CN109685007A - Method for early warning, user equipment, storage medium and the device being accustomed to eye - Google Patents
Method for early warning, user equipment, storage medium and the device being accustomed to eye Download PDFInfo
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- CN109685007A CN109685007A CN201811588201.2A CN201811588201A CN109685007A CN 109685007 A CN109685007 A CN 109685007A CN 201811588201 A CN201811588201 A CN 201811588201A CN 109685007 A CN109685007 A CN 109685007A
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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
- G06V40/161—Detection; Localisation; Normalisation
- G06V40/166—Detection; Localisation; Normalisation using acquisition arrangements
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
- G06N3/045—Combinations of networks
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/08—Learning methods
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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
- G06V40/103—Static body considered as a whole, e.g. static pedestrian or occupant recognition
-
- 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
- G06V40/18—Eye characteristics, e.g. of the iris
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Abstract
The invention discloses the method for early warning being accustomed to eye, user equipment, storage medium and devices.Image taking is carried out to predeterminable area according to predetermined period in the present invention, to obtain image to be analyzed；User's sitting posture information corresponding with each pre-set user is determined according to the image to be analyzed, and the pre-set user is in the spatial dimension of the predeterminable area；User's sitting posture information is matched with default sitting posture posture；It when user's sitting posture information and the default sitting posture posture mismatch, generates first and uses eye warning information, to carry out the early warning of bad eye habit with eye warning information by described first.Multiple pre-set users can be existed simultaneously in the predeterminable area shot in the present invention, and, the matching of sitting posture posture can be carried out simultaneously and then provides warning information, also it can be monitored early warning for more people simultaneously, solves the technical issues of monitoring and early warning mode being accustomed to eye cannot be monitored early warning for more people simultaneously.
Description
Technical field
The present invention relates to monitoring and early warning technology fields, more particularly to method for early warning, the user equipment, storage Jie be accustomed to eye
Matter and device.
Background technique
In view of larger with ametropic number of patients proportion in Chinese total population, moreover, ametropia
Clinical manifestation largely show as myopia.For children and teenager, abnormal sitting posture is really and with mistake between at the moment
Length is the main reason for causing myopia.
As it can be seen that if teen-age being monitored in real time to children and with eye habit, timely early warning and being effectively prevented, Ke Yiming
The illness rate of myopia is reduced aobviously.
But most monitoring and early warning modes being accustomed to eye are used only for single student, for example, the wearable eye of student
Mirror carries out the monitoring and early warning being accustomed to eye, and the equipment installed on student's desktop is monitored early warning, can not be directed to simultaneously
Multiple students.
So there is the technology that cannot be monitored early warning for more people simultaneously and ask in the monitoring and early warning mode being accustomed to eye
Topic.
Above content is only used to facilitate the understanding of the technical scheme, and is not represented and is recognized that above content is existing skill
Art.
Summary of the invention
The main purpose of the present invention is to provide the method for early warning being accustomed to eye, user equipment, storage medium and device, purports
The technical issues of the monitoring and early warning mode that solution is accustomed to eye cannot be monitored early warning for more people simultaneously.
To achieve the above object, the present invention provides a kind of method for early warning being accustomed to eye, the pre- police being accustomed to eye
Method the following steps are included:
Image taking is carried out to predeterminable area according to predetermined period, to obtain image to be analyzed；
User's sitting posture information corresponding with each pre-set user, the pre-set user are determined according to the image to be analyzed
In spatial dimension in the predeterminable area；
User's sitting posture information is matched with default sitting posture posture；
When user's sitting posture information and the default sitting posture posture mismatch, generates first and use eye warning information, with
The early warning of bad eye habit is carried out with eye warning information by described first.
Preferably, described that image taking, after obtaining image to be analyzed, institute are carried out to predeterminable area according to predetermined period
State the method for early warning being accustomed to eye further include:
Pre-set user group is read from the first pre-set user information database, and determines that the pre-set user is intragroup
Each pre-set user.
Preferably, it is described according to the image to be analyzed determine corresponding with each pre-set user user's sitting posture information it
Afterwards, the method for early warning being accustomed to eye further include:
It is determined according to the sitting posture change moment in user's sitting posture information corresponding continuous at the moment growing；
It continuous is compared described at the moment long with presetting at the moment long range；
It is described it is continuous with it is at the moment long be not at it is described it is default at the moment long range when, generate second and believed with eye early warning
Breath, to carry out the early warning of bad eye habit with eye warning information by described second.
Preferably, it is described it is described it is continuous with it is at the moment long be not at it is default at the moment long range when, generate second and use eye
Warning information, after carrying out the early warning that bad eye is accustomed to eye warning information by described second, what the eye was accustomed to
Method for early warning further include:
The userspersonal information of pre-set user is read from the second pre-set user information database；
According to the userspersonal information, user's sitting posture information, user's sitting posture information and the default sitting posture
Posture carry out matched matching result, it is described it is continuous with it is at the moment long and it is described it is continuous at the moment length with it is described default at the moment growing
The comparison result generation eye statistical report that range is compared.
It is preferably, described that user's sitting posture information corresponding with each pre-set user is determined according to the image to be analyzed,
Include:
The default facial image of pre-set user is read from third pre-set user information database；
The identification pre-set user corresponding with the default facial image in the image to be analyzed；
The image to be analyzed is split according to the default facial image, it is corresponding with the pre-set user to obtain
Pose presentation to be analyzed；
The pose presentation to be analyzed is inputted into default training convolutional neural networks, to obtain the default training convolutional mind
The user's sitting posture information corresponding with the pre-set user exported through network.
Preferably, described that image taking, before obtaining image to be analyzed, institute are carried out to predeterminable area according to predetermined period
State the method for early warning being accustomed to eye further include:
Image taking is carried out to predeterminable area, to obtain sample image；
The default facial image of pre-set user is identified in the sample image；
The sample image is split according to the default facial image of the pre-set user, is preset with obtaining with described
The corresponding sample pose presentation of user；
It is trained by the sample pose presentation to initial convolutional neural networks are preset, with default after being trained
Initial convolutional neural networks, and the default initial convolutional neural networks after training are regarded as into default training convolutional neural networks.
Preferably, described that the sample image is split according to the default facial image of the pre-set user, to obtain
After obtaining sample pose presentation corresponding with the pre-set user, the method for early warning being accustomed to eye further include:
Obtain label information；
The sample pose presentation is labeled as by the label information to preset the standard in initial convolutional neural networks
Pose presentation；
It is described to be trained by the sample pose presentation to initial convolutional neural networks are preset, after being trained
Initial convolutional neural networks are preset, and the default initial convolutional neural networks after training are regarded as into default training convolutional nerve net
Network, comprising:
It is trained by the standard pose presentation to initial convolutional neural networks are preset, with default after being trained
Initial convolutional neural networks, and the default initial convolutional neural networks after training are regarded as into default training convolutional neural networks.
In addition, to achieve the above object, the present invention also proposes a kind of user equipment, the user equipment include camera,
Memory, processor and the early warning program being accustomed to eye that is stored on the memory and can run on the processor,
The early warning program being accustomed to eye is arranged for carrying out the step of method for early warning of eye habit as described above.
In addition, to achieve the above object, the present invention also proposes a kind of storage medium, useful eye is stored on the storage medium
The early warning program of habit, the early warning program being accustomed to eye is realized when being executed by processor as described above to be accustomed to eye
The step of method for early warning.
In addition, to achieve the above object, the present invention also proposes a kind of prior-warning device being accustomed to eye, what the eye was accustomed to
Prior-warning device includes:
Image taking module, for carrying out image taking to predeterminable area according to predetermined period, to obtain image to be analyzed；
Sitting posture determining module, for determining user's sitting posture corresponding with each pre-set user according to the image to be analyzed
Information, the pre-set user are in the spatial dimension of the predeterminable area；
Sitting posture matching module, for matching user's sitting posture information with default sitting posture posture；
With eye warning module, for when user's sitting posture information and the default sitting posture posture mismatch, generating the
One uses eye warning information, to carry out the early warning of bad eye habit with eye warning information by described first.
Image taking first will be carried out to predeterminable area in the present invention, to obtain image to be analyzed, further according to image to be analyzed
It determines user's sitting posture information corresponding with each pre-set user, user's sitting posture information is matched with default sitting posture posture,
It when user's sitting posture information and default sitting posture posture mismatch, generates first and uses eye warning information, to use eye early warning by first
Information carries out the bad early warning being accustomed to eye.It is apparent that can be existed simultaneously in the predeterminable area shot in the present invention multiple default
User, also, the present invention can carry out simultaneously sitting posture posture matching so that provide warning information, also can simultaneously for more people into
Row monitoring and early warning, the technology that early warning cannot be monitored for more people simultaneously by solving the monitoring and early warning mode being accustomed to eye are asked
Topic.
Detailed description of the invention
Fig. 1 is the user device architecture schematic diagram for the hardware running environment that the embodiment of the present invention is related to；
Fig. 2 is the flow diagram for the method for early warning first embodiment that the present invention is accustomed to eye；
Fig. 3 is the flow diagram for the method for early warning second embodiment that the present invention is accustomed to eye；
Fig. 4 is the flow diagram for the method for early warning 3rd embodiment that the present invention is accustomed to eye；
Fig. 5 is the structural block diagram for the prior-warning device first embodiment that the present invention is accustomed to eye.
The embodiments will be further described with reference to the accompanying drawings for the realization, the function and the advantages of the object of the present invention.
Specific embodiment
It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, it is not intended to limit the present invention.
Referring to Fig.1, Fig. 1 is the user device architecture schematic diagram for the hardware running environment that the embodiment of the present invention is related to.
As shown in Figure 1, the user equipment may include: processor 1001, such as CPU, communication bus 1002, user interface
1003, network interface 1004, memory 1005.Wherein, communication bus 1002 is for realizing the connection communication between these components.
User interface 1003 may include display screen (Display), optional user interface 1003 can also include standard wireline interface,
Wireless interface, the wireline interface for user interface 1003 can be USB interface in the present invention.Network interface 1004 optionally may be used
To include standard wireline interface and wireless interface (such as WI-FI interface).Memory 1005 can be high speed RAM memory, can also
To be stable memory (non-volatile memory), such as magnetic disk storage.Memory 1005 optionally can also be
Independently of the storage device of aforementioned processor 1001.
It will be understood by those skilled in the art that structure shown in Fig. 1 does not constitute the restriction to user equipment, can wrap
It includes than illustrating more or fewer components, perhaps combines certain components or different component layouts.
As shown in Figure 1, as may include that operating system, network are logical in a kind of memory 1005 of computer storage medium
Believe module, Subscriber Interface Module SIM and the early warning program being accustomed to eye.
In user equipment shown in Fig. 1, network interface 1004 is mainly used for connecting background server, takes with the backstage
Business device carries out data communication；User interface 1003 is mainly used for connecting peripheral hardware；The user equipment is called by processor 1001
The early warning program being accustomed to eye stored in memory 1005, and execute following operation:
Image taking is carried out to predeterminable area according to predetermined period, to obtain image to be analyzed；
User's sitting posture information corresponding with each pre-set user, the pre-set user are determined according to the image to be analyzed
In spatial dimension in the predeterminable area；
User's sitting posture information is matched with default sitting posture posture；
When user's sitting posture information and the default sitting posture posture mismatch, generates first and use eye warning information, with
The early warning of bad eye habit is carried out with eye warning information by described first.
Further, processor 1001 can call the early warning program being accustomed to eye stored in memory 1005, also hold
The following operation of row:
Pre-set user group is read from the first pre-set user information database, and determines that the pre-set user is intragroup
Each pre-set user.
Further, processor 1001 can call the early warning program being accustomed to eye stored in memory 1005, also hold
The following operation of row:
It is determined according to the sitting posture change moment in user's sitting posture information corresponding continuous at the moment growing；
It continuous is compared described at the moment long with presetting at the moment long range；
It is described it is continuous with it is at the moment long be not at it is described it is default at the moment long range when, generate second and believed with eye early warning
Breath, to carry out the early warning of bad eye habit with eye warning information by described second.
Further, processor 1001 can call the early warning program being accustomed to eye stored in memory 1005, also hold
The following operation of row:
The userspersonal information of pre-set user is read from the second pre-set user information database；
According to the userspersonal information, user's sitting posture information, user's sitting posture information and the default sitting posture
Posture carry out matched matching result, it is described it is continuous with it is at the moment long and it is described it is continuous at the moment length with it is described default at the moment growing
The comparison result generation eye statistical report that range is compared.
Further, processor 1001 can call the early warning program being accustomed to eye stored in memory 1005, also hold
The following operation of row:
The default facial image of pre-set user is read from third pre-set user information database；
The identification pre-set user corresponding with the default facial image in the image to be analyzed；
The image to be analyzed is split according to the default facial image, it is corresponding with the pre-set user to obtain
Pose presentation to be analyzed；
The pose presentation to be analyzed is inputted into default training convolutional neural networks, to obtain the default training convolutional mind
The user's sitting posture information corresponding with the pre-set user exported through network.
Further, processor 1001 can call the early warning program being accustomed to eye stored in memory 1005, also hold
The following operation of row:
Image taking is carried out to predeterminable area, to obtain sample image；
The default facial image of pre-set user is identified in the sample image；
The sample image is split according to the default facial image of the pre-set user, is preset with obtaining with described
The corresponding sample pose presentation of user；
It is trained by the sample pose presentation to initial convolutional neural networks are preset, with default after being trained
Initial convolutional neural networks, and the default initial convolutional neural networks after training are regarded as into default training convolutional neural networks.
Further, processor 1001 can call the early warning program being accustomed to eye stored in memory 1005, also hold
The following operation of row:
Obtain label information；
The sample pose presentation is labeled as by the label information to preset the standard in initial convolutional neural networks
Pose presentation；
Correspondingly, following operation is also executed:
It is trained by the standard pose presentation to initial convolutional neural networks are preset, with default after being trained
Initial convolutional neural networks, and the default initial convolutional neural networks after training are regarded as into default training convolutional neural networks.
Image taking first will be carried out to predeterminable area in the present embodiment, to obtain image to be analyzed, further according to figure to be analyzed
As determining user's sitting posture information corresponding with each pre-set user, by user's sitting posture information and the progress of default sitting posture posture
Match, when user's sitting posture information and default sitting posture posture mismatch, generate first and use eye warning information, with pre- with eye by first
Alert information carries out the bad early warning being accustomed to eye.It is apparent that can be existed simultaneously in the predeterminable area shot in the present embodiment multiple
Pre-set user, also, the present embodiment can carry out the matching of sitting posture posture simultaneously and then provide warning information, can also be directed to simultaneously
More people are monitored early warning, solve the skill that the monitoring and early warning mode being accustomed to eye cannot be monitored early warning for more people simultaneously
Art problem.
Based on above-mentioned hardware configuration, the embodiment for the method for early warning that the present invention is accustomed to eye is proposed.
It is the flow diagram for the method for early warning first embodiment that the present invention is accustomed to eye referring to Fig. 2, Fig. 2.
In the first embodiment, it is described with eye be accustomed to method for early warning the following steps are included:
Step S10: image taking is carried out to predeterminable area according to predetermined period, to obtain image to be analyzed.
It is understood that in view of wearable device can be used to carry out the monitoring and early warning being accustomed to eye, Yong Huye for user
Monitoring device can be installed on the table come carry out with eye be accustomed to monitoring and early warning, still, these monitoring and early warning modes simultaneously only
It can implement for a people, more people cannot be directed to simultaneously.If being intended to simultaneously for more people, these modes are more numb on the implementation
It is tired, and higher cost.
It should be understood that the present embodiment will be shot simultaneously into more people when shooting image to be analyzed, and monitor simultaneously more
People's is accustomed to eye, also just plays while being monitored for more people the effect of early warning.Also, any set is worn also without user
It is standby, implement relatively simple.
In the concrete realization, the executing subject of the present embodiment is user equipment, includes camera, camera in user equipment
It can be high-definition camera.If by the user equipment applications under the scene in classroom, the blackboard that camera can be set in classroom
Near, so that camera can face the front of students, face and the sitting posture of students can be taken.
It should be understood that predeterminable area is the classroom environment that camera faces when applicable scene is classroom, preset
Period can be ten seconds for interval, then camera can take the photograph a picture every ten second beats against classroom environment, shot with obtaining into student
Classroom picture, that is, image to be analyzed.
Certainly, it is picture or video that the present embodiment, which is not intended to limit the image to be analyzed shot,.It, can if obtaining video
Each frame in video is intercepted, to obtain picture.
Step S20: determining user's sitting posture information corresponding with each pre-set user according to the image to be analyzed, described
Pre-set user is in the spatial dimension of the predeterminable area.
It is understood that due to having shot the image into multiple students in the picture of classroom, to may recognize that multiple
Raw sitting posture, and it is recorded as user's sitting posture information of each student.Wherein, user's sitting posture information record has the sitting posture of pre-set user
Information.
Step S30: user's sitting posture information is matched with default sitting posture posture.
It should be understood that for the ease of identify incorrect sitting-pose in turn result in it is undesirable be accustomed to eye, can be preset
The default sitting posture posture of good sitting position is regarded as, default sitting posture posture can refer to common good sitting position requirement.For example, can will be pre-
If sitting posture posture is set as, the upper part of the body of user's body is upright and eyes of user is apart from one ruler of desktop etc..
It is understood that the user's sitting posture information that can be will acquire is matched with the default sitting posture posture, if user
The upper half of the user's body recorded in sitting posture information as upright and eyes of user really apart from one ruler of desktop, then it is believed that matching
Success, user's sitting posture is good, is not necessarily to early warning；If different from default sitting posture posture, can regard as mismatching.
Step S40: it when user's sitting posture information and the default sitting posture posture mismatch, generates first and uses eye early warning
Information, to carry out the early warning of bad eye habit with eye warning information by described first.
It is understood that producing first when mismatching and using eye warning information, first is recordable with eye warning information
There is the prompt information of the student true to abnormal sitting posture.First can be displayed in preset web with eye warning information, for student or
Teacher's person reading can also provide decision data and support, and then carry out to undesirable student is accustomed to eye for school and relevant departments
Early warning.
Image taking first will be carried out to predeterminable area in the present embodiment, to obtain image to be analyzed, further according to figure to be analyzed
As determining user's sitting posture information corresponding with each pre-set user, by user's sitting posture information and the progress of default sitting posture posture
Match, when user's sitting posture information and default sitting posture posture mismatch, generate first and use eye warning information, with pre- with eye by first
Alert information carries out the bad early warning being accustomed to eye.It is apparent that can be existed simultaneously in the predeterminable area shot in the present embodiment multiple
Pre-set user, also, the present embodiment can carry out the matching of sitting posture posture simultaneously and then provide warning information, can also be directed to simultaneously
More people are monitored early warning, solve the skill that the monitoring and early warning mode being accustomed to eye cannot be monitored early warning for more people simultaneously
Art problem.
It is the flow diagram for the method for early warning second embodiment that the present invention is accustomed to eye referring to Fig. 3, Fig. 3, based on above-mentioned
First embodiment shown in Fig. 2 proposes the second embodiment for the method for early warning that the present invention is accustomed to eye.
It is described that image taking is carried out to predeterminable area according to predetermined period in second embodiment, to obtain image to be analyzed
Later, the method for early warning being accustomed to eye further include:
Pre-set user group is read from the first pre-set user information database, and determines that the pre-set user is intragroup
Each pre-set user.
In the concrete realization, if being suitable for classroom environment carries out the early warning being accustomed to eye, it is contemplated that the classroom of each class
One user equipment will be installed, so, when carrying out early warning, it will first determine class locating for user equipment.For example, user equipment is pacified
Loaded on A classes, then pre-set user group is A class students, and the intragroup pre-set user of pre-set user is A classes of each student, for example,
Student A1, student A2 and student A3 etc..Similarly, if being installed on B classes, pre-set user group is B classes of students.
Further, after the step S20, the method for early warning being accustomed to eye further include:
Step S301: it is determined according to the sitting posture change moment in user's sitting posture information corresponding continuous at the moment growing.
It is understood that it is bad with eye habit other than it can refer to user's sitting posture, further include user continuously use eye when
It is long, it is continuous too long easy into defective modes such as visual fatigues at the moment growing, and then cause the visual problems such as myopia.
It in the concrete realization, then can be from the continually changing seat of user since user's sitting posture information of predetermined period will be obtained
The duration of the continuous user of user is determined in appearance.For example, if user to be always maintained at certain posture constant, carry out continuous timing,
If user's sitting posture information changed at continuous timing 40 minutes, then can be calculated as continuous 40 minutes at the moment length, sitting posture becomes
The more moment is the 40th minute.
Step S302: it continuous is compared described at the moment long with presetting at the moment long range.
It should be understood that can will regard as well being set as 0≤x≤30 point at the moment long range with the default of eye habit
Clock, x are default at the moment long range.
Step S303: it is described it is continuous with it is at the moment long be not at it is described it is default at the moment long range when, generate second and use
Eye warning information, to carry out the early warning of bad eye habit with eye warning information by described second.
It is understood that then produce second and use eye warning information it is apparent that 40 minutes do not fall within the range or not, with
The pre-set user belonging to page end prompting webpage reader user's posture information continuously uses the duration of eye too long, it is proposed that carries out
The adjustment being accustomed to eye.
Certainly, it is described it is continuous at the moment long in default at the moment long range when, process can be terminated.
Further, after the step S303, the method for early warning being accustomed to eye further include:
Step S50: the userspersonal information of pre-set user is read from the second pre-set user information database.
It is understood that used for the ease of school and relevant departments, produce with eye statistical report for using.With
Eye statistical report record have each student use eye situation, and record have globality use eye condition evaluation.
In the concrete realization, the individual subscriber letter of each student can be read out from the second pre-set user information database
Breath, userspersonal information includes name, age and class's information etc., and the second pre-set user can also be established as unit of class
Information database.
It should be understood that after the step S303, while also after the step s 40, execute step step S50.
Step S60: according to the userspersonal information, user's sitting posture information, user's sitting posture information with it is described
Default sitting posture posture carry out matched matching result, it is described it is continuous with it is at the moment long and it is described it is continuous with it is at the moment long with it is described default
The comparison result generation eye statistical report being compared at the moment long range.
It is understood that with will include the userspersonal information of student in class, user's sitting posture in eye statistical report
Information and continuous at the moment growing, meanwhile, it is also recordable to have the matching result of the related sitting posture of student and related use in class
At the moment long comparison result.
In the concrete realization, the specific of single student uses eye situation with eye statistical report is also recordable, for example, statistics available
The matching result is the first object number of matches of successful match in first preset duration, and according to first object number of matches
First user's sitting posture accuracy is generated, and first user's sitting posture accuracy is added to eye statistical report.Specifically, optional
In some pre-set user, and count pre-set user sitting posture in one day and be identified as correct quantity, if the quantity is 400,
And carrying out matched total matching times is 1000, then the first user's sitting posture accuracy generated can describe the user for 0.4,0.4
Sitting posture situation.
It should be understood that having the globality of student in class eye shape condition with eye statistical report is also recordable, for example, can
The second object matching quantity that pre-set user group matching result in preset duration is successful match is counted, and according to the
Two object matching quantity generate second user sitting posture accuracy, and second user sitting posture accuracy is added to be counted with eye and is reported
It accuses.Specifically, pre-set user group can be chosen, for example, A classes, and count the sitting posture in one day of all students in A classes and recognized
It is set to correct quantity, if the quantity is 7000, and carrying out matched total matching times is 10000, then the second user generated
Sitting posture accuracy is 0.7, the 0.7 whole sitting posture situation that can describe A classes.
In addition, the first pre-set user information database referred to, the second pre-set user information database and subsequent referring to
Third pre-set user information database be only title, do not limit these three User Information Databases one and be set to different users
Information database, these three User Information Databases can be identical User Information Database.
It will also be introduced for continuously being considered at the moment long in the present embodiment, so that assesses user more fully hereinafter uses eye
Habit.Meanwhile can also by user's sitting posture information, continue at the moment growing and record the assessment of both indexs into eye and count
Report, to provide the data support of student's eye habit for school and relevant departments.
It is the flow diagram for the method for early warning 3rd embodiment that the present invention is accustomed to eye referring to Fig. 4, Fig. 4, based on above-mentioned
First embodiment shown in Fig. 2 proposes the 3rd embodiment for the method for early warning that the present invention is accustomed to eye.
In 3rd embodiment, the step S20, comprising:
Step S201: the default facial image of pre-set user is read from third pre-set user information database.
It is understood that user's sitting posture information in order to confirm pre-set user from the image to be analyzed that shooting obtains,
Face recognition technology and depth convolutional neural networks algorithm can be introduced simultaneously, confirmed in image to be analyzed by face recognition technology
Each student, then checked by sitting posture of the depth convolutional neural networks algorithm to each student.
In the concrete realization, the facial image that each student can be first stored in third pre-set user information database is
Recognition of face, which provides, compares sample.
Step S202: the identification pre-set user corresponding with the default facial image in the image to be analyzed.
It should be understood that if image to be analyzed be classroom picture, can using the default facial image of each student as than
To sample, pupilage belonging to the default facial image is identified from the picture of classroom.Wherein, pre-set user can be denoted as student
Name, student number or identification card number etc..
Step S203: being split the image to be analyzed according to the default facial image, with obtain with it is described pre-
If the corresponding pose presentation to be analyzed of user.
It is understood that shot in classroom picture has been determined into each student pupilage after, can be to classroom
Picture is split, and is divided into fraction picture corresponding with each student, for example, shooting the posture figure into the sitting posture of student A1
As, shoot into the sitting posture of student A2 pose presentation and shoot the pose presentation of sitting posture into student A3 etc..
Step S204: inputting default training convolutional neural networks for the pose presentation to be analyzed, described default to obtain
User's sitting posture information corresponding with the pre-set user of training convolutional neural networks output.
It should be understood that after segmenting pose presentation to be analyzed corresponding with each student, can by after division to
The input layer that pose presentation inputs default training convolutional neural networks is analyzed, finally to obtain in the pose presentation to be analyzed
The recognition result of sitting posture of student.
Further, described that image taking is carried out to predeterminable area according to predetermined period, before obtaining image to be analyzed,
The method for early warning being accustomed to eye further include:
Image taking is carried out to predeterminable area, to obtain sample image；
The default facial image of pre-set user is identified in the sample image；
The sample image is split according to the default facial image of the pre-set user, is preset with obtaining with described
The corresponding sample pose presentation of user；
It is trained by the sample pose presentation to initial convolutional neural networks are preset, with default after being trained
Initial convolutional neural networks, and the default initial convolutional neural networks after training are regarded as into default training convolutional neural networks.
It is understood that default training convolutional neural networks are the convolutional neural networks after training, may be directly applied to
For the identification link of sitting posture.It, can be first to presetting initial convolutional neural networks in order to obtain the convolutional neural networks after the training
It is trained.
In the concrete realization, same region can be shot in advance, and divided in the sample image shot in advance
Cut out the respective pose presentation of each student.Then, it is carried out by obtained pose presentation to initial convolutional neural networks are preset
Training, so that presetting the weighting coefficient in initial convolutional neural networks is optimum weighting coefficient.In subsequent practical application mistake
The convolutional neural networks after training can be used directly to complete the early warning for being accustomed to eye in Cheng Zhong.
Further, described that the sample image is split according to the default facial image of the pre-set user, with
After obtaining sample pose presentation corresponding with the pre-set user, the method for early warning being accustomed to eye further include:
Obtain label information；
The sample pose presentation is labeled as by the label information to preset the standard in initial convolutional neural networks
Pose presentation；
It is described to be trained by the sample pose presentation to initial convolutional neural networks are preset, after being trained
Initial convolutional neural networks are preset, and the default initial convolutional neural networks after training are regarded as into default training convolutional nerve net
Network, comprising:
It is trained by the standard pose presentation to initial convolutional neural networks are preset, with default after being trained
Initial convolutional neural networks, and the default initial convolutional neural networks after training are regarded as into default training convolutional neural networks.
It is understood that in order to improve recognition accuracy of the convolutional neural networks after training for correct sitting posture, it can
Positive sample is inputted in training convolutional neural networks, positive sample is the sample posture that pre-set user is taken action according to correct sitting posture
Image.Meanwhile the sample pose presentation can be labeled as positive sample, that is, standard appearance by label information in convolutional neural networks
State image.Convolutional neural networks are trained by standard pose presentation, the convolutional neural networks after training can be made
It is optimal the effect of identification.
It should be understood that can first allow each student to be sitting in religion to obtain the sample pose presentation for meeting sitting posture requirement
It in room on the seat of oneself, and is sat up straight with correctly presetting sitting posture posture, then, is acquired under the lower scene by camera
Picture as the sample pose presentation for meeting sitting posture requirement.
The operation of sitting posture identification is completed in the present embodiment in combination with face recognition technology and convolutional neural networks, and then certainly
The dynamic inspection completed for user's sitting posture.
In addition, the embodiment of the present invention also proposes a kind of storage medium, the pre- of useful eye habit is stored on the storage medium
Alert program, the early warning program being accustomed to eye realize following operation when being executed by processor:
Image taking is carried out to predeterminable area according to predetermined period, to obtain image to be analyzed；
User's sitting posture information corresponding with each pre-set user, the pre-set user are determined according to the image to be analyzed
In spatial dimension in the predeterminable area；
User's sitting posture information is matched with default sitting posture posture；
When user's sitting posture information and the default sitting posture posture mismatch, generates first and use eye warning information, with
The early warning of bad eye habit is carried out with eye warning information by described first.
Further, following operation is also realized when the early warning program being accustomed to eye is executed by processor:
Pre-set user group is read from the first pre-set user information database, and determines that the pre-set user is intragroup
Each pre-set user.
Further, following operation is also realized when the early warning program being accustomed to eye is executed by processor:
It is determined according to the sitting posture change moment in user's sitting posture information corresponding continuous at the moment growing；
It continuous is compared described at the moment long with presetting at the moment long range；
It is described it is continuous with it is at the moment long be not at it is described it is default at the moment long range when, generate second and believed with eye early warning
Breath, to carry out the early warning of bad eye habit with eye warning information by described second.
Further, following operation is also realized when the early warning program being accustomed to eye is executed by processor:
The userspersonal information of pre-set user is read from the second pre-set user information database；
According to the userspersonal information, user's sitting posture information, user's sitting posture information and the default sitting posture
Posture carry out matched matching result, it is described it is continuous with it is at the moment long and it is described it is continuous at the moment length with it is described default at the moment growing
The comparison result generation eye statistical report that range is compared.
Further, following operation is also realized when the early warning program being accustomed to eye is executed by processor:
The default facial image of pre-set user is read from third pre-set user information database；
The identification pre-set user corresponding with the default facial image in the image to be analyzed；
The image to be analyzed is split according to the default facial image, it is corresponding with the pre-set user to obtain
Pose presentation to be analyzed；
The pose presentation to be analyzed is inputted into default training convolutional neural networks, to obtain the default training convolutional mind
The user's sitting posture information corresponding with the pre-set user exported through network.
Further, following operation is also realized when the early warning program being accustomed to eye is executed by processor:
Image taking is carried out to predeterminable area, to obtain sample image；
The default facial image of pre-set user is identified in the sample image；
The sample image is split according to the default facial image of the pre-set user, is preset with obtaining with described
The corresponding sample pose presentation of user；
It is trained by the sample pose presentation to initial convolutional neural networks are preset, with default after being trained
Initial convolutional neural networks, and the default initial convolutional neural networks after training are regarded as into default training convolutional neural networks.
Further, following operation is also realized when the early warning program being accustomed to eye is executed by processor:
Obtain label information；
The sample pose presentation is labeled as by the label information to preset the standard in initial convolutional neural networks
Pose presentation；
Correspondingly, following operation is also realized:
It is trained by the standard pose presentation to initial convolutional neural networks are preset, with default after being trained
Initial convolutional neural networks, and the default initial convolutional neural networks after training are regarded as into default training convolutional neural networks.
Image taking first will be carried out to predeterminable area in the present embodiment, to obtain image to be analyzed, further according to figure to be analyzed
As determining user's sitting posture information corresponding with each pre-set user, by user's sitting posture information and the progress of default sitting posture posture
Match, when user's sitting posture information and default sitting posture posture mismatch, generate first and use eye warning information, with pre- with eye by first
Alert information carries out the bad early warning being accustomed to eye.It is apparent that can be existed simultaneously in the predeterminable area shot in the present embodiment multiple
Pre-set user, also, the present embodiment can carry out the matching of sitting posture posture simultaneously and then provide warning information, can also be directed to simultaneously
More people are monitored early warning, solve the skill that the monitoring and early warning mode being accustomed to eye cannot be monitored early warning for more people simultaneously
Art problem.
In addition, the embodiment of the present invention also proposes a kind of prior-warning device being accustomed to eye, what the eye was accustomed to referring to Fig. 5
Prior-warning device includes:
Image taking module 10, for carrying out image taking to predeterminable area according to predetermined period, to obtain figure to be analyzed
Picture.
It is understood that in view of wearable device can be used to carry out the monitoring and early warning being accustomed to eye, Yong Huye for user
Monitoring device can be installed on the table come carry out with eye be accustomed to monitoring and early warning, still, these monitoring and early warning modes simultaneously only
It can implement for a people, more people cannot be directed to simultaneously.If being intended to simultaneously for more people, these modes are more numb on the implementation
It is tired, and higher cost.
It should be understood that the present embodiment will be shot simultaneously into more people when shooting image to be analyzed, and monitor simultaneously more
People's is accustomed to eye, also just plays while being monitored for more people the effect of early warning.Also, any set is worn also without user
It is standby, implement relatively simple.
It should be understood that predeterminable area is the classroom environment that camera faces when applicable scene is classroom, preset
Period can be ten seconds for interval, then camera can take the photograph a picture every ten second beats against classroom environment, shot with obtaining into student
Classroom picture, that is, image to be analyzed.
Certainly, it is picture or video that the present embodiment, which is not intended to limit the image to be analyzed shot,.It, can if obtaining video
Each frame in video is intercepted, to obtain picture.
Sitting posture determining module 20, for determining that user corresponding with each pre-set user sits according to the image to be analyzed
Appearance information, the pre-set user are in the spatial dimension of the predeterminable area.
It is understood that due to having shot the image into multiple students in the picture of classroom, to may recognize that multiple
Raw sitting posture, and it is recorded as user's sitting posture information of each student.Wherein, user's sitting posture information record has the sitting posture of pre-set user
Information.
Sitting posture matching module 30, for matching user's sitting posture information with default sitting posture posture.
It should be understood that for the ease of identify incorrect sitting-pose in turn result in it is undesirable be accustomed to eye, can be preset
The default sitting posture posture of good sitting position is regarded as, default sitting posture posture can refer to common good sitting position requirement.For example, can will be pre-
If sitting posture posture is set as, the upper part of the body of user's body is upright and eyes of user is apart from one ruler of desktop etc..
It is understood that the user's sitting posture information that can be will acquire is matched with the default sitting posture posture, if user
The upper half of the user's body recorded in sitting posture information as upright and eyes of user really apart from one ruler of desktop, then it is believed that matching
Success, user's sitting posture is good, is not necessarily to early warning；If different from default sitting posture posture, can regard as mismatching.
With eye warning module 40, it is used to generate when user's sitting posture information and the default sitting posture posture mismatch
First uses eye warning information, to carry out the early warning of bad eye habit with eye warning information by described first.
It is understood that producing first when mismatching and using eye warning information, first is recordable with eye warning information
There is the prompt information of the student true to abnormal sitting posture.First can be displayed in preset web with eye warning information, for student or
Teacher's person reading can also provide decision data and support, and then carry out to undesirable student is accustomed to eye for school and relevant departments
Early warning.
Image taking first will be carried out to predeterminable area in the present embodiment, to obtain image to be analyzed, further according to figure to be analyzed
As determining user's sitting posture information corresponding with each pre-set user, by user's sitting posture information and the progress of default sitting posture posture
Match, when user's sitting posture information and default sitting posture posture mismatch, generate first and use eye warning information, with pre- with eye by first
Alert information carries out the bad early warning being accustomed to eye.It is apparent that can be existed simultaneously in the predeterminable area shot in the present embodiment multiple
Pre-set user, also, the present embodiment can carry out the matching of sitting posture posture simultaneously and then provide warning information, can also be directed to simultaneously
More people are monitored early warning, solve the skill that the monitoring and early warning mode being accustomed to eye cannot be monitored early warning for more people simultaneously
Art problem.
In one embodiment, the prior-warning device being accustomed to eye further include:
Group's confirmation module for reading pre-set user group from the first pre-set user information database, and determines institute
State the intragroup each pre-set user of pre-set user.
In one embodiment, the prior-warning device being accustomed to eye further include:
Duration warning module, for determining corresponding continuous use according to the sitting posture change moment in user's sitting posture information
At the moment grow；It continuous is compared described at the moment long with presetting at the moment long range；It is described it is continuous at the moment length be not at
It is described it is default at the moment long range when, generate second and use eye warning information, to be carried out by described second with eye warning information
The bad early warning being accustomed to eye.
In one embodiment, the prior-warning device being accustomed to eye further include:
Report generation module, for reading the individual subscriber letter of pre-set user from the second pre-set user information database
Breath；According to the userspersonal information, user's sitting posture information, user's sitting posture information and the default sitting posture posture into
The matched matching result of row, it is described it is continuous with it is at the moment long and it is described it is continuous at the moment long with the default at the moment long range into
The comparison result that row compares, which generates, uses eye statistical report.
In one embodiment, the sitting posture determining module 20 is also used to read from third pre-set user information database
The default facial image of pre-set user；The identification default use corresponding with the default facial image in the image to be analyzed
Family；The image to be analyzed is split according to the default facial image, with obtain it is corresponding with the pre-set user to
Analyze pose presentation；The pose presentation to be analyzed is inputted into default training convolutional neural networks, to obtain the default training
User's sitting posture information corresponding with the pre-set user of convolutional neural networks output.
In one embodiment, the prior-warning device being accustomed to eye further include:
Neural metwork training module, for carrying out image taking to predeterminable area, to obtain sample image；In the sample
The default facial image of pre-set user is identified in image；According to the default facial image of the pre-set user to the sample image
It is split, to obtain sample pose presentation corresponding with the pre-set user；By the sample pose presentation to default first
Beginning convolutional neural networks are trained, with the default initial convolutional neural networks after being trained, and will after training it is default just
Beginning convolutional neural networks regard as default training convolutional neural networks.
In one embodiment, the prior-warning device being accustomed to eye further include:
Standard picture module, for obtaining label information；The sample pose presentation is marked by the label information
To preset the standard pose presentation in initial convolutional neural networks；
The neural metwork training module is also used to through the standard pose presentation to presetting initial convolutional neural networks
It is trained, with the default initial convolutional neural networks after being trained, and by the default initial convolutional neural networks after training
Regard as default training convolutional neural networks.
The other embodiments or specific implementation of the prior-warning device of the present invention being accustomed to eye can refer to above-mentioned each side
Method embodiment, details are not described herein again.
It should be noted that, in this document, the terms "include", "comprise" or its any other variant are intended to non-row
His property includes, so that the process, method, article or the system that include a series of elements not only include those elements, and
And further include other elements that are not explicitly listed, or further include for this process, method, article or system institute it is intrinsic
Element.In the absence of more restrictions, the element limited by sentence "including a ...", it is not excluded that including being somebody's turn to do
There is also other identical elements in the process, method of element, article or system.
The serial number of the above embodiments of the invention is only for description, does not represent the advantages or disadvantages of the embodiments.If listing equipment for drying
Unit claim in, several in these devices, which can be, to be embodied by the same item of hardware.Word first,
Second and the use of third etc. do not indicate any sequence, can be title by these word explanations.
Through the above description of the embodiments, those skilled in the art can be understood that above-described embodiment side
Method can be realized by means of software and necessary general hardware platform, naturally it is also possible to by hardware, but in many cases
The former is more preferably embodiment.Based on this understanding, technical solution of the present invention substantially in other words does the prior art
The part contributed out can be embodied in the form of software products, which is stored in a storage medium
In (such as ROM/RAM, magnetic disk, CD), including some instructions are used so that a terminal device (can be mobile phone, computer, clothes
Business device, air conditioner or the network equipment etc.) execute method described in each embodiment of the present invention.
The above is only a preferred embodiment of the present invention, is not intended to limit the scope of the invention, all to utilize this hair
Equivalent structure or equivalent flow shift made by bright specification and accompanying drawing content is applied directly or indirectly in other relevant skills
Art field, is included within the scope of the present invention.
Claims (10)
1. it is a kind of with eye be accustomed to method for early warning, which is characterized in that it is described with eye be accustomed to method for early warning the following steps are included:
Image taking is carried out to predeterminable area according to predetermined period, to obtain image to be analyzed；
User's sitting posture information corresponding with each pre-set user is determined according to the image to be analyzed, and the pre-set user is in
In the spatial dimension of the predeterminable area；
User's sitting posture information is matched with default sitting posture posture；
When user's sitting posture information and the default sitting posture posture mismatch, generates first and use eye warning information, to pass through
Described first carries out the early warning of bad eye habit with eye warning information.
2. as described in claim 1 with eye be accustomed to method for early warning, which is characterized in that it is described according to predetermined period to preset areas
Domain carries out image taking, after obtaining image to be analyzed, the method for early warning being accustomed to eye further include:
Pre-set user group is read from the first pre-set user information database, and determines that the pre-set user is intragroup each pre-
If user.
3. the method for early warning being accustomed to as described in claim 1 with eye, which is characterized in that described true according to the image to be analyzed
After fixed user's sitting posture information corresponding with each pre-set user, the method for early warning being accustomed to eye further include:
It is determined according to the sitting posture change moment in user's sitting posture information corresponding continuous at the moment growing；
It continuous is compared described at the moment long with presetting at the moment long range；
It is described it is continuous with it is at the moment long be not at it is described it is default at the moment long range when, generate second and use eye warning information, with
The early warning of bad eye habit is carried out with eye warning information by described second.
4. the method for early warning being accustomed to as claimed in claim 3 with eye, which is characterized in that described at the moment long not in the continuous use
When in the default use at the moment long range, generates second and use eye warning information, to use eye warning information by described second
After carrying out the bad early warning being accustomed to eye, the method for early warning being accustomed to eye further include:
The userspersonal information of pre-set user is read from the second pre-set user information database；
According to the userspersonal information, user's sitting posture information, user's sitting posture information and the default sitting posture posture
Carry out matched matching result, the continuous at the moment long and described continuous at the moment long and described default at the moment long range
The comparison result generation eye statistical report being compared.
5. the method for early warning being accustomed to according to any one of claims 1 to 4 with eye, which is characterized in that described according to
Image to be analyzed determines user's sitting posture information corresponding with each pre-set user, comprising:
The default facial image of pre-set user is read from third pre-set user information database；
The identification pre-set user corresponding with the default facial image in the image to be analyzed；
The image to be analyzed is split according to the default facial image, with obtain it is corresponding with the pre-set user to
Analyze pose presentation；
The pose presentation to be analyzed is inputted into default training convolutional neural networks, to obtain the default training convolutional nerve net
User's sitting posture information corresponding with the pre-set user of network output.
6. as claimed in claim 5 with eye be accustomed to method for early warning, which is characterized in that it is described according to predetermined period to preset areas
Domain carries out image taking, before obtaining image to be analyzed, the method for early warning being accustomed to eye further include:
Image taking is carried out to predeterminable area, to obtain sample image；
The default facial image of pre-set user is identified in the sample image；
The sample image is split according to the default facial image of the pre-set user, to obtain and the pre-set user
Corresponding sample pose presentation；
It is trained by the sample pose presentation to initial convolutional neural networks are preset, with default initial after being trained
Convolutional neural networks, and the default initial convolutional neural networks after training are regarded as into default training convolutional neural networks.
7. the method for early warning being accustomed to as claimed in claim 6 with eye, which is characterized in that described according to the pre- of the pre-set user
If facial image is split the sample image, after obtaining sample pose presentation corresponding with the pre-set user,
The method for early warning being accustomed to eye further include:
Obtain label information；
The sample pose presentation is labeled as by the label information to preset the standard posture in initial convolutional neural networks
Image；
It is described to be trained by the sample pose presentation to initial convolutional neural networks are preset, with default after being trained
Initial convolutional neural networks, and the default initial convolutional neural networks after training are regarded as into default training convolutional neural networks,
Include:
It is trained by the standard pose presentation to initial convolutional neural networks are preset, with default initial after being trained
Convolutional neural networks, and the default initial convolutional neural networks after training are regarded as into default training convolutional neural networks.
8. a kind of user equipment, which is characterized in that the user equipment includes: camera, memory, processor and is stored in institute
The early warning program being accustomed to eye is stated on memory and can run on the processor, the early warning program being accustomed to eye is by institute
State the step of method for early warning being accustomed to eye as described in any one of claims 1 to 7 is realized when processor executes.
9. a kind of storage medium, which is characterized in that the early warning program of useful eye habit is stored on the storage medium, it is described to use eye
The pre- police being accustomed to eye as described in any one of claims 1 to 7 are realized when the early warning program of habit is executed by processor
The step of method.
10. it is a kind of with eye be accustomed to prior-warning device, which is characterized in that it is described with eye be accustomed to prior-warning device include:
Image taking module, for carrying out image taking to predeterminable area according to predetermined period, to obtain image to be analyzed；
Sitting posture determining module, for determining that user's sitting posture corresponding with each pre-set user is believed according to the image to be analyzed
Breath, the pre-set user are in the spatial dimension of the predeterminable area；
Sitting posture matching module, for matching user's sitting posture information with default sitting posture posture；
With eye warning module, it is used to generate first when user's sitting posture information and the default sitting posture posture mismatch and use
Eye warning information, to carry out the early warning of bad eye habit with eye warning information by described first.
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