CN110379108A - A kind of method and its system of unmanned shop anti-thefting monitoring - Google Patents
A kind of method and its system of unmanned shop anti-thefting monitoring Download PDFInfo
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- CN110379108A CN110379108A CN201910764535.9A CN201910764535A CN110379108A CN 110379108 A CN110379108 A CN 110379108A CN 201910764535 A CN201910764535 A CN 201910764535A CN 110379108 A CN110379108 A CN 110379108A
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- unmanned shop
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B13/00—Burglar, theft or intruder alarms
- G08B13/18—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength
- G08B13/189—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems
- G08B13/194—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems
- G08B13/196—Actuation by interference with heat, light, or radiation of shorter wavelength; Actuation by intruding sources of heat, light, or radiation of shorter wavelength using passive radiation detection systems using image scanning and comparing systems using television cameras
- G08B13/19602—Image analysis to detect motion of the intruder, e.g. by frame subtraction
- G08B13/19613—Recognition of a predetermined image pattern or behaviour pattern indicating theft or intrusion
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- Computer Vision & Pattern Recognition (AREA)
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- General Physics & Mathematics (AREA)
- Alarm Systems (AREA)
- Burglar Alarm Systems (AREA)
Abstract
The present invention relates to anti-thefting monitoring technical fields, the method and its system of a kind of unmanned shop anti-thefting monitoring are specifically disclosed, including carrying out preset processing and being interconnected with unmanned shop management system, the information resources of monitoring point static state are obtained, compare adjacent information resources twice to judge whether to change；If changing, video is submitted to extract variation characteristic, and analyze and determine to variation characteristic；If belonging to irregular change, then behavior object is locked and starts anti-theft early-warning processing, can accurately identify whether situation changes in unmanned shop by image static analysis with this, the video of the period is submitted if changing and carries out dynamic analysis, without analyzing whole video, it and is that dynamic discriminance analysis targetedly is carried out to the changed period, improve recognition efficiency, and the object of action of irregular change is locked, facilitate background monitoring, anti-theft early-warning processing can be carried out, is prevented trouble before it happens.
Description
Technical field
The present invention relates to anti-thefting monitoring technical field, specifically discloses a kind of method of unmanned shop anti-thefting monitoring and its be
System.
Background technique
With the development of science and technology, the shopping way of people becomes more and more diversified, has gradually appeared nothing on the market
The shop of people's management.The appearance in unmanned shop has brought convenience, and storekeeper may not need concrete management, and then for shopper
It can be done shopping, and can independently paid with entering unmanned shop in 24 hours one day at any time, without being lined up.
Currently, common unmanned shop anti-theft monitoring system is usually to install camera in unmanned shop, then manually rear
Platform in unmanned shop to being monitored, when discovery someone steals commodity alarm.However, current unmanned shop anti-theft monitoring system is simultaneously
It is not perfect, it is highly dependent on the artificial monitoring in backstage, cannot not only prejudge out suspicion behavior, but also is easy to happen discovery and steals
Surreptitiously behavior not in time the case where, to bring loss to unmanned shop storekeeper.
Therefore, it is necessary to a kind of schemes that can solve the above problem.
Summary of the invention
In order to overcome shortcoming and defect existing in the prior art, a purpose of the present invention is that it is anti-to provide a kind of unmanned shop
Steal the method and its system of monitoring.
To achieve the above object, the present invention uses following scheme.
A kind of method of unmanned shop anti-thefting monitoring, comprising:
Preset processing a little is monitored to space in unmanned shop, and is interconnected with unmanned shop management system；
Moment obtains the information resources of monitoring point static state, compares the adjacent information resources that obtain twice to judge the corresponding nothing in monitoring point
Whether situation changes in people shop；
If changing, the video of monitoring point is submitted to extract variation characteristic, and carry out to the variation characteristic extracted
It analyzes and determines；
If belonging to irregular change, behavior object is locked, and starts anti-theft early-warning processing.
Further, described that preset processing a little is monitored to space in unmanned shop and mutual with unmanned shop management system
Connection, comprising:
Space in unmanned shop is divided into several regions, and several monitoring points are set in each region；
Each region is numbered, the monitoring point list in each numbering area is established, monitoring point list and monitoring point are provided
Source is interrelated；
Each monitoring point is accessed in unmanned shop management system by related protocol.
Further, moment obtains the information resources of monitoring point static state, compare adjacent acquisition information resources twice with
Judge whether situation changes in the corresponding unmanned shop in monitoring point, comprising:
Moment obtains the still image of monitoring point, identifies with CNN convolutional neural networks to still image；
Judge whether the still image of adjacent two frame changes；
If changing, the related video for intercepting the monitoring point is made to submit and be prepared；If there is no variations, to the prison
Image, video of the control point within the period there is no variation carry out discard processing.
It is further, described that still image is identified with CNN convolutional neural networks, comprising:
The convolution kernel being adapted with still image is determined by the way that different convolution kernels is constantly arranged, using at the beginning of the convolution kernel of adaptation
Step extracts the feature of image, and determines image in the output valve of convolutional layer；
The output valve of convolutional layer is sent to Chi Huacengzuochiization and is acted on, to remove picture noise, retains the main feature of image；
The feature of image parts is summarized by the effect of full articulamentum, generates classifier, carries out Forecasting recognition.
Further, it includes facial structure variation characteristic, limb that the video for submitting monitoring point, which extracts variation characteristic,
Body language change feature and action trail variation characteristic.
Further, the variation characteristic extracted is analyzed and determined, comprising:
Face characteristic in face's variation characteristic and face database is subjected to big data analysis, is judged whether and stealing people
Form it is similar, wherein at least include eye position, corners of the mouth curvature and eyebrow camber；
Limbs speech variation characteristic in limbs speech variation characteristic and body language database is subjected to big data analysis, judgement
It is whether similar with the variation of the limbs speech of stealing people, wherein at least including involved party head whether look about, limbs
Whether roll up；
Judge whether action trail is similar with the variation of the action trail of stealing people, whether wherein at least includes involved party one
Whether determine to hover, stop in commodity in range is more than the scheduled time；
If structure change feature, body language variation characteristic and action trail variation characteristic are consistent with stealing, mark
For irregular change.
Further, described that behavior object is locked, and start anti-theft early-warning processing, comprising:
To the object of action setting locking frame of irregular change in video, and make to lock the shifting of frame following behavior object
It is dynamic；
It is broadcasted by voice system into unmanned shop and reminds voice；
Watchful information is sent to object of action mobile terminal.
Further, after starting anti-theft early-warning processing, antitheft tracing and monitoring is carried out to the object of action of irregular change,
Specifically:
Identify whether object of action is Chong Die with commodity region in video, and judges that object of action leaves quotient behind commodity region
Whether product region changes；
If commodity region changes, the mobile terminal of object of action and the connection of unmanned shop door are disconnected, until recognizing row
It is just accessed again after completing payment for object.
The present invention also provides a kind of systems of unmanned shop anti-thefting monitoring, including server；
Server includes processor and storage equipment；
Processor is adapted for carrying out program instruction；
Equipment is stored, storage program instruction is suitable for, described program instruction is suitable for being loaded by processor and being executed above-mentioned to realize
Unmanned shop anti-thefting monitoring method.
The present invention also provides a kind of mobile terminals, comprising:
Processor is adapted for carrying out program instruction；
Equipment is stored, storage program instruction is suitable for, described program instruction is suitable for being loaded by processor and being executed above-mentioned to realize
Unmanned shop anti-thefting monitoring method.
Beneficial effects of the present invention: the method and its system of a kind of unmanned shop anti-thefting monitoring are provided, by unmanned shop
Space is monitored preset processing a little and interconnects with unmanned shop management system, and it is quiet can to obtain constantly monitoring point when being monitored
The information resources of state compare the adjacent information resources that obtain twice to judge whether situation becomes in the corresponding unmanned shop in monitoring point
Change；If changing, the video of monitoring point is submitted to extract variation characteristic, and divide the variation characteristic extracted
Analysis judgement；If belonging to irregular change, anti-theft early-warning processing is locked and started to behavior object, image is passed through with this
Static analysis can accurately identify whether situation changes in unmanned shop, will corresponding period if changing
Video, which is submitted, carries out dynamic analysis, without can not only economize on resources to whole video analysis, Er Qieshi
Dynamic discriminance analysis targetedly is carried out to the changed period, recognition efficiency can be greatly improved, and to non-
The object of action of normal variation is locked, and background monitoring is facilitated, and can also carry out anti-theft early-warning processing to object of action, can be with
It prevents trouble before it happens.
Detailed description of the invention
Fig. 1 is the flow diagram of anti-thefting monitoring of embodiment of the present invention method.
Specific embodiment
For the ease of the understanding of those skilled in the art, the present invention is made further below with reference to examples and drawings
Bright, the content that embodiment refers to not is limitation of the invention.
A kind of method of unmanned shop anti-thefting monitoring is analyzed by static image analysis and dynamic video to reduce dynamic
The process of analysis allows to targetedly be analyzed, and improves the efficiency of analysis identification, to reach better antitheft prison
The effect of control, detailed process are as shown in Figure 1, comprising:
In order to can comprehensively monitor to the space carried out in unmanned shop, need to be monitored space in unmanned shop a little preset
It handles and is interconnected with unmanned shop management system.Preferably, the space in unmanned shop is divided if preset processing includes at least
Dry region, and several monitoring points are set in each region, each monitoring point can be directed at the different positions of the area planar
It sets, each monitoring point can also be directed to the different height of same position, thus realize the monitoring of horizontal space and longitudinal space,
It realizes to comprehensively being monitored in unmanned shop.Then each region is numbered, establishes the monitoring point range in each numbering area
Table, monitoring point list and monitoring point resource is interrelated, it can be convenient with this and each monitoring point be managed, be also convenient for people
Work inquires the resource information of some monitoring point.After the setting for completing monitoring point, by related protocol by each monitoring point
It accesses in unmanned shop management system, realizes the functions such as live preview, playing back videos, speech talkback.
When being monitored to unmanned shop, discriminance analysis all is carried out to video if it is whole, larger workload can account for
There is the resource of analysis, then probably analysis monitoring point does not change during this period of time, the waste of resource is caused, and
Inefficiency.Therefore, the present invention is in such a way that static analysis and dynamic analysis combine.Specifically, the moment obtains monitoring point
Static information resources, the static information resource carry out still image based on still image, with CNN convolutional neural networks
Identification, image recognition compare adjacent obtain twice information resources (namely still image of adjacent two frame) to judge to monitor after coming out
Whether situation changes in the corresponding unmanned shop of point, and the image identified through CNN convolutional neural networks can quickly judge
Whether change.Illustrate that the corresponding unmanned shop region in the monitoring point is walked about if changing, therefore can be by the time
The video of section submits analysis to obtain variation characteristic, and the related video for needing to intercept the monitoring point before submission mentions
It hands over and prepares, for example format conversion, marked zone number, monitoring point list etc., in order to subsequent extraction signature analysis.If
There is no variation, then illustrate this monitoring point during this period of time without the stream of people, since there is no variations, without being divided
Analysis, therefore image of the monitoring point within the period there is no variation, video can be lost without reservation
Abandoning processing is conducive to store more changed videos to discharge the storage space of system.
More specifically, it includes different by being constantly arranged for carrying out identification to still image with CNN convolutional neural networks
Convolution kernel determines the convolution kernel being adapted with still image, tentatively extracts the feature of image using the convolution kernel of adaptation, and true
Image is determined in the output valve of convolutional layer；The output valve of convolutional layer is sent to Chi Huacengzuochiization and is acted on, to remove picture noise, is protected
Stay the main feature of image；The feature of image parts is summarized by the effect of full articulamentum, generates classifier, into
Row Forecasting recognition.
The variation characteristic extracted need to then be analyzed and determined.The video of monitoring point is submitted to extract variation special
Sign includes but is not limited to facial structure variation characteristic, body language variation characteristic and action trail variation characteristic.It not passes herein
The features such as the face for identifying object of action of system judge whether recidivist determines suspect for it, but variation characteristic is passed through
Big data analysis judges whether it is similar with the form of stealing people, so as to preferably carry out control to object of action.
Specifically, the face characteristic in face's variation characteristic and face database is subjected to big data analysis, judged whether
It is similar with the form of stealing people, it wherein at least include eye position, corners of the mouth curvature and eyebrow camber；Limbs speech is changed
Limbs speech variation characteristic in feature and body language database carries out big data analysis, judges whether with stealing people's
The variation of limbs speech is similar, and wherein at least whether the head including involved party looks about, whether limbs roll up；Judgement behavior rail
Whether mark is similar with the variation of the action trail of stealing people, wherein at least whether hover in a certain range including involved party,
Whether stop in commodity is more than the scheduled time；If structure change feature, body language variation characteristic and action trail variation are special
Sign is consistent with stealing, then is labeled as irregular change.
Certainly, even if object of action meets the form of stealing, it can be used as and pay close attention to object, but object of action is simultaneously
Unexecuted stealing, in order to prevent trouble before it happens, to the object of action setting locking frame of irregular change in video, and
And make to lock the movement of frame following behavior object, so that backstage personnel conveniently be allowed to know that behavior object is abnormal condition, it is convenient for
Backstage personnel are reminded to pay close attention to.Start anti-theft early-warning processing simultaneously, for example prompting is broadcasted into unmanned shop by voice system
Voice can remind the other staff in unmanned shop to pay attention to the property of keeping oneself.Further, since unmanned shop is to use to be scanned into
The mode of door, unmanned shop management system is connected to the mobile terminal of object of action when entering, and can be moved to object of action
Dynamic terminal sends watchful information, can under the premise of not causing that personnel are alarmed in other shops watchful object of action, can give way
Stealing is actively abandoned for object.
Object of action still carries out theft after watchful in order to prevent, therefore after starting anti-theft early-warning processing, to improper
The object of action of variation carries out antitheft tracing and monitoring.Specifically, identify whether object of action is heavy with commodity region in video
It is folded, and judge whether commodity region changes after object of action leaves commodity region；If commodity region changes, break
Unmanned shop can not be opened by scanning by opening the mobile terminal of object of action and the connection of unmanned shop door namely behavior object
, it is just accessed again until recognizing after object of action completes payment, the openable unmanned shop of object of action ability after accessing again
Door leaves.It can ensure the commercial articles safety in unmanned shop to avoid allowing behavior object to flee from unmanned shop after stealing with this, avoid
The loss of storekeeper.It can also at will be inputted after avoiding object of action from stealing plus the type and its corresponding price of identification commodity
The door that one price can open unmanned shop is fled from.
A kind of method of unmanned shop anti-thefting monitoring provided by the invention, can accurately be identified by the static analysis of image
Whether situation changes in unmanned shop out, submits the video of corresponding period if changing and carries out dynamic point
Analysis can not only economize on resources, but also be targetedly to changed without analyzing whole video
Period carries out dynamic discriminance analysis, can greatly improve recognition efficiency, and carry out to the object of action of irregular change
Locking, facilitates background monitoring, can also carry out anti-theft early-warning processing to object of action, can prevent trouble before it happens.
The present invention provides also a kind of system of unmanned shop anti-thefting monitoring, including server；
Server includes processor and storage equipment；
Processor is adapted for carrying out program instruction；
Equipment is stored, storage program instruction is suitable for, described program instruction is suitable for being loaded by processor and being executed to realize above-mentioned state
Unmanned shop anti-thefting monitoring method.
The present invention provides a kind of mobile terminal, comprising:
Processor is adapted for carrying out program instruction；
Equipment is stored, storage program instruction is suitable for, described program instruction is suitable for being loaded by processor and being executed above-mentioned to realize
Unmanned shop anti-thefting monitoring method.
The above is only present pre-ferred embodiments, is not intended to limit the present invention in any form, although
The present invention is disclosed as above with preferred embodiment, and however, it is not intended to limit the invention, any person skilled in the art,
It does not depart within the scope of technical solution of the present invention, when the technology contents using the disclosure above make a little change or are modified to equivalent change
The equivalent embodiment of change, but without departing from the technical solutions of the present invention, technology refers to above embodiments according to the present invention
Made any simple modification, equivalent change and modification, belong in the range of technical solution of the present invention.
Claims (10)
1. a kind of method of unmanned shop anti-thefting monitoring characterized by comprising
Preset processing a little is monitored to space in unmanned shop, and is interconnected with unmanned shop management system；
Moment obtains the information resources of monitoring point static state, compares the adjacent information resources that obtain twice to judge the corresponding nothing in monitoring point
Whether situation changes in people shop；
If changing, the video of monitoring point is submitted to extract variation characteristic, and carry out to the variation characteristic extracted
It analyzes and determines；
If belonging to irregular change, behavior object is locked, and starts anti-theft early-warning processing.
2. a kind of method of unmanned shop anti-thefting monitoring according to claim 1, which is characterized in that described to empty in unmanned shop
Between be monitored preset processing a little, and interconnected with unmanned shop management system, comprising:
Space in unmanned shop is divided into several regions, and several monitoring points are set in each region；
Each region is numbered, the monitoring point list in each numbering area is established, monitoring point list and monitoring point are provided
Source is interrelated；
Each monitoring point is accessed in unmanned shop management system by related protocol.
3. a kind of method of unmanned shop anti-thefting monitoring according to claim 1, which is characterized in that the moment obtains monitoring
The static information resources of point compare the adjacent information resources that obtain twice to judge whether situation is sent out in the corresponding unmanned shop in monitoring point
Changing, comprising:
Moment obtains the still image of monitoring point, identifies with CNN convolutional neural networks to still image；
Judge whether the still image of adjacent two frame changes；
If changing, the related video for intercepting the monitoring point is made to submit and be prepared；If there is no variations, to the prison
Image, video of the control point within the period there is no variation carry out discard processing.
4. a kind of method of unmanned shop anti-thefting monitoring according to claim 3, which is characterized in that described to use CNN convolution
Neural network identifies still image, comprising:
The convolution kernel being adapted with still image is determined by the way that different convolution kernels is constantly arranged, using at the beginning of the convolution kernel of adaptation
Step extracts the feature of image, and determines image in the output valve of convolutional layer；
The output valve of convolutional layer is sent to Chi Huacengzuochiization and is acted on, to remove picture noise, retains the main feature of image；
The feature of image parts is summarized by the effect of full articulamentum, generates classifier, carries out Forecasting recognition.
5. a kind of method of unmanned shop anti-thefting monitoring according to claim 1, which is characterized in that the submission monitoring point
It includes facial structure variation characteristic, body language variation characteristic and action trail variation characteristic that video, which extracts variation characteristic,.
6. a kind of method of unmanned shop anti-thefting monitoring according to claim 5, which is characterized in that the change extracted
Change feature to be analyzed and determined, comprising:
Face characteristic in face's variation characteristic and face database is subjected to big data analysis, is judged whether and stealing people
Form it is similar, wherein at least include eye position, corners of the mouth curvature and eyebrow camber；
Limbs speech variation characteristic in limbs speech variation characteristic and body language database is subjected to big data analysis, judgement
It is whether similar with the variation of the limbs speech of stealing people, wherein at least including involved party head whether look about, limbs
Whether roll up；
Judge whether action trail is similar with the variation of the action trail of stealing people, whether wherein at least includes involved party one
Whether determine to hover, stop in commodity in range is more than the scheduled time；
If structure change feature, body language variation characteristic and action trail variation characteristic are consistent with stealing, mark
For irregular change.
7. a kind of method of unmanned shop anti-thefting monitoring according to claim 1, which is characterized in that described to behavior object
It is locked, and starts anti-theft early-warning processing, comprising:
To the object of action setting locking frame of irregular change in video, and make to lock the shifting of frame following behavior object
It is dynamic；
It is broadcasted by voice system into unmanned shop and reminds voice；
Watchful information is sent to object of action mobile terminal.
8. a kind of method of unmanned shop anti-thefting monitoring according to claim 1, which is characterized in that at starting anti-theft early-warning
After reason, antitheft tracing and monitoring is carried out to the object of action of irregular change, specifically:
Identify whether object of action is Chong Die with commodity region in video, and judges that object of action leaves quotient behind commodity region
Whether product region changes；
If commodity region changes, the mobile terminal of object of action and the connection of unmanned shop door are disconnected, until recognizing row
It is just accessed again after completing payment for object.
9. a kind of system of unmanned shop anti-thefting monitoring, which is characterized in that including server；
Server includes processor and storage equipment；
Processor is adapted for carrying out program instruction；
Equipment is stored, storage program instruction is suitable for, described program instruction is suitable for being loaded by processor and being executed to realize that right is wanted
Seek unmanned shop anti-thefting monitoring method described in 1 to 8 any one.
10. a kind of mobile terminal characterized by comprising
Processor is adapted for carrying out program instruction；
Equipment is stored, storage program instruction is suitable for, described program instruction is suitable for being loaded by processor and being executed to realize that right is wanted
Seek unmanned shop anti-thefting monitoring method described in 1 to 8 any one.
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| CN111223260A (en) * | 2020-01-19 | 2020-06-02 | 上海智勘科技有限公司 | Method and system for intelligently monitoring goods theft prevention in warehousing management |
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