CN110135852B

CN110135852B - Riding payment method, riding payment system, payment acceptance equipment and server

Info

Publication number: CN110135852B
Application number: CN201910308712.2A
Authority: CN
Inventors: 郑嵩; 蒋文军; 程亮; 张活林; 赵灵军; 刘金瑞
Original assignee: Shenzhen Emperor Technology Co Ltd
Current assignee: Shenzhen Emperor Technology Co Ltd
Priority date: 2019-04-17
Filing date: 2019-04-17
Publication date: 2023-11-14
Anticipated expiration: 2039-04-17
Also published as: CN110135852A

Abstract

The embodiment of the invention discloses a riding payment method, which comprises the following steps: and responding to the triggering operation, starting a face recognition function, scanning and recognizing the face of the passenger through the face recognition function to obtain a target face image, and interacting with a server according to the target face image and riding information to finish corresponding deduction operation. The riding payment method can effectively prevent the situation of mistakenly brushing the face. In addition, a riding payment system, a payment acceptance device and a server are also provided.

Description

Riding payment method, riding payment system, payment acceptance equipment and server

Technical Field

The invention relates to the technical field of riding equipment processing, in particular to a riding payment method, a riding payment system, a payment acceptance device and a server.

Background

With the development of face recognition technology, face payment gradually appears in various occasions, and riding fee deduction is carried out by adopting the face payment technology in the public transportation field, so that the travel of people is greatly facilitated. The traditional face payment technology is to directly identify each face passing through a face acquisition area and then directly deduct money. However, in the public travel field, there are generally a plurality of payment functions, for example, code scanning riding, card swiping riding and the like may exist at the same time. For a passenger who has swiped a card or a passenger who swipes a code, the passenger is also swiped by the face acquisition area, i.e. the possibility that the passenger is swiped by mistake is high.

Disclosure of Invention

In view of the above, it is necessary to propose a riding payment system and method that can prevent being misapplied.

A ride payment method, the method comprising:

responding to the triggering operation, and starting a face recognition function;

scanning and identifying the face of the passenger through the face identification function to obtain a target face image;

and interacting with a server according to the target face image and the riding information to finish corresponding fee deduction operation.

A ride payment method, the method comprising:

receiving a target face image and riding information sent by a payment acceptance device, wherein the target face image is obtained by scanning the face of a passenger by the payment acceptance device in response to triggering operation to start a face recognition function;

and matching the target face image with the face image in the registered real-name account, and when the matching is successful, deducting fees according to the riding information and returning corresponding deduction information.

A ride payment system, the system comprising: payment acceptance equipment and a server;

the payment acceptance device comprises: the face recognition module and the face recognition triggering module;

The face recognition module is used for carrying out scanning recognition on the face of the passenger and sending the scanned target face image and riding information to the server;

the face recognition triggering module is used for responding to triggering operation to start the face recognition module;

the server is used for completing corresponding deduction operation according to the received target face image and riding information.

A payment acceptance device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the steps of:

A server comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the steps of:

According to the riding payment method, system, payment acceptance equipment and server, the face recognition function is started only by responding to the triggering operation of the user, the problem of misbrushing the face is effectively solved by adding the face recognition triggering module, and the deduction operation of face payment is completed through interaction between the face recognition module and the server.

Drawings

In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

Wherein:

FIG. 1 is a flow chart of a ride payment method applied to a payment acceptance device in one embodiment;

FIG. 2 is a flow chart of a ride payment method applied to a payment acceptance device in another embodiment;

FIG. 3 is a flow chart of a ride payment method applied to a server in one embodiment;

FIG. 4 is a flow chart of a ride payment method applied to a server in another embodiment;

FIG. 5 is an architecture diagram of a ride payment system in one embodiment;

FIG. 6 is a block diagram of the internal architecture of a payment acceptance device in one embodiment;

FIG. 7 is a block diagram of the internal architecture of a server in one embodiment;

FIG. 8 is an architecture diagram of a ride payment system in another embodiment;

FIG. 9 is a block diagram of the internal structure of a terminal in one embodiment;

FIG. 10 is an architecture diagram of a ride payment system in yet another embodiment;

FIG. 11 is a flow diagram of real-name account registration in one embodiment;

FIG. 12 is a schematic diagram of real-name account business transaction flow in one embodiment;

FIG. 13 is a schematic diagram of an abnormal consumption flow in one embodiment;

FIG. 14 is a schematic diagram of a blacklist service process flow in one embodiment;

FIG. 15 is a schematic diagram of a process flow of face payment in one embodiment;

FIG. 16 is a schematic diagram of a server-side business process flow in one embodiment;

FIG. 17 is an internal block diagram of a payment acceptance device in one embodiment;

FIG. 18 is an internal block diagram of a server in one embodiment.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

As shown in fig. 1, in one embodiment, there is provided a riding payment method applied to a payment acceptance apparatus, the method including:

step 102, in response to the triggering operation, the face recognition function is started.

In order to prevent the user from being mistakenly swiped during the payment, an operation of triggering the face recognition function is added, and the willingness to pay of the user is confirmed through the triggering operation. The triggering operation can be triggered in a plurality of modes, for example, the face recognition function can be started by pressing a corresponding button, the triggering operation can be triggered by a touch screen, for example, the triggering operation can be triggered by dragging a jigsaw block to complete a jigsaw on the touch screen, the triggering operation can be triggered by sequentially clicking characters or words on the touch screen, the triggering operation can be triggered by directly sliding the touch screen according to the arrow indication direction, and the like. In addition, the triggering operation may be triggered by sensing (e.g., sound, gesture, etc.), for example, by voice, or may be triggered by waving an arm according to a direction, or waving a palm, etc., although the triggering manner may be other manners, and the triggering manner is not limited in any way. The face recognition function is a function of scanning and recognizing a face.

And 104, scanning and identifying the face of the passenger through a face identification function to obtain a target face image.

The face recognition function can be realized by adopting a camera, and a target face image is obtained by scanning and shooting the face of the passenger. The target face image is an image containing the faces of the passengers.

And 106, interacting with the server according to the target face image and the riding information to finish corresponding deduction operation.

After the target face image is scanned, the target face image and riding information can be sent to the server, the server matches corresponding users (each user is associated with a fee deduction account) according to the target face image, and fee deduction operation is completed according to the riding information.

The bus information contains different information under different scenes, for example, for a bus route with fixed bus charge, the bus information only needs to include route information, and for the bus information which needs to determine the charge according to the station, the bus information needs to include station information (for example, up-down station information). In another embodiment, the deduction of the fare may be preset by the attendant through the handset, and the riding information includes: information on the cost of riding.

For bus scenes, the station information can be determined by positioning the position of the payment acceptance device, and the positioning mode can adopt GPS positioning, and can adopt other modes of positioning. For a subway or light rail scene, the station information may be information stored in advance in the payment acceptance apparatus.

In another embodiment, the payment acceptance device may compare the target face image with the faces in the white list face library, and if the target face image exists in the white list face library, the comparison result, the target face image and the riding information are directly sent to the server together, and the server directly completes the fee deduction operation according to the comparison result, without comparison.

According to the riding payment method, the face recognition function is started only by responding to the triggering operation of the user, the problem of misbrushing the face is effectively solved by adding the face recognition triggering function, and the deduction operation of face payment is completed through interaction between the face recognition module and the server.

In one embodiment, after the face of the passenger is scanned and identified by the face recognition function, the method further comprises the steps of: and comparing the target face image with the face images in the blacklist face library to obtain a comparison result, and outputting corresponding prompt information according to the comparison result.

The payment acceptance device stores a blacklist face library, after a target face image is scanned by a face recognition function, the target face image is compared with the face image in the blacklist face library to obtain a comparison result, if the target face image is matched with the face image in the blacklist face library, the passenger is a blacklist person, the face brushing failure is indicated, corresponding face brushing failure prompt information (such as arrearage and charging request) can be returned, and if the target face image is not matched with the face image in the blacklist face library, the information of successful face brushing can be returned directly in order to improve the face brushing efficiency.

In one embodiment, the blacklist face library is issued to the payment acceptance device in advance by the server or is actively acquired from the server by the payment acceptance device, and the blacklist offline comparison can be completed directly in the payment acceptance device by adopting the blacklist face library. In this embodiment, only the information about whether the corresponding face brushing is successful or not can be returned by comparing with the local black name single face library, so that offline face brushing can be realized, and when a network exists in the follow-up process, the collected target face image and riding information can be asynchronously sent to the server, and the deduction is completed in the follow-up process of the server, so that the trip efficiency is prevented from being influenced due to the network.

The prompt information can be set in a self-defined mode according to actual requirements, for example, if the face brushing fails, the prompt information of defaulting and recharging can be output, and if the face brushing is successful, the prompt information of the face brushing is successful can be output. The prompting mode can be displayed on a screen or can be a voice broadcasting mode.

In the above embodiment, the offline comparison can be realized by adopting the blacklist face library to perform the comparison at the payment acceptance device, and the offline comparison is uploaded to the server to deduct fees when a network exists, so that the face brushing efficiency is improved, and the face brushing payment can be rapidly completed even under the condition of poor network.

In one embodiment, the blacklist face library is a line blacklist face library associated with a line obtained from a server.

Because the blacklist face library of the whole network may have a lot of data, in order to improve the matching speed and reduce the load of the payment acceptance terminal, each payment acceptance device stores a line blacklist face library associated with a line. The line blacklist face library is obtained through the habit of the server on the riding behavior of the faces in the blacklist face library. In the embodiment, the load of the payment acceptance equipment can be greatly reduced by adopting the line blacklist face library, and the face comparison speed is improved.

In one embodiment, outputting corresponding prompt information according to the comparison result includes: when the target face image is not in the black name single face library, outputting a prompt message of successful face brushing; and outputting a prompt message of failed face brushing when the target face image is in the blacklist face library.

The specific prompt information of successful face brushing may be set in a user-defined manner, for example, may be set as "successful face brushing", may be set as "successful payment", and may also be set as "please pass" or the like representing successful face brushing. Similarly, specific prompt information of the face brushing failure can be set in a self-defined manner, for example, the prompt information can be set as 'insufficient balance, charging request' or 'arrearage, charging request', etc. Through outputting the prompt information, whether the passenger is successful in face brushing or not can be clearly informed, and the passenger riding payment behavior can be effectively monitored.

In one embodiment, outputting the corresponding prompt information according to the comparison result further includes: when the target face image is not in the blackname single face library, judging whether fee deduction information returned by the server is received within preset time; if yes, corresponding prompt information is returned according to the fee deduction information; if not, directly outputting preset prompt information.

When the target face image is judged not to be in the black name single face library, the target face image and riding information are sent to the server for fee deduction, when the network is better, the returned fee deduction information can be received in a short time, but when the network is poorer, the returned fee deduction information can be received in a longer time. In order not to delay the riding efficiency of passengers, if the returned information is not received within the preset time, the preset prompting information is directly output, for example, "the face is brushed successfully, and the passenger is requested to pass through". In the above embodiment, when the returned deduction information is not received within the preset time, the preset prompt information is directly output, which is favorable for improving the face-brushing payment efficiency under the condition of bad network, thereby bringing good experience to passengers.

In one embodiment, the riding payment method further includes: when the target face image is not in the blackname single face library, the target face image and riding information are sent to a server; and receiving fee deduction information returned by the server according to the target face image and the riding information.

When the target face image is not in the blackname single face library, the target face image and riding information are sent to the server, and fee deduction information returned by the server is received. The fee deduction information is divided into fee deduction success information and fee deduction failure information. When the information is in the blacklist face library, the information of refusing riding is directly returned, and the information is not required to be sent to the server for judgment. In one embodiment, when the deduction information is that the deduction is successful, a prompt message of successful face brushing is output; and outputting a prompt message of failure of face brushing when the deduction information is that the deduction is failed.

In one embodiment, before the step of interacting with the server according to the target face image and the riding information to complete the corresponding deduction operation, the method further comprises: comparing the target face image with face images in a white list face library to obtain a comparison result; when the target face image is in the white list face library, pre-deducting fees are carried out, and prompt information of successful face brushing is output; according to the target face image and riding information, interacting with a server to complete corresponding deduction operation, including: and sending the target face image and the pre-deduction to a server, so that the server finishes deduction in a deduction account corresponding to the target face image according to the pre-deduction.

Wherein the payment acceptance device further includes: a white name single face library. Comparing the target face image with the face images in the white list face library, when the target face image is in the white list single face library, pre-deducting fees, outputting successful face brushing, sending the pre-deducting fees and the target face image to a server, and completing actual fee deduction according to the pre-deducting fees by the server. The pre-deduction includes: deduction account information corresponding to the pre-deduction can be directly deducted at the server according to the deduction account information in the pre-deduction, and user comparison is not needed by the server, so that payment efficiency is improved, and satisfaction of passengers is improved.

In one embodiment, the white list face library is a line white list single face library, the server analyzes riding behaviors of passengers to obtain routes frequently taken by the passengers, sorts the passengers according to the liveness (frequency) of taking a certain line, adds the passengers with liveness ranked in a preset name (for example, the first 1000) to a variable list of the line, and then sends the variable list to a payment acceptance device of the corresponding line. Therefore, under the condition of poor network or network disconnection, the face images in the line white-name single face library are conveniently compared, and the pre-deduction can be performed first if the comparison is successful, so that the payment efficiency is improved.

In one embodiment, the sending the target face image and the riding information to the server, so that the server completes corresponding deduction operation according to the target face image and the riding information, includes: and sending the target face image and riding information to a server, indicating the server to match the target face image with the face image in the registered real-name account, and deducting fees and returning corresponding fee deduction information when the matching is successful.

The payment acceptance device sends the target face image and riding information to the server, the server matches the target face image with the face image in the registered real-name account, deducts fees, and returns fee deduction information to the payment acceptance device.

As shown in fig. 2, in one embodiment, a riding payment method is provided, including:

step 202, in response to the triggering operation, the face recognition function is started.

And 204, scanning and identifying the face of the passenger through a face identification function to obtain a target face image.

Step 206, comparing the target face image with face images in the blacklist face library and the whitelist face library respectively to obtain a comparison result, when the target face image is in the blacklist face library, entering step 208, when the target face image is in the whitelist face library, entering step 210, and when the target face image is neither in the blacklist face library nor in the whitelist face library, entering step 209.

The comparison modes are two, and the first mode is as follows: comparing the target face image with the face image in the blacklist face library, outputting prompt information of failure in face brushing when the target face image is in the blacklist face library, comparing the target face image with the face image in the whitelist face library when the target face image is not in the blacklist face library, pre-charging if the target face image is in the whitelist face library, outputting prompt information of success in face brushing, and sending the target face image and riding information to a server if the target face image is not in the whitelist face library so that the server can finish charging. Alternatively, the comparison may be performed with faces in the white list face library, and then with faces in the black list face library.

In another embodiment, the whitelist face library in the payment acceptance device is a line whitelist face library associated with the line. Because the full-network white-name single face library may have a lot of data, in order to improve the matching speed and reduce the load of the payment acceptance terminal, each payment acceptance device stores a line white-name single face library associated with a line. The line white-name single face library is obtained through riding behavior habits of faces in the line white-name single face library by a server. In the embodiment, the load of the payment acceptance equipment can be greatly reduced by adopting the line white name single face library, and the face comparison speed is improved.

Step 208, outputting prompt information of failure of face brushing.

And step 209, the target face image and the riding information are sent to the server, so that the server finishes fee deduction according to the target face image and the riding information.

Step 210, pre-deducting fees and outputting prompt information of successful face brushing.

And step 212, the target face image and the pre-deduction are sent to the server, so that the server finishes deduction in a deduction account corresponding to the target face image according to the pre-deduction.

As shown in fig. 3, in one embodiment, a riding payment method is provided, applied to a server, and the method includes:

Step 302, receiving a target face image and riding information sent by a payment acceptance device, wherein the target face image is obtained by the payment acceptance device in response to triggering operation to start a face recognition function to scan the face of a passenger.

The server receives the target face image and riding information uploaded by the payment acceptance device. The riding information includes: one or more of information such as a bus route, bus station, bus time, etc. The riding station comprises: a get-on station and a get-off station. The target face image is obtained by the payment acceptance device responding to the triggering operation and starting the face recognition function to scan. If a bus scene only comprises an upper station point, if a subway is needed to comprise the upper station point and a lower station point.

Step 304, matching the target face image with the face image in the registered real-name account, and when the matching is successful, deducting fees and returning corresponding deduction information.

The server matches the target face image with the face image in the registered real-name account, deducts fees if the matching is successful, and returns fee deduction information. In one embodiment, the similarity between the target face image and the face image corresponding to the registered real-name account is calculated, and when the similarity is greater than a preset threshold (for example, 99%), it is determined that the two correspond to the same person.

In the embodiment of the riding payment method, the payment acceptance device starts the face recognition function in response to the triggering operation, then the scanned target face image and riding information are sent to the server, the server carries out fee deduction when matching is successful through matching with the face image in the real-name account, corresponding fee deduction information is returned, and false face brushing is avoided through the triggering operation of the payment acceptance device.

As shown in fig. 4, in one embodiment, a riding payment method is provided, applied to a server, including:

and step 402, receiving a target face image and riding information sent by a payment acceptance device, wherein the target face image is obtained by the payment acceptance device by scanning the face of a passenger by starting a face recognition function in response to a trigger operation.

Step 404, matching the target face image with the face image in the registered real-name account, and when the target face image is matched with the real-name account, performing fee deduction operation; when the real name account is not matched, step 406 is entered.

Step 406, matching the target face image with the face image in the established credit account, if the matching with the established credit account is successful, entering step 408, and if the matching with the credit account is not successful, entering step 410.

Step 408, associating the riding information corresponding to the target face image with the credit account, and recording the arrearage amount corresponding to the credit account;

step 410, creating a new credit account, associating the target face image and the riding information with the new credit account, and recording the arrearage amount corresponding to the new credit account.

The face payment is to register real names in advance, so that the face image corresponding to the registered real name account is stored in the server. In order to enable the user which is not registered to experience the face payment function first, the user can experience the face payment riding function first for free, and a credit account is created in the server. Specifically, after receiving the target face image and the riding information uploaded by the payment acceptance device, the server firstly matches the target face image with the face image in the registered real-name account, if the matching is successful, fee deduction is correspondingly carried out, and the riding information and the real-name account are stored in an associated mode, namely the riding record of the passenger is stored. If the matching is unsuccessful, the user is not registered with the real name, the user is matched with the face image in the established credit account, if the matching is successful, the riding information corresponding to the target face image is associated with the established credit account, and the arrearage corresponding to the credit account is recorded. If the credit account is not matched, the user is the first experience, a new credit account is created, the target face image and riding information are associated with the new credit account, and the corresponding arrearage amount is recorded. In order to make the user unable to experience free for unlimited times, the amount of the arrears amount can be limited, for example, the user can experience free for three times, if each riding is 2 yuan, then 6 yuan can be used as the arrears amount, when the arrears amount is exceeded, the user is not allowed to continue riding, and the user is prompted to finish real-name registration as soon as possible to recharge.

In the above embodiment, by establishing the credit account, the user can experience the function of the face-brushing riding under the condition that the user is not registered yet, so that more people can use the function of the face-brushing riding.

In one embodiment, the riding payment method further includes: comparing the target face image with face images in a blacklist face library; and if the target face image exists in the black name single face library, returning the refusal riding information to the payment acceptance equipment.

The server stores a full-network black name single face library, compares the target face image with face images in the black list face library after receiving the target face image, and returns refusal riding information to the payment acceptance equipment when the target face image exists in the black list face library.

In one embodiment, the riding payment method further includes: obtaining riding information associated with a real name account or a credit account, wherein the riding information comprises the following steps of: a bus route and a bus station; and analyzing the behavior habits of passengers corresponding to the real-name accounts or the credit accounts according to the riding information, and establishing riding files corresponding to each real-name account or each credit account.

Wherein, in order to establish the riding profile with each passenger, the server acquires riding information of each passenger, the riding information comprising: ride route, ride stop, ride time, ride consumption record, and the like. The behavior habit of the user is analyzed according to the riding information of the user, for example, a route frequently ridden by the user, a time point frequently ridden by the user and the like are analyzed. By establishing the riding profile corresponding to each real-name account or credit account, the riding profile of the passengers can be analyzed, for example, riding behaviors of the users in the blacklist face library can be analyzed, and the circuit blacklist can be established in a targeted manner.

In one embodiment, the riding payment method further includes: obtaining a riding archive corresponding to face images in a blacklist face library, determining blacklist line information corresponding to passengers in the blacklist face library according to the riding archive, determining a line blacklist according to the blacklist line information, and correspondingly transmitting the line blacklist to payment acceptance equipment corresponding to the corresponding line.

Based on behavior analysis, historical riding information corresponding to face images in a blacklist face library can be analyzed, riding habits corresponding to the face images in the blacklist are analyzed, a corresponding line blacklist is determined according to the riding habits, and the line blacklist is issued to payment acceptance equipment corresponding to the line. Because the data size of the blacklist of the whole network is large, in order to reduce the number of the blacklists in the payment acceptance equipment, a circuit blacklist corresponding to each circuit is established, namely, the blacklist is associated with the circuit by analyzing the frequent riding circuit of a user in the blacklist, so that the blacklist can be issued to the corresponding circuit in a focused way, all the blacklists are not required to be issued to each payment acceptance equipment, the data storage amount in the payment acceptance equipment is greatly reduced, and the illegal riding behavior of passengers can be more effectively controlled.

In one embodiment, the riding payment method further includes: receiving a real-name registration request sent by a user terminal, wherein the real-name registration request comprises a registration face image and a corresponding deduction account; and distributing a unique real-name account for the corresponding user according to the registered face image, and carrying out association storage on the real-name account, the registered face image and the deduction account.

The method comprises the steps of installing a corresponding APP (application program) in a terminal, and then performing real-name registration through the APP. When registering real names, the registered face images and the deduction accounts are required to be sent to the server through the terminal, the server distributes unique real name accounts according to the registered face images, and the real name accounts, the registered face images and the deduction accounts are associated. And when the target face image consistent with the registered face image is recognized later, carrying out riding fee deduction directly from the deduction account.

In one embodiment, assigning unique real-name accounts to respective users based on registered face images includes: searching whether a credit account corresponding to the registered face image exists or not according to the registered face image, and if the corresponding credit account exists, upgrading the credit account into a real-name account; if the corresponding credit account does not exist, a unique real-name account is directly allocated to the registered face image.

The user applying for real-name registration is likely to be the user who has experienced face payment before, the credit account corresponding to the passenger is stored in the server, then the server directly upgrades the credit account into the real-name account, and if the user applying for real-name registration does not have the credit account before, a real-name account is directly created and allocated to the user.

In one embodiment, matching the target face image with face images in a registered real-name account comprises acquiring a historical riding record corresponding to each face image when a plurality of face images similar to the target face image exist in the real-name account or a credit account; and determining a real-name account or a credit account matched with the target face image according to the historical riding record corresponding to each face image.

In this case, since a plurality of similar faces may appear, for example, when the similarity between the plurality of face images and the target face image obtained by recognition is greater than a preset threshold, further comparison is required. In order to improve the accuracy of face recognition, when the server recognizes that a plurality of face images similar to the target face image exist, a corresponding historical riding record corresponding to each face image is acquired, and the face image matched with the target face image is assisted to be determined according to the historical riding record corresponding to each face image, namely, a matched real-name account or credit account is determined, so that face recognition can be performed more accurately.

In another embodiment, when there are multiple face images similar to the target face image, the target face image is stored and subsequently submitted to the manual platform for processing.

In the process of face-brushing payment, if a plurality of face images similar to the target face image appear, the target face image and the plurality of face images can be stored in a correlated mode, and then the face images are identified through a manual platform or a face identification auxiliary module.

When a real-name account or a credit account is created for a user, if the obtained target face image is similar to a plurality of face images, the target face image and the plurality of face images are stored in a correlated mode, and therefore the plurality of similar face images can be identified in a targeted mode conveniently.

The plurality of similar face images are identified, so that the face identification accuracy is improved, the payment safety of a user is improved, and the condition of stolen brushing or misbrushing is avoided.

In one embodiment, the riding payment method further comprises the steps of obtaining arrears corresponding to real-name accounts or credit accounts, and adding face images corresponding to the real-name accounts or the credit accounts to a black-name single face library when the arrears are larger than preset arrears. And when the arrears amount corresponding to the real-name account or the credit account is cleared, removing the corresponding face image from the blacklist face library.

In one embodiment, the determining the real-name account or the credit account matching the target face image according to the historical driving record corresponding to the real-name account or the credit account includes: acquiring current riding information corresponding to the target face image, and extracting riding parameters associated with the current riding information from historical riding records corresponding to each real-name account or credit account according to the current riding information; determining a score value corresponding to each real-name account or credit account according to the riding parameters and a preset scoring rule; and determining a real-name account or a credit account matched with the target face image according to the score value.

When there are a plurality of face images similar to the target face image, current riding information corresponding to the target face image needs to be acquired, and then riding parameters associated with the current riding information are extracted from historical riding records corresponding to the plurality of similar face images (corresponding to a plurality of real-name accounts or credit accounts), wherein the riding parameters comprise: and information such as the historical riding times corresponding to the current riding route, the time of the historical riding on the route and the like.

The establishment of the scoring rule is related to the associated times of riding and the historical times of riding, the times of riding and the score values are positively related, namely, the more the times of riding corresponding lines, the higher the corresponding score values, the more the time corresponding to the historical times of riding in the current riding information, and the higher the corresponding score values. Generally, the line on which a person takes is relatively fixed, and the riding time point is relatively fixed, for example, the daily departure time of a person may be concentrated between 7 points and 8 points, so that matching with the current riding information acquired at present according to the historical riding line and time point is beneficial to assist in judging a real-name account or a credit account matched with the target face image.

In one embodiment, after extracting the ride parameters associated with the current ride information, the score value corresponding to the real name account or the credit account is calculated using the following formula:

wherein S represents a fraction value, ω _i Representing the weight corresponding to each riding parameter, f (x _i ) And (3) representing the score value corresponding to each riding parameter, and taking the real-name account or the credit account with the highest score as the account matched with the target face image.

In one embodiment, a scoring model corresponding to each real-name account is established, the score value of each searched real-name account is determined according to the current riding information and the scoring model, and then the real-name account with the highest score value is selected as the matched real-name account.

The method comprises the steps of establishing travel files of all passengers according to riding information of all the passengers; analyzing riding parameters in the traveling files of each passenger to establish a look-up table corresponding to each riding parameter, and taking the look-up table as a scoring model associated with a real-name account; acquiring riding parameters in riding information; matching the obtained riding parameters with the lookup tables associated with the searched real-name accounts respectively to obtain scores corresponding to the riding parameters; and determining the score value of each searched real-name account according to the score value and the weight value corresponding to each key parameter.

In one embodiment, the riding payment method further includes: comparing the target face image with face images in a white list face library; and when the target face image exists in the white name single face library, returning the riding permission information to the payment acceptance device.

The server comprises a white-name single face library, and legal face images are stored in the white-name single face library. And comparing the target face image with the white list face image, and if the target face image is matched with the white list face image, returning the bus-taking permission information to the payment acceptance equipment.

In one embodiment, the riding payment method further includes: obtaining a historical bus taking record corresponding to the real name account or the credit account, wherein the historical bus taking record comprises the following steps: bus route information and bus times information; calculating a credit score value corresponding to each real-name account or credit account according to the historical bus taking record; determining a line white name single face library corresponding to each riding line according to the credit score value and the riding line information; and synchronizing the line white name single face library to the payment acceptance equipment corresponding to the corresponding line.

The historical bus taking record comprises the following steps: historical bus line information, historical bus times information, historical bus payment cost information, and the like, and a credit score value corresponding to each real name account or credit account is calculated according to the historical bus records. The credit score value is used for scoring the riding credit of the passenger, and the passenger with the high credit score value is added into the white single face library. In order to obtain the line white list, one or more corresponding lines are determined according to riding line information corresponding to the real name account or the credit account, then a line white single face library is determined, and the line white single face library is synchronized to one or more payment acceptance devices corresponding to the corresponding lines.

The credit score value is established in association with the number of times of riding and the riding consumption information, and generally, the more the number of times of riding is through the face, the higher the riding consumption and the higher the corresponding credit score value. After the credit score value is established, the users are ranked according to the credit score value. And acquiring the credit score value of the passenger in each line, and adding a real-name account or a credit account with the credit score value larger than a preset credit value into a white-name single face library of the corresponding line. The face images in the white name single face library of each line are sequenced according to the credit score value from large to small, and passengers with the preset number (for example, 1000) are synchronized to the payment acceptance equipment corresponding to the corresponding line, wherein the synchronization mode can be that the server sends the white list of the line with the preset number to the payment acceptance equipment at fixed time, or the payment acceptance equipment actively sends a request to acquire.

In the above embodiment, only the line white name single face library ranked in the preset number is synchronized to the payment acceptance device, which is beneficial to reducing the load of the payment acceptance device and improving the matching efficiency.

In one embodiment, the riding payment method further includes: acquiring a history riding record corresponding to the real-name account, wherein the history riding record comprises the following steps: the riding route information and riding frequency of riding each route; adding real-name accounts with the riding frequency larger than a preset value in each line into a line white-name single face library corresponding to the corresponding line; and synchronizing the line white name single face library to the payment acceptance equipment corresponding to the corresponding line.

The historical riding records comprise riding frequencies of historical riding lines, real-name accounts with riding frequencies larger than a preset value in each line are added into line white-name single face libraries corresponding to the corresponding lines, and updated line white-name single face libraries are synchronized to payment acceptance equipment corresponding to the corresponding lines at regular time.

In one embodiment, the riding payment method further includes: receiving a query request of a riding record or a consumption record sent by a user terminal; and sending the corresponding riding record or consumption record to the user terminal according to the inquiry request.

The user can send a query request of the riding records or the consumption records to the server through the user terminal, and then the server sends the corresponding riding records or the consumption records to the terminal for display according to the corresponding query request.

In one embodiment, the riding payment method further includes: when the arrearage amount corresponding to the face image in the blacklist face library is clear, the face image is moved out of the blacklist face library, and the blacklist face library is updated; and issuing the updated black name single face library to the payment acceptance equipment.

When the arrearage amount corresponding to the face image in the blackname single face library is clear, the face image is moved out of the blacklist face library, the blacklist face library is updated, and the server is further used for issuing the updated blackname single face library to the payment acceptance equipment.

In one embodiment, the riding payment method further includes: receiving a complaint request sent by a user terminal, wherein the complaint request comprises a record of objection; and processing according to the complaint request, and returning the processed progress to the user terminal.

When the deduction abnormal condition occurs, the user can complain about the records with objections in the user terminal, send the complaint request to the server, and can check the complaint processing flow and processing nodes in real time. Accordingly, the server returns the real-time processing flow of the complaint to the terminal in response to the complaint inquiry request of the terminal.

As shown in fig. 5, a riding payment system is proposed, which can be applied to both public transportation and urban transportation such as subway, and includes: a payment acceptance device 500 and a server 600;

the payment acceptance apparatus 500 includes: a face recognition module 502 and a face recognition trigger module 504;

the face recognition module 502 is used for scanning and recognizing the face of the passenger and sending the scanned target face image and riding information to the server;

the face recognition trigger module 504 is configured to turn on the face recognition module in response to a trigger operation;

The server 600 is configured to complete corresponding deduction operations according to the received target face image and the riding information.

The payment acceptance device 500 is used for accepting a riding payment of a user. Comprising the following steps: the device comprises a face recognition module and a face recognition triggering module. The face recognition triggering module is used for starting the face payment module, and in order to prevent false brushing, the face recognition triggering device is added to confirm the payment willingness of the passengers. The face triggering module may be implemented in various manners, for example, the face payment function may be started by a passenger through a key, or may be triggered by a touch screen type soft key or a soft keyboard, or may be triggered by sensing (such as a sound, a gesture, etc.). In one embodiment, a shielding cover and prompt information can be added outside the face recognition triggering module, so that the client is prevented from being triggered due to curiosity or accidents.

The face recognition module 502 is configured to scan and recognize a face of a passenger, and send a scanned target face image to the server 600, where the server 600 may complete a corresponding deduction operation according to the received target face image.

The riding payment system comprises a payment acceptance device and a server, wherein the payment acceptance device comprises a face recognition module and a face recognition triggering module, the face recognition triggering module is used for responding to the triggering operation of a passenger to start the face recognition module, then the face recognition module is used for scanning and recognizing the face of the passenger, then the scanned target face image is sent to the server, and the server finishes the deduction operation according to the received target face image.

In one embodiment, the payment acceptance device further includes: a blacklist module 506; the blacklist module 506 is configured to store a blacklist face library.

In another embodiment, the payment acceptance device further includes: the processing module is used for acquiring a target face image obtained by scanning by the face recognition module, comparing the target face image with face images in the blacklist face library to obtain a comparison result, and determining whether the face brushing is successful or not according to the comparison result.

The payment acceptance device is stored with a blacklist module, and the blacklist module is stored with a blacklist face library. After the face recognition module scans the target face image, the target face image is transmitted to the processing module, then the target face image is compared with the face images in the blacklist face library to obtain a comparison result, if the target face image is matched with the face images in the blacklist face library, the face recognition failure is indicated, corresponding arrearage information can be returned, and if the target face image is not matched with the face images in the blacklist face library, the face recognition success is indicated, and the face recognition success information can be returned. In one embodiment, the blacklist face library is issued to the payment acceptance device in advance by the server, so that the blacklist offline comparison can be completed directly in the payment acceptance device. In this embodiment, only the information about whether the corresponding face is successfully brushed can be returned by comparing with the local black name single face library, off-line face brushing can be realized, and the acquired target face image and riding information can be asynchronously sent to the server when a wireless network is arranged in the follow-up process, and the server can finish fee deduction in the follow-up process, so that the influence on the travel efficiency due to the network is avoided.

Referring to fig. 6, in one embodiment, the payment acceptance device further includes: an interaction module 508; the interaction module is used for receiving the returned blacklist matching result and carrying out corresponding prompt according to the result.

The payment acceptance terminal receives a comparison result of comparing the target face image with the face images in the blacklist face library through the interaction module, and then returns a corresponding prompt, for example, if the comparison result is not the blacklist face image, a prompt of 'successful face brushing' is returned. If the comparison result is the blacklist face image, a prompt of 'arrearage please recharge' is returned, wherein the prompt mode can be displayed on a screen or can be a voice broadcasting mode.

Referring to fig. 6, in one embodiment, the payment acceptance device further includes: at least one of the code scanning module 510 and the sensing module 512; the code scanning module is used for scanning the two-dimension code of the passenger and sending the two-dimension code to the server so that the server can complete the fee deduction operation; the sensing module is used for sensing a riding card of a passenger so as to finish the fee deduction operation.

In order to facilitate the user to pay in various modes, at least one of a code scanning module and an induction module is integrated in the payment acceptance equipment. The code scanning module is used for scanning the two-dimensional code presented by the passenger and then sending the two-dimensional code to the server to finish the fee deduction operation. The sensing module is used for sensing a riding card of a passenger and then completing the fee deduction operation.

In one embodiment, the server is further configured to receive the target face image and the riding information uploaded by the payment acceptance device, match the target face image with the face image in the registered real-name account, deduct fees when the matching is successful, store riding information corresponding to the target face image in association with the corresponding real-name account, match the target face image with the face image in the established credit account when the matching is not successful, correlate the riding information corresponding to the target face image with the credit account if the matching is successful, record the owed amount corresponding to the credit account, and create a credit account, correlate the target face image and the riding information with the credit account and record the owed amount corresponding to the target face image when the matching is not successful.

The face payment is to register real names in advance, so that the face image corresponding to the registered real name account is stored in the server. In order to enable the user which is not registered to experience the face payment function, the user can experience the face payment riding function for free. After receiving the target face image and the riding information uploaded by the payment acceptance equipment, the server firstly matches the target face image with the face image in the registered real-name account, if the matching is successful, fee deduction is correspondingly carried out, and the riding information and the real-name account are stored in an associated mode, namely the riding record of the passenger is stored. If the matching is unsuccessful, the user is not registered with the real name, the user is matched with the face image in the established credit account, if the matching is successful, the riding information corresponding to the target face image is associated with the established credit account, and the arrearage corresponding to the credit account is recorded. If the credit account is not matched, the user is the first experience, a new credit account is created, the target face image and riding information are associated with the new credit account, and the corresponding arrearage amount is recorded. In order to make the user unable to experience free for unlimited times, the amount of the arrears amount can be limited, for example, the user can experience free for three times, if each riding is 2 yuan, then 6 yuan can be used as the arrears amount, when the arrears amount is exceeded, the user is not allowed to continue riding, and the user is prompted to finish real-name registration as soon as possible to recharge.

Referring to fig. 7, in one embodiment, a server includes: a credit management module 602; the credit line management module is used for obtaining the arrearage amount corresponding to the real-name account or the credit account, and adding the face image corresponding to the real-name account or the credit account into the blacklist face library when the arrearage amount is larger than the preset arrearage amount.

In order to establish the riding credit mechanism, the server also comprises a credit line management module, wherein the credit line management module is used for recording the arrearage amount corresponding to each real-name account or credit account. In one embodiment, an arrearage amount of the real-name account is set, and when the arrearage amount of the real-name account is greater than the arrearage amount, the real-name account is added into the blacklist face library. And after the subsequent recharging and repayment, the person can be moved out of the blacklist face library. In another embodiment, a free riding amount (i.e. arrearage amount) of the credit account is set, and when the arrearage amount corresponding to the credit account is greater than the free riding amount, the face image corresponding to the credit account is added into the blacklist face library.

Referring to fig. 7, in one embodiment, a server includes: a face auxiliary recognition module 604; the face auxiliary recognition module is used for determining a face image matched with the target face image according to the historical riding record corresponding to each face image when a plurality of face images similar to the target face image exist in the face library.

Wherein, because a plurality of similar faces can appear, in order to improve the degree of accuracy of face identification, still include in the server: and the face auxiliary recognition module. The face auxiliary recognition module is used for acquiring a corresponding historical riding record corresponding to each face image when recognizing that a plurality of face images similar to the target face image exist, and assisting in determining the face image matched with the target face image according to the historical riding record corresponding to each face image, so that face recognition can be performed more accurately.

Referring to fig. 7, in one embodiment, a server includes: the blacklist management module 606 stores a blacklist face library; the blacklist management module is used for judging whether the received target face image exists in a blackname single face library, and if so, returning the information of refusing riding to the payment acceptance equipment; the blacklist management module is also used for moving the face image out of the blacklist face library and updating the blacklist face library when the arrearage amount corresponding to the face image in the blacklist face library is clear; the server is also used for transmitting the updated black name single face library to the payment acceptance equipment.

The blacklist management module stores a blacklist face library, compares a target face image with face images in the blacklist face library after receiving the target face image sent by the payment acceptance terminal, and returns information of refusing riding to the payment acceptance device if the target face image exists in the blacklist face library so that the payment acceptance terminal displays information such as 'payment failure', 'arrearage', and the like, and is used for prompting passengers to arrearage so as to be convenient for the passengers to recharge in time. And when the passenger is charged later, namely the arrearage amount is clear, the blacklist management module removes the face image from the blacklist face library. In addition, the server can update the blacklist face library in time and then issue the blacklist library to the payment acceptance equipment so that the identification of the blacklist can be completed when the payment acceptance equipment is offline.

Referring to fig. 7, in one embodiment, the server further comprises: a behavior analysis module 608; the behavior analysis module is used for acquiring riding information of each passenger, and the riding information comprises: the riding route, riding station and riding time are analyzed according to riding information to analyze the behavior habit of corresponding passengers, and riding files corresponding to each passenger are established; the behavior analysis module is also used for acquiring historical riding information corresponding to the face images in the blacklist face library, analyzing the historical riding information, determining riding habits corresponding to each face image in the blacklist face library, determining a line blacklist according to the riding habits, and correspondingly transmitting the line blacklist to the payment acceptance equipment corresponding to the line.

Wherein, to build a riding profile with each passenger, the server obtains riding information of each passenger through the behavior analysis module 608, the riding information includes: ride route, ride stop, ride time, ride consumption record, and the like. The behavior habit of the user is analyzed according to the riding information of the user, for example, a route frequently ridden by the user, a time point frequently ridden by the user and the like are analyzed. In addition, based on the behavior analysis module, historical riding information corresponding to face images in the blacklist face library can be analyzed, riding habits corresponding to the face images in the blacklist are analyzed, a corresponding line blacklist is determined according to the riding habits, and the line blacklist is issued to payment acceptance equipment corresponding to the line. Because the data size of the blacklist of the whole network is large, in order to reduce the number of the blacklists in the payment acceptance equipment, a circuit blacklist corresponding to each circuit is established, namely, the blacklist is associated with the circuit by analyzing the frequent riding circuit of a user in the blacklist, so that the blacklist can be issued to the corresponding circuit in a focused way, all the blacklists are not required to be issued to each payment acceptance equipment, the data storage amount in the payment acceptance equipment is greatly reduced, and the illegal riding behavior of passengers can be more effectively controlled.

As shown in fig. 8, in one embodiment, the riding payment system further includes: a terminal 700; the terminal is used for receiving a registered face image and a corresponding deduction account of a user for real-name registration, and sending the registered face image and the deduction account to the server; the server is also used for distributing unique real-name accounts to the corresponding users according to the registered face images and associating the real-name accounts, the registered face images and the deduction accounts.

The terminal is a user terminal, and real-name registration is performed through an application program (APP) by installing a corresponding APP in the terminal. When registering real names, the registered face images and the deduction accounts are required to be sent to the server through the terminal, the server distributes unique real name accounts according to the registered face images, and the real name accounts, the registered face images and the deduction accounts are associated. And when the target face image consistent with the registered face image is recognized later, carrying out riding fee deduction directly from the deduction account.

Referring to fig. 9, in one embodiment, a terminal includes: a query module 702; the inquiry module is used for sending an inquiry request of the riding records or the consumption records to the server; the server is also used for sending the corresponding riding records or consumption records to the terminal according to the inquiry request.

The terminal comprises a query module, a user can send a query request of the riding records or the consumption records to the server through the query module, and then the server sends the corresponding riding records or the consumption records to the terminal for display according to the corresponding query request.

Referring to fig. 9, in one embodiment, the terminal further includes: complaint module 704; the complaint module is used for complaining the records with objections and sending a complaint request to the server; the server is also used for returning the real-time processing flow of the complaints to the terminal.

When the deduction abnormal condition occurs, the user can complain about the records with objections through a complaint module 704 in the terminal, and send a complaint request to the server, and can check the complaint processing flow and processing nodes in real time. Accordingly, the server returns the real-time processing flow of the complaint to the terminal in response to the complaint inquiry request of the terminal.

As shown in fig. 10, in one embodiment, the ride payment system includes: terminal 1002, payment acceptance device 1004, and server 1006. The terminal 1002 includes a real-name account registration module, an abnormal consumption complaint module, a riding fee and record inquiry module, and a recharging and blacklist processing module. The payment acceptance device 1004 includes: the device comprises a face recognition module, a face recognition triggering module, an induction module, a code scanning module, a communication module, a blacklist module, an interaction module and a positioning module. The server 1006 includes: the system comprises an account management module, a face matching module, a behavior analysis module, a credit management module, an auxiliary face recognition module, a fee payment and settlement module, an abnormal consumption complaint module, a recharging and consumption record inquiry module and a blacklist management module.

The real-name account registration module in the terminal 1002 is used for providing a channel for real-name registration of a user, the abnormal consumption complaint module is used for providing a channel for complaining about the consumption of objections to the user, the riding expense and record inquiry module is used for providing a channel for inquiring about the consumption condition to the user, and the recharging and blacklist processing module is used for providing a channel for recharging and eliminating a blacklist to the user. The communication module in the payment acceptance device 1004 is used for communicating with a server, and the positioning module is used for positioning the current device, so that the positioning module can be used for positioning the station information of the passenger getting on the vehicle, and the positioning mode can be GPS positioning, and of course, other positioning modes can also be adopted. The fee payment and settlement module in the server 1006 is used for calculating the bus fee and carrying out corresponding fee deduction, and the abnormal consumption complaint module is used for recording complaints sent by the terminal. The recharging and consuming record inquiring module is used for providing inquiring records for the inquiring module in the terminal.

As shown in fig. 11, in one embodiment, a flow diagram of real-name account registration is presented. Firstly, whether real-name registration is carried out is judged through a terminal login APP, if not, a real-name registration page is entered, residence address, identity card information and registration face images are acquired through the real-name registration page, then identity information is verified, if verification and identification are carried out, registration failure is returned, if verification is successful, a binding payment account is indicated, after the binding of the payment account is completed, the registration face images are uploaded to a server, the server detects whether a credit account corresponding to the registration face images exists, if so, the credit account is updated to the real-name registration account, real-name registration is completed, and if not, a new real-name account is directly registered.

As shown in FIG. 12, in one embodiment, a real-name account business transaction flow diagram. Firstly, the terminal detects whether an abnormal consumption record exists, if so, the terminal enters an abnormal consumption complaint flow, if not, the terminal detects whether a real-name account is arreared, if so, the terminal enters a recharging payment flow, if not, the terminal detects whether the real-name account is blacklisted, if so, the terminal enters a blacklist processing flow for processing, and if not, the terminal does not process the real-name account.

As shown in fig. 13, in one embodiment, is a schematic diagram of an abnormal consumption flow. Firstly, passengers complain about abnormal consumption records through APP in the terminal, the complaint records are manually audited through a complaint platform, if the audits are passed, the fees are refunded, the consumption records are updated, and meanwhile, audit results can be pushed through short messages, weChat and other modes. In addition, the reason of the abnormality is analyzed by the face auxiliary recognition module, and whether the abnormality occurs due to the existence of the similar face is judged. If the auditing is not passed, the result and the reason are pushed to the user in a short message and WeChat mode.

As shown in fig. 14, in one embodiment, a blacklist service process flow diagram is provided. When the passenger inquires the arrears through the APP, the charging and paying can be carried out, after the server receives the success of the charging and paying, the user is deleted from the blacklist, the blacklist face library is updated, and the updated blacklist face library is issued to the payment acceptance terminal.

As shown in fig. 15, in one embodiment, a process flow diagram for face payment is provided. The face recognition triggering module is used for triggering and starting the face recognition module, then the face recognition module is used for scanning to obtain a target face image, then the target face image is compared with a local blackname single face library, whether the target face image is in the local blacklist face library is judged, if yes, the payment acceptance terminal returns to disable passing, then the passenger is prompted, if not, the face brushing is prompted to be successful, then the payment acceptance terminal uploads the target face image and riding information to the server when the wireless network is effective, and the server carries out corresponding fee deduction processing.

As shown in fig. 16, the process flow of the cloud big data platform (i.e. server) is shown. The cloud big data platform calculates the riding cost of passengers by calling a settlement interface, queries possible associated accounts through face information matching, obtains personal travel files through big data analysis, determines the true personal identities of a plurality of similar face information, and then searches whether real-name accounts associated with the face information (namely target face images) are found.

If the payment is found, real-name payment is carried out, whether the payment is successful is judged, if the payment is successful, the payment successful record is refreshed and pushed to a corresponding APP (terminal), if the payment is failed, the real-name account payment failure record is refreshed, whether the consumption cost exceeds a consumption threshold is checked, if not, payment failure and prompt recharging information are pushed to the APP, if yes, the real-name account is added to a blacklist, the information added to the blacklist is pushed to the APP, and then the blacklist is periodically synchronized to a payment terminal of a common bus line and a region through a big data platform.

If the personal credit account is not found, searching whether the face information has the associated personal credit account (namely the credit account), if not, establishing the personal credit account, recording the bus taking line information and the bus taking expense, and establishing a threshold of credit consumption. If the consumption cost exceeds the consumption threshold, refreshing the consumption record of the personal credit account, if the consumption cost exceeds the consumption threshold, bringing the personal credit account into a blacklist, analyzing the common riding places, circuits and areas of the user through a big data analysis platform, and preferentially synchronizing the blacklist to the common payment terminals (namely payment acceptance equipment) of the riding circuits and areas through the big data platform.

Fig. 17 is a diagram showing an internal configuration of the payment acceptance apparatus in one embodiment. As shown in fig. 17, the computer device includes a processor, a memory, a camera, and a network interface connected by a system bus. The memory includes a nonvolatile storage medium and an internal memory. The non-volatile storage medium of the computer device stores an operating system and may also store a computer program that, when executed by a processor, causes the processor to implement a ride-on payment method. The internal memory may also have stored therein a computer program which, when executed by the processor, causes the processor to perform a method of payment by bus. The camera is used for collecting face images of passengers, and the network interface is used for communicating with the external connection. It will be appreciated by those skilled in the art that the structure shown in FIG. 17 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.

Fig. 18 shows an internal structural diagram of a server in one embodiment. As shown in fig. 18, the computer device includes a processor, a memory, and a network interface connected by a system bus. The memory includes a nonvolatile storage medium and an internal memory. The non-volatile storage medium of the computer device stores an operating system and may also store a computer program that, when executed by a processor, causes the processor to implement a ride-on payment method. The internal memory may also have stored therein a computer program which, when executed by the processor, causes the processor to perform a method of payment by bus. The network interface is used for communicating with the external connection. It will be appreciated by those skilled in the art that the structure shown in FIG. 18 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.

A payment acceptance device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the steps of: responding to the triggering operation, and starting a face recognition function; the face of the passenger is scanned and identified through the face identification function, and a target face image is obtained; and interacting with a server according to the target face image and the riding information to finish corresponding fee deduction operation.

A server comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the steps of: receiving a target face image and riding information sent by a payment acceptance device, wherein the target face image is obtained by scanning the face of a passenger by the payment acceptance device in response to triggering operation to start a face recognition function; and matching the target face image with the face image in the registered real-name account, and when the matching is successful, deducting fees according to the riding information and returning corresponding deduction information.

The above-described riding payment method, riding payment system, payment acceptance apparatus, and server belong to one general inventive concept, and the contents in the embodiments of the riding payment method, riding payment system, payment acceptance apparatus, and server are mutually applicable.

Those skilled in the art will appreciate that all or part of the processes in the methods of the above embodiments may be implemented by a computer program for instructing relevant hardware, where the program may be stored in a non-volatile computer readable storage medium, and where the program, when executed, may include processes in the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.

The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.

The foregoing examples illustrate only a few embodiments of the application and are described in detail herein without thereby limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of protection of the present application is to be determined by the appended claims.

Claims

1. A ride payment method, the method comprising:

matching the target face image with the face image in the registered real-name account, and when the matching is successful, deducting fees according to the riding information and returning corresponding deduction information;

Wherein the method further comprises:

when the real-name account is not matched, matching the target face image with the face image in the established credit account;

when the established credit account is matched, the riding information corresponding to the target face image is associated with the credit account, and the arrearage amount corresponding to the credit account is recorded;

the matching the target face image with the face image in the registered real-name account comprises the following steps:

when a plurality of face images similar to the target face image exist in the real-name account or the credit account, acquiring a historical riding record corresponding to the real-name account or the credit account;

determining a real-name account or a credit account matched with the target face image according to the historical riding record corresponding to the real-name account or the credit account;

the determining the real-name account or the credit account matched with the target face image according to the historical bus record corresponding to the real-name account or the credit account comprises the following steps:

acquiring current riding information corresponding to the target face image, and extracting riding parameters associated with the current riding information from historical riding records corresponding to each real-name account or credit account according to the current riding information;

Determining a score value corresponding to each real-name account or credit account according to the riding parameters and a preset scoring rule;

determining a real-name account or a credit account matched with the target face image according to the score value;

the riding parameters at least comprise riding times and historical riding time, wherein the riding times and the score value are positively correlated, and the more recent the time corresponding to the riding time in the current riding information is, the higher the score value of the historical riding time is;

the determining, according to the score value, a real-name account or a credit account matched with the target face image includes:

and taking the real-name account or the credit account with the highest score as the account matched with the target face image.

2. The method according to claim 1, wherein the method further comprises:

and when the established credit account is not matched, creating a new credit account, associating the target face image and the riding information with the new credit account, and recording the arrearage amount corresponding to the new credit account.

3. The method according to claim 1, wherein the method further comprises:

Comparing the target face image with face images in a blacklist face library;

and if the target face image exists in the black name single face library, returning the bus refusal information to the payment acceptance equipment.

4. The method according to claim 1, wherein the method further comprises:

obtaining riding information associated with a real name account or a credit account, wherein the riding information comprises the following steps: a bus route and a bus station;

and analyzing the passenger behavior habits of the real-name accounts or the credit accounts according to the riding information, and establishing riding files corresponding to each real-name account or each credit account.

5. The method according to claim 1, wherein the method further comprises:

comparing the target face image with face images in a white list face library;

and when the target face image exists in the white name single face library, returning the riding permission information to the payment acceptance device.

6. The method according to claim 1, wherein the method further comprises:

obtaining a historical bus taking record corresponding to the real name account or the credit account, wherein the historical bus taking record comprises the following steps: bus route information and bus times information;

Calculating a credit score value corresponding to each real-name account or credit account according to the historical bus taking record;

determining a line white name single face library corresponding to each riding line according to the credit score value and the riding line information;

and synchronizing the line white name single face library to the payment acceptance equipment corresponding to the corresponding line.

7. The method according to claim 1, wherein the method further comprises:

acquiring a history riding record corresponding to the real-name account, wherein the history riding record comprises the following steps: the riding route information and riding frequency of riding each route;

adding real-name accounts with the riding frequency larger than a preset value in each line into a line white-name single face library corresponding to the corresponding line;

8. A ride payment method, the method comprising:

according to the target face image and riding information, interacting with a server to complete corresponding fee deduction operation;

The server is used for receiving a target face image and riding information sent by the payment acceptance device, wherein the target face image is obtained by the payment acceptance device starting a face recognition function in response to triggering operation and scanning the face of a passenger;

matching the target face image with the face image in the registered real-name account, and when the matching is successful, deducting fees according to the riding information and returning corresponding deduction information; wherein, the server is further used for: when the real-name account is not matched, matching the target face image with the face image in the established credit account;

the matching of the target face image with face images in registered real-name accounts comprises the steps of acquiring a historical riding record corresponding to the real-name account or the credit account when a plurality of face images similar to the target face image exist in the real-name account or the credit account;

the determining the real-name account or the credit account matched with the target face image according to the historical bus record corresponding to the real-name account or the credit account comprises the following steps: acquiring current riding information corresponding to the target face image, and extracting riding parameters associated with the current riding information from historical riding records corresponding to each real-name account or credit account according to the current riding information;

the determining, according to the score value, a real-name account or a credit account matched with the target face image includes: and taking the real-name account or the credit account with the highest score as the account matched with the target face image.

9. The method according to claim 8, further comprising, after the scanning and recognizing the face of the passenger by the face recognition function, obtaining a target face image:

comparing the target face image with face images in a blacklist face library to obtain a comparison result;

and outputting corresponding prompt information according to the comparison result.

10. The method of claim 9, wherein the blackname single face library is a line blacklist face library associated with a line obtained from a server.

11. The method of claim 9, wherein outputting the corresponding prompt message according to the comparison result comprises:

when the target face image is not in the black name single face library, judging whether fee deduction information returned by the server is received within preset time;

if yes, corresponding prompt information is returned according to the fee deduction information;

if not, directly outputting preset prompt information.

12. The method of claim 9, wherein the interacting with the server according to the target face image and the riding information to complete the corresponding deduction operation comprises:

When the target face image is not in the blackname single face library, the target face image and riding information are sent to a server;

and receiving fee deduction information returned by the server according to the target face image and the riding information.

13. The method of claim 8, further comprising, prior to the step of interacting with a server to complete the corresponding deduction operation based on the target face image and the ride information:

comparing the target face image with face images in a white list face library to obtain a comparison result;

when the target face image is in the white name single face library, pre-deducting fees are carried out, and prompt information of successful face brushing is output;

the corresponding fee deduction operation is completed by interaction with a server according to the target face image and riding information, and the fee deduction operation comprises the following steps:

and sending the target face image and the pre-deduction to the server, so that the server finishes deduction in a deduction account corresponding to the target face image according to the pre-deduction.

14. A ride payment system, the system comprising:

payment acceptance equipment and a server;

the server is used for completing corresponding deduction operation according to the received target face image and riding information;

the server is further configured to receive a target face image and riding information uploaded by the payment acceptance device, match the target face image with a face image in a registered real-name account, deduct fees when the matching is successful, store riding information corresponding to the target face image in association with a corresponding real-name account, match the target face image with a face image in an established credit account when the matching is not successful, correlate riding information corresponding to the target face image with the credit account, record a owed amount corresponding to the credit account, and create a credit account when the matching is not successful, correlate the target face image, the riding information with the credit account, and record an owed amount corresponding to the target face image, the server includes: a face auxiliary recognition module; the face auxiliary recognition module is used for determining a face image matched with the target face image according to a historical riding record corresponding to each face image when a plurality of face images similar to the target face image exist in the face library; the determining the real name account or the credit account matched with the target face image according to the historical bus record corresponding to the real name account or the credit account comprises the following steps: acquiring current riding information corresponding to the target face image, and extracting riding parameters associated with the current riding information from historical riding records corresponding to each real-name account or credit account according to the current riding information; determining a score value corresponding to each real-name account or credit account according to the riding parameters and a preset scoring rule; determining a real-name account or a credit account matched with the target face image according to the score value; the riding parameters at least comprise riding times and historical riding time, wherein the riding times and the score value are positively correlated, and the more recent the time corresponding to the riding time in the current riding information is, the higher the score value of the historical riding time is; the determining, according to the score value, a real-name account or a credit account matched with the target face image includes: and taking the real-name account or the credit account with the highest score as the account matched with the target face image.

15. The system of claim 14, wherein the payment acceptance device further comprises: the blacklist module and the processing module;

the blacklist module is used for storing a blacklist face library;

the processing module is used for obtaining a target face image obtained by scanning by the face recognition module, comparing the target face image with face images in a blacklist face library to obtain a comparison result, and determining whether face brushing is successful or not according to the comparison result.

16. The system of claim 14, wherein the server comprises: the blacklist management module is used for storing a blacklist face library;

the blacklist management module is used for judging whether the received target face image exists in the blackname single face library, and if so, returning the information of refusing riding to the payment acceptance equipment;

the blacklist management module is further used for moving the face image out of the blacklist face library and updating the blacklist single face library when the arrearage amount corresponding to the face image in the blacklist face library is clear;

the server is further configured to issue the updated blacklist face library to the payment acceptance device.

17. The system of claim 15, wherein the server further comprises: a behavior analysis module;

the behavior analysis module is used for acquiring riding information of each passenger, and the riding information comprises: the riding route and riding station are used for analyzing the behavior habits of corresponding passengers according to the riding information, and riding files corresponding to each passenger are established;

the behavior analysis module is further used for acquiring historical riding information corresponding to face images in the blacklist face library, analyzing the historical riding information, determining riding habits corresponding to each face image in the blacklist face library, determining a line blacklist according to the riding habits, and correspondingly transmitting the line blacklist to payment acceptance equipment corresponding to the line.

18. A payment acceptance device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the steps of the method of any of claims 8 to 13.

19. A server comprising a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of the method of any of claims 1 to 7.