy logic intelligent camera 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 |
KR20100016696A (en) * | 2008-08-05 | 2010-02-16 | 주식회사 리얼맨토스 | Student learning attitude analysis systems in virtual lecture |
CN102013176A (en) * | 2010-12-01 | 2011-04-13 | 曹乃承 | Online learning system |
CN102201148A (en) * | 2011-05-25 | 2011-09-28 | 北京航空航天大学 | Driver fatigue detecting method and system based on vision |
CN102340686A (en) * | 2011-10-11 | 2012-02-01 | 杨海 | Method and device for detecting attentiveness of online video viewer |
CN103679591A (en) * | 2012-09-25 | 2014-03-26 | 山东博学教育软件科技有限公司 | Remote learning state monitoring system and method |
-
2014
- 2014-12-04 CN CN201410734791.0A patent/CN104408783B/en active Active
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2006023506A (en) * | 2004-07-07 | 2006-01-26 | Tokai Univ | Electronic teaching material learning support device, electronic teaching material learning support system, electronic teaching material learning support method, and electronic learning support program |
US20060190419A1 (en) * | 2005-02-22 | 2006-08-24 | Bunn Frank E | Video surveillance data analysis algorithms, with local and network-shared communications for facial, physical condition, and intoxication recognition, fuzzy logic intelligent camera system |
KR20100016696A (en) * | 2008-08-05 | 2010-02-16 | 주식회사 리얼맨토스 | Student learning attitude analysis systems in virtual lecture |
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 |
CN102013176A (en) * | 2010-12-01 | 2011-04-13 | 曹乃承 | Online learning system |
CN102201148A (en) * | 2011-05-25 | 2011-09-28 | 北京航空航天大学 | Driver fatigue detecting method and system based on vision |
CN102340686A (en) * | 2011-10-11 | 2012-02-01 | 杨海 | Method and device for detecting attentiveness of online video viewer |
CN103679591A (en) * | 2012-09-25 | 2014-03-26 | 山东博学教育软件科技有限公司 | Remote learning state monitoring system and method |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106128188A (en) * | 2016-08-31 | 2016-11-16 | 华南理工大学 | Desktop education focus analyzes system and the method for analysis thereof |
CN110443506A (en) * | 2019-08-07 | 2019-11-12 | 深圳市云企汇财税顾问有限公司 | A kind of enterprise tax risk monitoring analysis system based on big data |
Also Published As
Publication number | Publication date |
---|---|
CN104408783B (en) | 2017-02-01 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
CN104408781A (en) | Concentration attendance system | |
CN110945522B (en) | Learning state judging method and device and intelligent robot | |
CN110197169B (en) | Non-contact learning state monitoring system and learning state detection method | |
CN108229376B (en) | Method and device for detecting blinking | |
CN109977903A (en) | The method, apparatus and computer storage medium of a kind of wisdom classroom student-directed | |
CN111726586A (en) | Production system operation standard monitoring and reminding system | |
CN105335727B (en) | The identity authorization system and method analyzed based on image and body-sensing | |
Hu et al. | Research on abnormal behavior detection of online examination based on image information | |
CN104751110A (en) | Bio-assay detection method and device | |
CN108898079A (en) | A kind of monitoring method and device, storage medium, camera terminal | |
Abdulkader et al. | Optimizing student engagement in edge-based online learning with advanced analytics | |
CN112613780B (en) | Method and device for generating learning report, electronic equipment and storage medium | |
CN109086693A (en) | A kind of detection technique of online teaching study attention | |
CN103108163A (en) | Network course learning and examination anti-cheating monitoring system and device | |
CN103617421A (en) | Fatigue detecting method and system based on comprehensive video feature analysis | |
CN109410098A (en) | A kind of student classroom behavioural analysis and monitoring method | |
CN105105738A (en) | Information processing method and device and electronic device | |
CN110598633A (en) | Tumble behavior identification method, device and system | |
CN203118082U (en) | Network course learning and examination anti-cheating monitoring device | |
CN104408782A (en) | Facial visibility attendance system | |
CN109472464A (en) | A kind of appraisal procedure of the online course quality based on eye movement tracking | |
CN104408783A (en) | Concentration degree checking system | |
CN109118512A (en) | A kind of classroom based on machine vision is come to work late and leave early detection method | |
CN113536893A (en) | Online teaching learning concentration degree identification method, device, system and medium | |
CN108492231A (en) | The monitoring system of class efficacy information based on students ' behavior data |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
C06 | Publication | ||
PB01 | Publication | ||
C10 | Entry into substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
C14 | Grant of patent or utility model | ||
GR01 | Patent grant |