CN104408782A - Facial visibility attendance system - Google Patents

Facial visibility attendance system Download PDF

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Publication number
CN104408782A
CN104408782A CN201410734317.8A CN201410734317A CN104408782A CN 104408782 A CN104408782 A CN 104408782A CN 201410734317 A CN201410734317 A CN 201410734317A CN 104408782 A CN104408782 A CN 104408782A
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CN
China
Prior art keywords
time
attendance
predeterminated frequency
work attendance
face
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CN201410734317.8A
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Chinese (zh)
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CN104408782B (en
Inventor
涂勇
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CHONGQING JINCAI FUXI TECHNOLOGY Co Ltd
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CHONGQING JINCAI FUXI TECHNOLOGY Co Ltd
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Publication of CN104408782A publication Critical patent/CN104408782A/en
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    • GPHYSICS
    • G07CHECKING-DEVICES
    • G07CTIME 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
    • G07C1/00Registering, indicating or recording the time of events or elapsed time, e.g. time-recorders for work people
    • G07C1/10Registering, 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
    • G07C1/16Registering, 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 by marking an element, e.g. a card or tape, in a position determined by the time

Abstract

The invention provides a facial visibility attendance system. The facial visibility attendance system is applied to the fields of remote network instruction, network match, network training, network meeting, network self-determined learning, network cooperative learning activity and the like. According to the facial visibility attendance system, through prestored front face figures of persons to be attended, the real-time face figures of the persons to be attended are contrasted with front face figures in a database according to a preset frequency in an activity so as to judge whether the persons to be attended are watching the screen, and thus corresponding data calculation is carried out by continuously setting corresponding time nodes and calculating time differences in an attendance process, and a facial visibility attendance table is generated and output when the activity is finished. The facial visibility of the persons to be attended is counted through the facial visibility attendance system, and thus the time of the persons to be attended facing the screen is clearly known, so that the serious degree of learning is known; meanwhile, the effect of remote supervision is achieved.

Description

Face diopter attendance checking system
Technical field
The present invention relates to a kind of application of image recognition, mainly refer to and utilize image recognition to realize the method for e-learning work attendance, especially relate to a kind of face diopter 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 distance network teaching, network contest class, online training, Web conference, 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, detect and statistics from rate, face diopter, focus, interactive degree in also cannot realizing.
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---network attendance software, i.e. Web work attendance (also known as TCP/IP work attendance).Because adopting B/S framework, (also claiming 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, detect and statistics from rate, face diopter, focus, interactive degree in cannot solving or realize.
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 face diopter attendance checking system, for solving the problem that cannot realize face diopter work attendance statistics in existing network attendance checking system.
For achieving the above object and other relevant objects, the invention provides following technical scheme:
A kind of face diopter attendance checking system, comprising: image collection module, for gathering the frontal faces figure treating work attendance person; Database module, for treating the frontal faces figure of work attendance person described in prestoring; First sampling module, for catching the real-time face figure treating work attendance person by the first predeterminated frequency, and is exported; Second sampling module, for catching the real-time face figure treating work attendance person by the second predeterminated frequency, and is exported; Comparing module, for comparing by the frontal faces figure in the first predeterminated frequency or the real-time face figure treating work attendance person caught by the second predeterminated frequency and described database, and set very first time node when described real-time face figure and described frontal faces figure first time does not match, and set the second timing node when described real-time face figure and described frontal faces figure first time matches after described very first time node; Computing module, calculates the time difference of described second timing node and described very first time node, and is stored output; Form generation module, for adding up all time differences and process, to generate face diopter Attendance Sheet and to be exported.
Preferably, in above-mentioned diopter attendance checking system, described comparing module, also for catching the real-time face figure treating work attendance person in end device dead ahead by the first predeterminated frequency, when first time gets real-time face figure, sets the 3rd timing node.
Preferably, in above-mentioned diopter attendance checking system, described comparing module, also for after described 3rd timing node, catches the real-time face figure treating work attendance person less than end device dead ahead by described first predeterminated frequency or the second predeterminated frequency, stops work attendance and sets the 4th timing node.
Preferably, in above-mentioned diopter attendance checking system, described computing module also for adding up described 3rd timing node and the 4th timing node, with treat described in obtaining work attendance person always in the diligent time.
Preferably, in above-mentioned diopter attendance checking system, described first predeterminated frequency is less than the second predeterminated frequency.
Preferably, in above-mentioned diopter attendance checking system, described second predeterminated frequency is 5 to 10 times of described first predeterminated frequency.
In sum, the present invention, by described diopter attendance checking system, to treating that work attendance person carries out the statistics of face diopter before end device, thus knows clearly its time in the face of screen, understand the conscientious degree of its study with this, reach the effect of remote supervisory simultaneously.
Accompanying drawing explanation
Fig. 1 is shown as the schematic diagram in a kind of enforcement of face of the present invention diopter attendance checking system.
Drawing reference numeral explanation
100 image collection module
200 first sampling modules
300 second sampling modules
400 contrast modules
500 database module
600 computing modules
700 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 technical scheme of the present invention is set forth clear, be used for explaining to some technology hereinafter below, to enable those skilled in the art to implement whole technical scheme of the present invention better.
Face diopter, mainly refers to the time of the long-range work attendance person for the treatment of front terminaloriented device, is using enforcement end device to carry out the T.T. spent by work or study and departing from the time ratios etc. of end device/front terminaloriented device.
See Fig. 1, show the schematic diagram in a kind of enforcement of face of the present invention diopter attendance checking system, as shown in the figure, described diopter attendance checking system comprises:
Image collection module 100, for gathering the frontal faces figure treating work attendance person; Database module 500, for treating the frontal faces figure of work attendance person described in prestoring; First sampling module 200, for catching the real-time face figure treating work attendance person by the first predeterminated frequency, and is exported; Second sampling module 300, for catching the real-time face figure treating work attendance person by the second predeterminated frequency, and is exported; Comparing module, for comparing by the frontal faces figure in the first predeterminated frequency or the real-time face figure treating work attendance person caught by the second predeterminated frequency and described database, and set very first time node when described real-time face figure and described frontal faces figure first time does not match, and set the second timing node when described real-time face figure and described frontal faces figure first time matches after described very first time node; Computing module 600, calculates the time difference of described second timing node and described very first time node, and is stored output; Form generation module 700, for adding up all time differences and process, to generate face diopter Attendance Sheet and to be exported.
Further, in described contrast module 400, can also be used for, always in the statistics of diligent time, namely catching the real-time face figure treating work attendance person in end device dead ahead by the first predeterminated frequency, when first time gets real-time face figure, setting the 3rd timing node.In addition, then catch the real-time face figure treating work attendance person less than end device dead ahead by described first predeterminated frequency or the second predeterminated frequency, stop work attendance and set the 4th timing node.
In acquisition always after the diligent time, the ratio that can also will obtain always in diligent time and work attendance T.T., wherein, is generally the real time of described education activities described work attendance T.T..
Particularly, in said system, described first predeterminated frequency is less than the second predeterminated frequency, carry out rapid detection with this and treat whether the face of work attendance person is got back on screen cover, thus reduction False Rate, if the second predeterminated frequency is too low, so likely treats that work attendance person has looked back at screen and again left and do not obtained by detecting, cause the inaccuracy of checking-in result.Usually, described second predeterminated frequency can be set to 5 to 10 times of described first predeterminated frequency.
Further, below for the first predeterminated frequency be one minute 1 time, the second predeterminated frequency is be described the course of work of above-mentioned diopter attendance checking system for five seconds 1 time.
First, first in database module 500, prestore the direct picture treating work attendance person obtained by image collection module 100, thus form the database treating work attendance person.
Then, in the Web-based instruction, Promoting Network Teaching Research, network contest class, online training, Web conference, Web-based Self-regulated Learning, in Online Cooperative Learning active procedure, when starting to learn, by the first sampling module 200, real-time face figure collection is carried out according to one minute 1 time (the first predeterminated frequency), and utilize described contrast module 400 to be contrasted by the frontal faces figure in the real-time face figure collected and database, judge to treat that whether work attendance person is at viewing screen content with this, and when first time gets real-time face figure, set the 3rd timing node A0, also activity can be started set of time is the 3rd timing node, in addition, if treat there is head off-set phenomenon in work attendance person, and record current point in time is A1, and automatically improve the frequency implemented face figure and gather.Namely by the second sampling module 300, gather with the frequency that 5s gathers once, turn back to front when capturing when the position of screen until work attendance person's head, recording current point in time is A2, and calculating and treating that work attendance person's head departs from the time is T1=A2-A1, if T1 is less than a certain limit value (as 15s), then judge that this departs from as reasonable head, be not counted in head and depart from the time, otherwise, judge that this rationally departs from as non-, counted head and depart from the time.Then, the T.T. T=(A2-A0) now utilizing computing module 600 to carry out according to current active, calculates now that this treats that the face diopter of work attendance person is M=1-T1/T.When again or repeatedly there is head off-set phenomenon until work attendance person, said method calculating is installed and treats that work attendance person's head departs from 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 face diopter M=1-T2/T ' of work attendance person.By that analogy, visible face diopter carries out real-time change along with activity, finally when activity end, recorded various time results is added up by form generation module 700, to generate face diopter Attendance Sheet, and is exported.
In sum, the present invention by described diopter attendance checking system, to treating that work attendance person carries out the statistics of face diopter before end device, thus knows clearly its time in the face of screen by the present invention, understand the conscientious degree of its study with this, reach the effect of remote supervisory simultaneously.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 (6)

1. a face diopter attendance checking system, is characterized in that, comprising:
Image collection module, for gathering the frontal faces figure treating work attendance person;
Database module, for treating the frontal faces figure of work attendance person described in prestoring;
First sampling module, for catching the real-time face figure treating work attendance person by the first predeterminated frequency, and is exported;
Second sampling module, for catching the real-time face figure treating work attendance person by the second predeterminated frequency, and is exported;
Comparing module, for comparing by the frontal faces figure in the first predeterminated frequency or the real-time face figure treating work attendance person caught by the second predeterminated frequency and described database, and set very first time node when described real-time face figure and described frontal faces figure first time does not match, and set the second timing node when described real-time face figure and described frontal faces figure first time matches after described very first time node;
Computing module, calculates the time difference of described second timing node and described very first time node, and is stored output;
Form generation module, for adding up all time differences and process, to generate face diopter Attendance Sheet and to be exported.
2. according to claim 1 diopter attendance checking system, it is characterized in that, described comparing module, also for catching the real-time face figure treating work attendance person in end device dead ahead by the first predeterminated frequency, when first time gets real-time face figure, sets the 3rd timing node.
3. according to claim 2 diopter attendance checking system, it is characterized in that, described comparing module is also for after described 3rd timing node, catch the real-time face figure treating work attendance person less than end device dead ahead by described first predeterminated frequency or the second predeterminated frequency, stop work attendance and set the 4th timing node.
4. according to claim 3 diopter attendance checking system, it is characterized in that, described computing module also for adding up described 3rd timing node and the 4th timing node, with treat described in obtaining work attendance person always in the diligent time always at the ratio of diligent time and work attendance T.T..
5. according to claim 1 and 2 diopter attendance checking system, is characterized in that, described first predeterminated frequency is less than the second predeterminated frequency.
6. according to claim 5 diopter attendance checking system, is characterized in that, described second predeterminated frequency is 5 to 10 times of described first predeterminated frequency.
CN201410734317.8A 2014-12-04 2014-12-04 Facial visibility attendance system Active CN104408782B (en)

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Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105491355A (en) * 2016-01-28 2016-04-13 江苏科技大学 Student class monitoring system based on mobile phone image acquisition and monitoring method thereof
CN106710020A (en) * 2016-12-05 2017-05-24 广州日滨科技发展有限公司 Intelligent attendance checking method and system
CN109819195A (en) * 2017-11-22 2019-05-28 重庆晋才富熙科技有限公司 Wisdom conference system
CN109819196A (en) * 2017-11-22 2019-05-28 重庆晋才富熙科技有限公司 Benefit based on meeting can method and system

Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
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
JP4631014B2 (en) * 2004-07-07 2011-02-16 学校法人東海大学 Electronic teaching material learning support device, electronic teaching material learning support system, electronic teaching material learning support method, and electronic learning support program
CN102013176A (en) * 2010-12-01 2011-04-13 曹乃承 Online learning system
CN102332094A (en) * 2011-10-24 2012-01-25 西安电子科技大学 Semi-supervised online study face detection method
CN102340686A (en) * 2011-10-11 2012-02-01 杨海 Method and device for detecting attentiveness of online video viewer
CN102799893A (en) * 2012-06-15 2012-11-28 北京理工大学 Method for processing monitoring video in examination room
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

Patent Citations (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP4631014B2 (en) * 2004-07-07 2011-02-16 学校法人東海大学 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
CN102340686A (en) * 2011-10-11 2012-02-01 杨海 Method and device for detecting attentiveness of online video viewer
CN102332094A (en) * 2011-10-24 2012-01-25 西安电子科技大学 Semi-supervised online study face detection method
CN102799893A (en) * 2012-06-15 2012-11-28 北京理工大学 Method for processing monitoring video in examination room
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 (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105491355A (en) * 2016-01-28 2016-04-13 江苏科技大学 Student class monitoring system based on mobile phone image acquisition and monitoring method thereof
CN106710020A (en) * 2016-12-05 2017-05-24 广州日滨科技发展有限公司 Intelligent attendance checking method and system
CN106710020B (en) * 2016-12-05 2019-01-11 日立楼宇技术(广州)有限公司 Intelligent Checking on Work Attendance method and system
CN109819195A (en) * 2017-11-22 2019-05-28 重庆晋才富熙科技有限公司 Wisdom conference system
CN109819196A (en) * 2017-11-22 2019-05-28 重庆晋才富熙科技有限公司 Benefit based on meeting can method and system

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