CN109858378A - Vending machine good selling method and device, medium and equipment based on living things feature recognition - Google Patents
Vending machine good selling method and device, medium and equipment based on living things feature recognition Download PDFInfo
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- CN109858378A CN109858378A CN201910003266.4A CN201910003266A CN109858378A CN 109858378 A CN109858378 A CN 109858378A CN 201910003266 A CN201910003266 A CN 201910003266A CN 109858378 A CN109858378 A CN 109858378A
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- 238000004590 computer program Methods 0.000 claims description 3
- 238000013473 artificial intelligence Methods 0.000 abstract description 2
- 238000012545 processing Methods 0.000 description 12
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- 238000010586 diagram Methods 0.000 description 8
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- 230000005291 magnetic effect Effects 0.000 description 3
- 230000003287 optical effect Effects 0.000 description 3
- 238000013461 design Methods 0.000 description 2
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- 238000013528 artificial neural network Methods 0.000 description 1
- 210000004027 cell Anatomy 0.000 description 1
- 238000006243 chemical reaction Methods 0.000 description 1
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Abstract
The invention discloses a kind of vending machine good selling method and device, medium and equipment based on living things feature recognition, is related to field of artificial intelligence.The vending machine good selling method comprises determining that the biological characteristic for the recipient that the merchandise news of the commodity of purchaser's purchase and purchaser are specified；Determine the biological characteristic for the picking side for being acquired and being uploaded by vending machine；If the biometric matches of the biological characteristic of the recipient and the picking side, shipment instruction is sent to the vending machine.The disclosure can be embodied as other people on vending machine and buy commodity.
Description
Technical field
This disclosure relates to field of artificial intelligence, in particular to a kind of vending machine based on living things feature recognition
Good selling method, vending machine goods selling equipment, storage medium and electronic equipment based on living things feature recognition.
Background technique
Automatic vending machine (Vending Machine, VEM) is can be according to the machine of the automatic shipment of coin of investment.Automatically
Vending machine is the commonly used equipment of business automation, it is not limited by time, place, can save manpower, facilitate transaction, be one
The completely new retailing form of kind.Currently, automatic vending machine is more and more common, station has been widely used in it, subway station, has write
The places such as word building.
Automatic vending machine is transformed by the mode for being only capable of investment coin can support e-payment, for example, automatic vending
Machine supplier is configured with e-payment interface on machine, and self-service purchase can be completed in user by way of mobile phone barcode scanning
The process of commodity.
However, currently, buyer is operated manually before must be positioned at vending machine, that is to say, that buyer must reach
The position of vending machine can carry out commodity purchasing by way of coin or electronics, and this mode processing speed is slower, and nothing
Method buys commodity for other people.
It should be noted that information is only used for reinforcing the reason to the background of the disclosure disclosed in above-mentioned background technology part
Solution, therefore may include the information not constituted to the prior art known to persons of ordinary skill in the art.
Summary of the invention
The disclosure is designed to provide a kind of vending machine good selling method based on living things feature recognition, based on biological characteristic
Vending machine goods selling equipment, storage medium and the electronic equipment of identification, and then overcome at least to a certain extent due to the relevant technologies
Limitation and defect caused by buyer must reach vending machine position and carry out purchase and operation and commodity can not be bought for other people
The problem of.
According to one aspect of the disclosure, a kind of vending machine good selling method based on living things feature recognition is provided, comprising: really
The biological characteristic for the recipient that the merchandise news and purchaser for ordering the commodity of buyer's purchase are specified；Determination is acquired by vending machine
And the biological characteristic of the picking side uploaded；If the biometric matches of the biological characteristic of recipient and picking side, to selling goods
Machine sends shipment instruction.
Optionally, biological characteristic is face characteristic；Wherein it is determined that the biological characteristic for the recipient that purchaser specifies includes:
Determine the facial image for the recipient that purchaser uploads.
Optionally, vending machine good selling method further include: construct the histogram of the facial image of recipient as the first histogram
Figure, and construct picking side facial image histogram as the second histogram；Calculate the first histogram and the second histogram
Similarity；Wherein, if the similarity of the first histogram and the second histogram is greater than the first preset threshold, the life of recipient
The biometric matches of object feature and picking side.
Optionally, vending machine good selling method further include: the convolutional neural networks after having trained using one extract recipient
The feature vector of facial image is as first eigenvector；The feature of the facial image of picking side is extracted using convolutional neural networks
Vector is as second feature vector；Calculate the cosine similarity of first eigenvector and second feature vector；Wherein, if calculated
Cosine similarity out is greater than the second preset threshold, then the biometric matches of the biological characteristic of recipient and picking side.
Optionally, purchaser and recipient are the registration user of machine platform of selling goods；Wherein it is determined that the receipts that purchaser specifies
The biological characteristic of cargo interests includes: the selected identification information for operating determining recipient of recipient carried out based on purchaser；According to receipts
The identification information of cargo interests determines the biological characteristic of recipient from registration user information database.
Optionally, vending machine good selling method further include: obtain the contact method of recipient；Contact method based on recipient
Position acquisition request is sent to the terminal of recipient, to obtain the position of recipient；Determining and recipient positional distance is most
Close vending machine；The address of the vending machine nearest with the positional distance of recipient is sent to the terminal of recipient, to receive
Vending machine arrives in side.
Optionally, after sending shipment instruction to vending machine, vending machine good selling method further include: acquisition is determined by recipient
Delivery information；Delivery information is sent to a delivery company, so as to delivery company by the commodity that purchaser buys be delivered to
The corresponding address of delivery information.
According to one aspect of the disclosure, a kind of vending machine goods selling equipment based on living things feature recognition is provided, this is sold goods
Machine goods selling equipment may include information determination module, feature acquisition module and shipment instruction sending module.
Specifically, information determination module is determined for the merchandise news of the commodity of purchaser's purchase and purchaser refers to
The biological characteristic of fixed recipient；Feature obtains the biology of picking side that module is determined for being acquired by vending machine and upload
Feature；If shipment instruction sending module can be used for the biological characteristic of recipient and the biometric matches of picking side, to
Vending machine sends shipment instruction.
Optionally, biological characteristic is face characteristic；Wherein, information determination module may include information determination unit.
Specifically, information determination unit is determined for the facial image of the recipient of purchaser's upload.
Optionally, vending machine goods selling equipment further includes histogram building module and histogram similarity calculation module.
Specifically, histogram building module can be used for constructing the histogram of the facial image of recipient as the first histogram
Figure, and construct picking side facial image histogram as the second histogram；Histogram similarity calculation module can be used
In the similarity for calculating the first histogram and the second histogram；Wherein, if the similarity of the first histogram and the second histogram
Greater than the first preset threshold, then biometric matches of the biological characteristic of recipient and picking side.
Optionally, vending machine goods selling equipment can also include fisrt feature extraction module, second feature extraction module and spy
Levy similarity calculation module.
Specifically, the convolutional neural networks after fisrt feature extraction module can be used for having trained using one extract recipient
Facial image feature vector as first eigenvector；Second feature extraction module can be used for using convolutional neural networks
The feature vector of the facial image of picking side is extracted as second feature vector；Characteristic similarity computing module can be used for calculating
The cosine similarity of first eigenvector and second feature vector；Wherein, if calculated cosine similarity is greater than second in advance
If threshold value, then biometric matches of the biological characteristic of recipient and picking side.
Optionally, purchaser and recipient are the registration user of machine platform of selling goods；Wherein, information determination module includes mark
Know determination unit and biological characteristic determination unit.
Specifically, selected operate of recipient that mark determination unit can be used for carrying out based on purchaser determines recipient
Identification information；Biological characteristic determination unit, which can be used for being determined from registration user information database according to the identification information of recipient, to be received
The biological characteristic of cargo interests.
Optionally, it may include contact method acquiring unit, consignee location acquiring unit, vending machine that feature, which obtains module,
Determination unit and address transmission unit.
Specifically, contact method acquiring unit can be used for obtaining the contact method of recipient；Consignee location obtains single
Member can be used for the contact method based on recipient and send position acquisition request to the terminal of recipient, to obtain recipient
Position；Vending machine determination unit is determined for the vending machine nearest with the positional distance of recipient；Address transmission unit can
With the terminal for the address of the vending machine nearest with the positional distance of recipient to be sent to recipient, so as to recipient arrival
Vending machine.
Optionally, vending machine goods selling equipment can also include that delivery information obtains module and delivery information sending module.
Specifically, delivery information, which obtains module, can be used for obtaining the delivery information determined by recipient；Delivery information hair
Module is sent to can be used for for delivery information being sent to a delivery company, so that the commodity that purchaser buys are delivered to by delivery company
Address corresponding with delivery information.
According to one aspect of the disclosure, a kind of storage medium is provided, computer program, the computer are stored thereon with
The vending machine good selling method described in above-mentioned any one based on living things feature recognition is realized when program is executed by processor.
According to one aspect of the disclosure, a kind of electronic equipment is provided, comprising: processor；And memory, for storing
The executable instruction of the processor；Wherein, the processor is configured to above-mentioned to execute via the executable instruction is executed
Vending machine good selling method described in any one based on living things feature recognition.
In the technical solution provided by some embodiments of the present disclosure, the merchandise news of the commodity of purchaser's purchase is determined
And the biological characteristic of recipient that purchaser specifies, determine the biological characteristic for the picking side for being acquired and being uploaded by vending machine, such as
The biological characteristic for the recipient that fruit determines and the biometric matches of picking side then send shipment instruction to vending machine.On the one hand,
The disclosure can buy commodity on vending machine for other people, and buyer is without reaching vending machine；On the other hand, the disclosure can be with
Realize long-range purchase commodity process, it is easy to operate for buyer, for recipient, due to directlying adopt biology
The mode of feature carries out picking, and without carrying other articles, process is convenient.
It should be understood that above general description and following detailed description be only it is exemplary and explanatory, not
The disclosure can be limited.
Detailed description of the invention
The drawings herein are incorporated into the specification and forms part of this specification, and shows the implementation for meeting the disclosure
Example, and together with specification for explaining the principles of this disclosure.It should be evident that the accompanying drawings in the following description is only the disclosure
Some embodiments for those of ordinary skill in the art without creative efforts, can also basis
These attached drawings obtain other attached drawings.In the accompanying drawings:
Fig. 1 diagrammatically illustrates the flow chart of vending machine good selling method according to an exemplary embodiment of the present disclosure；
Fig. 2 diagrammatically illustrates the block diagram of vending machine goods selling equipment according to an exemplary embodiment of the present disclosure；
Fig. 3 diagrammatically illustrates the block diagram of information determination module according to an exemplary embodiment of the present disclosure；
Fig. 4 diagrammatically illustrates the box of the vending machine goods selling equipment of the another exemplary embodiment according to the disclosure
Figure；
Fig. 5 diagrammatically illustrates the box of the vending machine goods selling equipment of another illustrative embodiments according to the disclosure
Figure；
Fig. 6 diagrammatically illustrates the block diagram of information determination module according to an exemplary embodiment of the present disclosure；
Fig. 7 diagrammatically illustrates the block diagram that feature according to an exemplary embodiment of the present disclosure obtains module；
Fig. 8 diagrammatically illustrates the box of the vending machine goods selling equipment according to the another exemplary embodiment of the disclosure
Figure；
Fig. 9 shows the schematic diagram of storage medium according to an exemplary embodiment of the present disclosure；And
Figure 10 diagrammatically illustrates the block diagram of electronic equipment according to an exemplary embodiment of the present disclosure.
Specific embodiment
Example embodiment is described more fully with reference to the drawings.However, example embodiment can be with a variety of shapes
Formula is implemented, and is not understood as limited to example set forth herein；On the contrary, thesing embodiments are provided so that the disclosure will more
Fully and completely, and by the design of example embodiment comprehensively it is communicated to those skilled in the art.Described feature, knot
Structure or characteristic can be incorporated in any suitable manner in one or more embodiments.In the following description, it provides perhaps
More details fully understand embodiment of the present disclosure to provide.It will be appreciated, however, by one skilled in the art that can
It is omitted with technical solution of the disclosure one or more in the specific detail, or others side can be used
Method, constituent element, device, step etc..In other cases, be not shown in detail or describe known solution to avoid a presumptuous guest usurps the role of the host and
So that all aspects of this disclosure thicken.
In addition, attached drawing is only the schematic illustrations of the disclosure, it is not necessarily drawn to scale.Identical attached drawing mark in figure
Note indicates same or similar part, thus will omit repetition thereof.Some block diagrams shown in the drawings are function
Energy entity, not necessarily must be corresponding with physically or logically independent entity.These function can be realized using software form
Energy entity, or these functional entitys are realized in one or more hardware modules or integrated circuit, or at heterogeneous networks and/or place
These functional entitys are realized in reason device device and/or microcontroller device.
Flow chart shown in the drawings is merely illustrative, it is not necessary to including all steps.For example, the step of having
It can also decompose, and the step of having can merge or part merges, therefore the sequence actually executed is possible to according to the actual situation
Change.Term " first " described in the disclosure, " second " are merely to the purpose distinguished, should not be used as the limitation of the disclosure.
It is described below to be realized by a server based on the vending machine good selling method of living things feature recognition, that is,
It says, which can execute each step of the vending machine good selling method of the disclosure, and in this case, the disclosure is sold goods
Machine goods selling equipment can be only fitted in the server.In addition, the server can be deployed in vending machine manufacturer backstage.
Fig. 1 diagrammatically illustrates the vending machine seller based on living things feature recognition of the illustrative embodiments of the disclosure
The flow chart of method.With reference to Fig. 1, the vending machine good selling method of the disclosure be may comprise steps of:
S12. the biological characteristic for the recipient that the merchandise news of the commodity of determining purchaser's purchase and purchaser specify.
Purchaser can buy the commodity sold goods on platform by terminal remotes such as mobile phone, plate, PC.It is paid in purchaser
After the completion, server can determine the merchandise news of purchaser's purchase.
During purchaser buys commodity, purchaser can specify recipient, and server is according to the specified of purchaser
Determine the biological characteristic of recipient.It will be illustrated so that biological characteristic is face characteristic as an example below, however, those skilled in the art
Member using the bio-identification mode such as fingerprint recognition, iris recognition it is easily understood that can realize the seller of the disclosure
Method, these should belong to the design of the disclosure.
According to some embodiments of the present disclosure, purchaser and recipient are the registration users of platform of selling goods, in registration,
It needs facial image being uploaded to platform of selling goods, to correspond with the account of registration.Purchaser and recipient can be in platforms
On be friend relation, purchaser can select recipient directly from buddy list.In this case, firstly, server can
With the selected identification information for operating determining recipient of the recipient carried out based on purchaser, wherein the identification information can be receipts
The account title of cargo interests, registration ID etc. can uniquely determine the information of recipient；Next, server can be believed according to the mark
Cease the facial image that recipient is determined from registration user information database.In addition, not being friend relation in purchaser and recipient
In the case of, purchaser can also directly purchaser and select selling goods to search on platform, so that server determines the mark of recipient
Know information, and then determines the facial image of recipient.
According to other embodiments of the disclosure, purchaser can select the face of recipient from the image of terminal storage
Image, and the facial image is uploaded to server.In addition, purchaser can instantly if purchaser is together with recipient
To shoot facial image and the upload of recipient by terminal, so that server obtains the facial image of recipient.
It should be understood that under normal circumstances, the purchaser of the disclosure and recipient are two different people, however,
When purchaser and recipient are same people, the vending machine good selling method of the disclosure also be can be realized, this also belongs to the guarantor of the disclosure
Protect range.
In addition, server can determine the contact method (for example, cell-phone number) of recipient, or purchase from the information of registration
Buyer can input the contact method of recipient, to recommend the vending machine being closer from it for recipient.
Specifically, firstly, the contact method of the available recipient of server, and based on the contact method to recipient
Terminal sends position acquisition request, for example, server can send SMS Tip to the mobile phone of recipient, to prompt recipient to open
The APP that vending machine is sold goods is opened, and opens positioning function；Next, server can be determined according to the position of recipient distance compared with
Close vending machine, for example, it may be determined that 5 vending machines being closer, however, the disclosure to the quantity of determining vending machine not
Do particular determination.In addition, server can determine a nearest vending machine of the positional distance away from recipient；Then, server
The address of determining vending machine can be sent to the terminal of recipient, sold goods so that recipient can be arrived at according to the address
Machine, wherein recipient can be facilitated to arrive at vending machine using the mode of navigation.
S14. the biological characteristic for the picking side for being acquired and being uploaded by vending machine is determined.
It should be noted that the mode of above-mentioned recommendation vending machine recipient merely for convenience arrives at vending machine, step S14
In vending machine can be different from the vending machine of above-mentioned recommendation.
Still by taking face characteristic is biological characteristic as an example, there is client when operation is on vending machine to attempt to obtain commodity, selling
The camera configured on cargo aircraft can shoot biological characteristic of the facial image as picking side of the client.
In the illustrative embodiments of the disclosure, term " picking side " and " recipient " are different concept.Picking side
The people for wanting to take commodity is referred to, and recipient is the people that can get commodity, that is to say, that only recipient can just get purchase
The commodity just bought, this programme may determine that whether recipient and picking side are the same person.
S16. if the biometric matches of the biological characteristic of recipient and picking side, shipment is sent to vending machine and is referred to
It enables.
In the illustrative embodiments of the disclosure, server can by the facial image for the recipient that purchaser specifies with
The facial image of picking side is compared.
According to some embodiments of the present disclosure, image histogram can use to be compared to two facial images.Tool
Body, server can construct the histogram of the facial image of recipient as the first histogram, and server can construct
The histogram of the facial image of picking side is as the second histogram, and then, server can calculate the first histogram and second directly
The similarity of square figure is as image comparison result.
Specifically, firstly, server can respectively to above-mentioned two image carry out HSV (Hue, Saturation, Value,
Tone, saturation degree, lightness) format conversion；Then, the histogram of the result building image after server can be converted based on format
Figure, and histogram is normalized；Next, server can calculate the similarity between two histograms.
If the similarity of the first histogram and the second histogram is greater than the first preset threshold, recipient can be determined
Facial image is matched with the facial image of picking side.Wherein, if being denoted as 1 for identical, the range of the first preset threshold
It can be, for example, between 0.85 to 1.
According to other embodiments of the disclosure, can the mode based on deep learning two facial images are compared
Compared with.Specifically, firstly, server can using one training after convolutional neural networks extract recipient facial image feature to
Amount is used as first eigenvector, and the feature vector of picking side's facial image can be extracted using the convolutional neural networks as the
Two feature vectors；Next, server can calculate the cosine similarity of first eigenvector and second feature vector as figure
As comparison result.
Furthermore it is possible to be trained using the sample after handmarking to the convolutional neural networks.The disclosure is to above-mentioned volume
The structure and training process of product neural network are not done specifically limited.
If calculated cosine similarity is greater than the second preset threshold, it can determine the facial image of recipient and take
The facial image of cargo interests matches.Wherein, in the case where cosine similarity is defined as taking 0 to 1, the range of the second preset threshold
It can be, for example, between 0.9 to 1.
In addition, if based on above two mode determine recipient facial image and picking side facial image not
Match, then picking side and recipient are not the same persons, then vending machine will not shipment.
In the matched situation of face characteristic of the face characteristic and picking side of determining recipient, that is to say, that true
It makes in the case that picking side and recipient be same people, server can send shipment instruction to vending machine, and vending machine can be with
The output port that commodity are moved to vending machine by shipment instruction is responded, so that picking side takes commodity away.
According to some embodiments of the present disclosure, it is contemplated that the current picking of recipient is inconvenient, commodity are larger, relatively heavy etc. reasons,
The disclosure can also include providing the scheme of service of delivering goods to recipient.
Specifically, server to vending machine send shipment instruction after, the interface of vending machine can show now delivery of cargo and
The option of delivery, recipient can realize the purpose of selection by way of interface is manually operated, and mention now in recipient selection
In the case where goods, commodity can be moved to the output port of vending machine by vending machine, so that picking side takes commodity away.
In the case where recipient selects delivery, address input interface can be popped up or be jumped in vending machine interface, so as to
Recipient inputs delivery information.The delivery information that recipient inputs can be uploaded to server by vending machine.Then, server can
The delivery company of cooperative relationship is established, with platform that delivery information is sent to and is sold goods so that the delivery company buys purchaser
Commodity be delivered to the corresponding address of delivery information.
In conclusion the vending machine seller based on living things feature recognition according to an exemplary embodiment of the present disclosure
Method.On the one hand, the disclosure can buy commodity on vending machine for other people, and buyer is without reaching vending machine；On the other hand,
The disclosure may be implemented remotely to buy commodity process, easy to operate for buyer, for recipient, due to straight
It connects and carries out picking by the way of biological characteristic, without carrying other articles, process is convenient.
It should be noted that although describing each step of method in the disclosure in the accompanying drawings with particular order, this is simultaneously
Undesired or hint must execute these steps in this particular order, or have to carry out the ability of step shown in whole
Realize desired result.Additional or alternative, it is convenient to omit multiple steps are merged into a step and executed by certain steps,
And/or a step is decomposed into execution of multiple steps etc..
Further, a kind of vending machine based on living things feature recognition is additionally provided in this example embodiment to sell goods dress
It sets.
Fig. 2 diagrammatically illustrates the vending machine goods selling equipment of the living things feature recognition of the illustrative embodiments of the disclosure
Block diagram.With reference to Fig. 2, vending machine goods selling equipment 2 according to an exemplary embodiment of the present disclosure may include that information determines mould
Block 21, feature obtain module 23 and shipment instruction sending module 25.
Specifically, information determination module 21 is determined for merchandise news and the purchaser of the commodity of purchaser's purchase
The biological characteristic of specified recipient；Feature obtains module 23 and is determined for being acquired by vending machine and the picking side that uploads
Biological characteristic；If shipment instruction sending module 25 can be used for the biological characteristic of recipient and the biological characteristic of picking side
Match, then sends shipment instruction to vending machine.
According to an exemplary embodiment of the present disclosure, biological characteristic is face characteristic；With reference to Fig. 3, information determination module 21 can
To include information determination unit 301.
Specifically, information determination unit 301 is determined for the facial image of the recipient of purchaser's upload.
According to an exemplary embodiment of the present disclosure, with reference to Fig. 4, vending machine goods selling equipment 4 is compared to vending machine goods selling equipment
2, it can also include histogram building module 41 and histogram similarity calculation module 43.
Specifically, the histogram that histogram building module 41 can be used for constructing the facial image of recipient is straight as first
Fang Tu, and construct picking side facial image histogram as the second histogram；Histogram similarity calculation module 43 can
With the similarity for calculating the first histogram and the second histogram；Wherein, if the phase of the first histogram and the second histogram
It is greater than the first preset threshold like degree, then the biometric matches of the biological characteristic of recipient and picking side.
According to an exemplary embodiment of the present disclosure, with reference to Fig. 5, vending machine goods selling equipment 5 is compared to vending machine goods selling equipment
2, it can also include fisrt feature extraction module 51, second feature extraction module 53 and characteristic similarity computing module 55.
Specifically, the convolutional neural networks extraction after fisrt feature extraction module 51 can be used for having trained using one is received
The feature vector of the facial image of side is as first eigenvector；Second feature extraction module 53 can be used for using convolutional Neural
Network extracts the feature vector of the facial image of picking side as second feature vector；Characteristic similarity computing module 55 can be used
In the cosine similarity for calculating first eigenvector and second feature vector；Wherein, if calculated cosine similarity is greater than
Second preset threshold, then biometric matches of the biological characteristic of recipient and picking side.
According to an exemplary embodiment of the present disclosure, purchaser and recipient are the registration user of machine platform of selling goods；With reference to
Fig. 6, information determination module 21 include mark determination unit 601 and biological characteristic determination unit 603.
Specifically, the selected operation determination of recipient that mark determination unit 601 can be used for carrying out based on purchaser is received
The identification information of side；Biological characteristic determination unit 603 can be used for according to the identification information of recipient from registration user information database
The biological characteristic of middle determining recipient.
According to an exemplary embodiment of the present disclosure, with reference to Fig. 7, it may include that contact method obtains list that feature, which obtains module 23,
Member 701, consignee location acquiring unit 703, vending machine determination unit 705 and address transmission unit 707.
Specifically, contact method acquiring unit 701 can be used for obtaining the contact method of recipient；Consignee location obtains
Unit 703 can be used for the contact method based on recipient and send position acquisition request to the terminal of recipient, receive to obtain
The position of cargo interests；Vending machine determination unit 705 is determined for the vending machine nearest with the positional distance of recipient；Address hair
The terminal for sending unit 707 to can be used for for being sent to the address of the vending machine nearest with the positional distance of recipient recipient, with
Just recipient arrives at vending machine.
According to an exemplary embodiment of the present disclosure, with reference to Fig. 8, vending machine goods selling equipment 8 is compared to vending machine goods selling equipment
2, it can also include that delivery information obtains module 81 and delivery information sending module 83.
Specifically, delivery information, which obtains module 81, can be used for obtaining the delivery information determined by recipient；Delivery information
Sending module 83 can be used for for delivery information being sent to a delivery company, so that the commodity that purchaser buys are passed by delivery company
It send to address corresponding with delivery information.
Vending machine goods selling equipment according to the exemplary embodiment of the disclosure based on living things feature recognition, on the one hand, this
It is open to buy commodity on vending machine for other people, and buyer is without reaching vending machine；On the other hand, the disclosure can be real
Commodity process is now remotely bought, it is easy to operate for buyer, for recipient, due to directlying adopt biological spy
The mode of sign carries out picking, and without carrying other articles, process is convenient.
Since each functional module and the above method of the program analysis of running performance device of embodiment of the present invention are invented
It is identical in embodiment, therefore details are not described herein.
In an exemplary embodiment of the disclosure, a kind of computer readable storage medium is additionally provided, energy is stored thereon with
Enough realize the program product of this specification above method.In some possible embodiments, various aspects of the invention may be used also
In the form of being embodied as a kind of program product comprising program code, when described program product is run on the terminal device, institute
Program code is stated for executing the terminal device described in above-mentioned " illustrative methods " part of this specification according to this hair
The step of bright various illustrative embodiments.
Refering to what is shown in Fig. 9, describing the program product for realizing the above method of embodiment according to the present invention
900, can using portable compact disc read only memory (CD-ROM) and including program code, and can in terminal device,
Such as it is run on PC.However, program product of the invention is without being limited thereto, in this document, readable storage medium storing program for executing can be with
To be any include or the tangible medium of storage program, the program can be commanded execution system, device or device use or
It is in connection.
Described program product can be using any combination of one or more readable mediums.Readable medium can be readable letter
Number medium or readable storage medium storing program for executing.Readable storage medium storing program for executing for example can be but be not limited to electricity, magnetic, optical, electromagnetic, infrared ray or
System, device or the device of semiconductor, or any above combination.The more specific example of readable storage medium storing program for executing is (non exhaustive
List) include: electrical connection with one or more conducting wires, portable disc, hard disk, random access memory (RAM), read-only
Memory (ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, portable compact disc read only memory
(CD-ROM), light storage device, magnetic memory device or above-mentioned any appropriate combination.
Computer-readable signal media may include in a base band or as carrier wave a part propagate data-signal,
In carry readable program code.The data-signal of this propagation can take various forms, including but not limited to electromagnetic signal,
Optical signal or above-mentioned any appropriate combination.Readable signal medium can also be any readable Jie other than readable storage medium storing program for executing
Matter, the readable medium can send, propagate or transmit for by instruction execution system, device or device use or and its
The program of combined use.
The program code for including on readable medium can transmit with any suitable medium, including but not limited to wirelessly, have
Line, optical cable, RF etc. or above-mentioned any appropriate combination.
The program for executing operation of the present invention can be write with any combination of one or more programming languages
Code, described program design language include object oriented program language-Java, C++ etc., further include conventional
Procedural programming language-such as " C " language or similar programming language.Program code can be fully in user
It calculates and executes in equipment, partly executes on a user device, being executed as an independent software package, partially in user's calculating
Upper side point is executed on a remote computing or is executed in remote computing device or server completely.It is being related to far
Journey calculates in the situation of equipment, and remote computing device can pass through the network of any kind, including local area network (LAN) or wide area network
(WAN), it is connected to user calculating equipment, or, it may be connected to external computing device (such as utilize ISP
To be connected by internet).
In an exemplary embodiment of the disclosure, a kind of electronic equipment that can be realized the above method is additionally provided.
Person of ordinary skill in the field it is understood that various aspects of the invention can be implemented as system, method or
Program product.Therefore, various aspects of the invention can be embodied in the following forms, it may be assumed that complete hardware embodiment, complete
The embodiment combined in terms of full Software Implementation (including firmware, microcode etc.) or hardware and software, can unite here
Referred to as circuit, " module " or " system ".
The electronic equipment 1000 of this embodiment according to the present invention is described referring to Figure 10.The electricity that Figure 10 is shown
Sub- equipment 1000 is only an example, should not function to the embodiment of the present invention and use scope bring any restrictions.
As shown in Figure 10, electronic equipment 1000 is showed in the form of universal computing device.The component of electronic equipment 1000 can
To include but is not limited to: at least one above-mentioned processing unit 1010, connects not homologous ray at least one above-mentioned storage unit 1020
The bus 1030 of component (including storage unit 1020 and processing unit 1010), display unit 1040.
Wherein, the storage unit is stored with program code, and said program code can be held by the processing unit 1010
Row, so that various according to the present invention described in the execution of the processing unit 1010 above-mentioned " illustrative methods " part of this specification
The step of illustrative embodiments.For example, the processing unit 1010 can execute step S12 as shown in fig. 1 to step
S16。
Storage unit 1020 may include the readable medium of volatile memory cell form, such as Random Access Storage Unit
(RAM) 10201 and/or cache memory unit 10202, it can further include read-only memory unit (ROM) 10203.
Storage unit 1020 can also include program/utility with one group of (at least one) program module 10205
10204, such program module 10205 includes but is not limited to: operating system, one or more application program, other programs
It may include the realization of network environment in module and program data, each of these examples or certain combination.
Bus 1030 can be to indicate one of a few class bus structures or a variety of, including storage unit bus or storage
Cell controller, peripheral bus, graphics acceleration port, processing unit use any bus structures in a variety of bus structures
Local bus.
Electronic equipment 1000 can also be with one or more external equipments 1100 (such as keyboard, sensing equipment, bluetooth equipment
Deng) communication, can also be enabled a user to one or more equipment interact with the electronic equipment 1000 communicate, and/or with make
The electronic equipment 1000 can with it is one or more of the other calculating equipment be communicated any equipment (such as router, modulation
Demodulator etc.) communication.This communication can be carried out by input/output (I/O) interface 1050.Also, electronic equipment 1000
Network adapter 1060 and one or more network (such as local area network (LAN), wide area network (WAN) and/or public affairs can also be passed through
Common network network, such as internet) communication.As shown, network adapter 1060 passes through its of bus 1030 and electronic equipment 1000
The communication of its module.It should be understood that although not shown in the drawings, other hardware and/or software can be used in conjunction with electronic equipment 1000
Module, including but not limited to: microcode, device driver, redundant processing unit, external disk drive array, RAID system, magnetic
Tape drive and data backup storage system etc..
Through the above description of the embodiments, those skilled in the art is it can be readily appreciated that example described herein is implemented
Mode can also be realized by software realization in such a way that software is in conjunction with necessary hardware.Therefore, according to the disclosure
The technical solution of embodiment can be embodied in the form of software products, which can store non-volatile at one
Property storage medium (can be CD-ROM, USB flash disk, mobile hard disk etc.) in or network on, including some instructions are so that a calculating
Equipment (can be personal computer, server, terminal installation or network equipment etc.) is executed according to disclosure embodiment
Method.
In addition, above-mentioned attached drawing is only the schematic theory of processing included by method according to an exemplary embodiment of the present invention
It is bright, rather than limit purpose.It can be readily appreciated that the time that above-mentioned processing shown in the drawings did not indicated or limited these processing is suitable
Sequence.In addition, be also easy to understand, these processing, which can be, for example either synchronously or asynchronously to be executed in multiple modules.
It should be noted that although being referred to several modules or list for acting the equipment executed in the above detailed description
Member, but this division is not enforceable.In fact, according to embodiment of the present disclosure, it is above-described two or more
Module or the feature and function of unit can embody in a module or unit.Conversely, an above-described mould
The feature and function of block or unit can be to be embodied by multiple modules or unit with further division.
Those skilled in the art after considering the specification and implementing the invention disclosed here, will readily occur to its of the disclosure
His embodiment.This application is intended to cover any variations, uses, or adaptations of the disclosure, these modifications, purposes or
Adaptive change follow the general principles of this disclosure and including the undocumented common knowledge in the art of the disclosure or
Conventional techniques.The description and examples are only to be considered as illustrative, and the true scope and spirit of the disclosure are by claim
It points out.
It should be understood that the present disclosure is not limited to the precise structures that have been described above and shown in the drawings, and
And various modifications and changes may be made without departing from the scope thereof.The scope of the present disclosure is only limited by the attached claims.
Claims (10)
1. a kind of vending machine good selling method based on living things feature recognition characterized by comprising
Determine the merchandise news of the commodity of purchaser's purchase and the biological characteristic of recipient that purchaser specifies；
Determine the biological characteristic for the picking side for being acquired and being uploaded by vending machine；
If the biometric matches of the biological characteristic of the recipient and the picking side, shipment is sent to the vending machine
Instruction.
2. vending machine good selling method according to claim 1, which is characterized in that the biological characteristic is face characteristic；Its
In, determine that the biological characteristic for the recipient that purchaser specifies includes:
Determine the facial image for the recipient that purchaser uploads.
3. vending machine good selling method according to claim 2, which is characterized in that the vending machine good selling method further include:
The histogram of the facial image of recipient is constructed as the first histogram, and constructs the histogram of the facial image of picking side
Figure is used as the second histogram；
Calculate the similarity of first histogram Yu second histogram；
Wherein, if the similarity of first histogram and second histogram is greater than the first preset threshold, the receipts
The biometric matches of the biological characteristic of cargo interests and the picking side.
4. vending machine good selling method according to claim 2, which is characterized in that the vending machine good selling method further include:
Convolutional neural networks after being had trained using one extract the feature vector of the facial image of recipient as fisrt feature to
Amount；
The feature vector of the facial image of the picking side is extracted as second feature vector using the convolutional neural networks；
Calculate the cosine similarity of the first eigenvector Yu the second feature vector；
Wherein, if calculated cosine similarity be greater than the second preset threshold, the biological characteristic of the recipient with it is described
The biometric matches of picking side.
5. vending machine good selling method according to claim 1, which is characterized in that purchaser and recipient are that vending machine is flat
The registration user of platform；Wherein it is determined that the biological characteristic for the recipient that purchaser specifies includes:
The selected identification information for operating determining recipient of recipient carried out based on purchaser；
The biological characteristic of recipient is determined from registration user information database according to the identification information of recipient.
6. vending machine good selling method according to claim 1, which is characterized in that the vending machine good selling method further include:
Obtain the contact method of recipient；
Contact method based on the recipient sends position acquisition request to the terminal of the recipient, to obtain the receipts
The position of cargo interests；
The determining vending machine nearest with the positional distance of the recipient；
The address of the vending machine nearest with the positional distance of the recipient is sent to the terminal of the recipient, so as to described
Recipient arrives at the vending machine.
7. vending machine good selling method according to claim 1, which is characterized in that sending shipment instruction to the vending machine
Afterwards, the vending machine good selling method further include:
Obtain the delivery information determined by the recipient；
The delivery information is sent to a delivery company, so that the commodity that the delivery company buys the purchaser deliver
To address corresponding with the delivery information.
8. a kind of vending machine goods selling equipment based on living things feature recognition characterized by comprising
Information determination module, the life for the recipient that merchandise news and purchaser for determining the commodity of purchaser's purchase are specified
Object feature；
Feature obtains module, for determining the biological characteristic for the picking side for being acquired and being uploaded by vending machine；
Shipment instruction sending module, if for the biological characteristic of the recipient and the biometric matches of the picking side,
Then shipment instruction is sent to the vending machine.
9. a kind of storage medium, is stored thereon with computer program, which is characterized in that the computer program is executed by processor
Vending machine good selling method described in Shi Shixian any one of claims 1 to 7 based on living things feature recognition.
10. a kind of electronic equipment characterized by comprising
Processor；And
Memory, for storing the executable instruction of the processor；
Wherein, the processor is configured to come described in any one of perform claim requirement 1 to 7 via the execution executable instruction
The vending machine good selling method based on living things feature recognition.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN201910003266.4A CN109858378A (en) | 2019-01-03 | 2019-01-03 | Vending machine good selling method and device, medium and equipment based on living things feature recognition |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910003266.4A CN109858378A (en) | 2019-01-03 | 2019-01-03 | Vending machine good selling method and device, medium and equipment based on living things feature recognition |
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| CN201910003266.4A Pending CN109858378A (en) | 2019-01-03 | 2019-01-03 | Vending machine good selling method and device, medium and equipment based on living things feature recognition |
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