WO2020019456A1

WO2020019456A1 - User instruction matching method and device, computer device and storage medium

Info

Publication number: WO2020019456A1
Application number: PCT/CN2018/106428
Authority: WO
Inventors: 朱文和
Original assignee: 平安科技（深圳）有限公司
Priority date: 2018-07-27
Filing date: 2018-09-19
Publication date: 2020-01-30
Also published as: CN108985251A; CN108985251B

Abstract

A user instruction matching method and device, a computer device and a storage medium, the method comprising: first, acquiring target instruction information of a participant (S10); if the target instruction information of all participants is not obtained within an effective period of time, allocating random instruction information to participants who do not obtain the target instruction information (S30); next, acquiring a gesture picture of a decision maker, and recognizing the gesture picture of the decision maker so as to obtain decision instruction information of the decision maker (S40); and matching the target instruction information or the random instruction information of each participant with the decision instruction information of the decision maker by means of a mapping relation table, so as to obtain an instruction matching result of each participant (S50). Random instruction information is allocated to participants who do not obtain the target instruction information, which may ensure the fairness of the data and avoids a waiting stage due to incomplete instruction acquisition, thereby improving the efficiency of user instruction matching.

Description

User instruction matching method, device, computer equipment and storage medium

This application is based on a Chinese invention patent application filed on July 27, 2018 with application number 201810842495.0 and entitled "User instruction matching method, device, computer equipment and storage medium", and claims its priority.

Technical field

The present application relates to the field of data processing, and in particular, to a user instruction matching method, device, computer device, and storage medium.

Background technique

The traditional lottery method is manually drawn by the lottery staff. With the development of the society, the lottery form has begun to be networked and automated. Generally, the lottery information of each user is collected to the network database through instructions. Send qualified instructions to the lottery system, for example, only the first one hundred of the lottery information will be selected according to the sending time. Further, through the computer lottery system, a plurality of winners are randomly selected from the first hundred pieces of lottery information.

Because the lottery process needs to meet transparency and fairness, if the network database receives more instructions, it will continue to send and receive instructions, and frequent instruction sending and receiving will cause the stability of the system to deteriorate, or the server In the process of communicating with the mobile terminal, the instructions may be lost due to the instability of the network. However, if the instruction is in the waiting stage due to incomplete instructions, it will make the entire instruction match take too much time and reduce the efficiency of the entire instruction match.

Summary of the Invention

The embodiments of the present application provide a user instruction matching method, device, computer equipment, and storage medium to solve the problem of low user instruction matching efficiency.

A user instruction matching method includes:

Obtain target instruction information of participants;

Judging whether target instruction information of all the participants is obtained within a valid time;

If the target instruction information of all the participants is not obtained within the valid time, assigning random instruction information to the participants who have not obtained the target instruction information;

Acquiring a gesture picture of a decision maker, identifying the gesture picture of the decision maker, and obtaining decision instruction information of the decision maker;

The target instruction information or the random instruction information of each participant is matched with the decision instruction information of the decision maker through a mapping relationship table to obtain the instruction matching result of each participant.

A user instruction matching device includes:

Participant information acquisition module, which is used to acquire target instruction information of participants;

A target instruction information judging module, configured to determine whether the target instruction information of all the participants is obtained within a valid time;

A random instruction information allocation module, configured to allocate random instruction information to participants who have not obtained the target instruction information if the target instruction information of all the participants has not been obtained within a valid time;

A decision instruction information acquisition module, configured to obtain a gesture picture of a decision maker, and identify the gesture picture of the decision maker, to obtain the decision instruction information of the decision maker;

The instruction matching result acquisition module is configured to match the target instruction information or the random instruction information of each participant with the decision instruction information of the decision maker through a mapping relationship table to obtain the information of each participant. Instruction match result.

A computer device includes a memory, a processor, and computer-readable instructions stored in the memory and executable on the processor. The processor performs the following steps:

Obtain target instruction information of participants;

Match the target instruction information or the random instruction information of each participant with the decision instruction information of the decision maker through a mapping relationship table to obtain the instruction matching result of each participant.

One or more non-volatile readable storage media storing computer-readable instructions, which when executed by one or more processors, cause the one or more processors to perform the following steps:

Obtain target instruction information of participants;

Details of one or more embodiments of the present application are set forth in the accompanying drawings and description below, and other features and advantages of the present application will become apparent from the description, the drawings, and the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to explain the technical solution of the embodiments of the present application more clearly, the drawings used in the description of the embodiments of the application will be briefly introduced below. Obviously, the drawings in the following description are just some embodiments of the application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without paying creative labor.

FIG. 1 is a schematic diagram of an application environment of a user instruction matching method according to an embodiment of the present application; FIG.

2 is an example diagram of a user instruction matching method according to an embodiment of the present application;

FIG. 3 is another example diagram of a user instruction matching method according to an embodiment of the present application; FIG.

FIG. 4 is another example diagram of a user instruction matching method in an embodiment of the present application; FIG.

FIG. 5 is another example diagram of a user instruction matching method in an embodiment of the present application; FIG.

FIG. 6 is another example diagram of a user instruction matching method according to an embodiment of the present application; FIG.

FIG. 7 is another example diagram of a user instruction matching method according to an embodiment of the present application; FIG.

8 is a schematic block diagram of a user instruction matching device according to an embodiment of the present application;

9 is another schematic block diagram of a user instruction matching device according to an embodiment of the present application;

FIG. 10 is a schematic diagram of a computer device according to an embodiment of the present application.

detailed description

In the following, the technical solutions in the embodiments of the present application will be clearly and completely described with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, but not all of them. Based on the embodiments in the present application, all other embodiments obtained by a person of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

The user instruction matching method provided in this application can be applied in the application environment shown in FIG. 1, in which a client (computer device) and an image acquisition terminal communicate with a server through a network, respectively. The client sends the target instruction information of the participant to the server. After the server obtains the target instruction information of the participant, the server controls the image acquisition terminal to obtain the gesture picture of the decision maker, and processes the instruction matching result of the participant. The client (computer device) may be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices. The image acquisition terminal may be, but is not limited to, a video camera, a camera, a scanner, or other equipment with a photographing function. The server can be implemented by an independent server or a server cluster composed of multiple servers.

In an embodiment, as shown in FIG. 2, a method for matching user instructions is provided. The method is applied to the server in FIG. 1 as an example, and includes the following steps:

S10: Obtain target instruction information of the participant.

Participants refer to users who need to perform instruction matching. The target instruction information refers to the generation of instruction information based on the instruction input by the participant. Preferably, the target instruction information is gesture instruction information, wherein the gesture instruction information is instruction information representing different gesture actions, such as: scissors, rock, or cloth, or gesture actions representing different numbers, such as: 1, 2, 3, 4 or 5.

In a specific embodiment, the client establishes a connection with the server. After the connection is successful, the participant inputs target instruction information through the client, and the client then sends the target instruction information entered by the participant through the client to the server, and the server obtains To get the target instruction information of the participant.

S20: Determine whether the target instruction information of all participants is obtained within the valid time.

The effective time refers to a time limit for receiving the target instruction information, and is a preset time, which can be adjusted according to actual needs, such as 1 minute, 2 minutes, or 5 minutes. By setting a valid time to limit the time limit for receiving target instruction information, the efficiency of the entire instruction matching can be improved. The starting time point of the valid time can be set to the time point when the server obtains the target instruction information of the first participant, or the time point when a specific trigger instruction is received as the starting time point of the valid time.

In this embodiment, the server will obtain the personal information of all participants in advance, and the personal information may include identity information, participant names, and contact information. The identity information may be the employee number, ID card number, mobile phone number of the participant, or other unique information that can identify the participant. Understandably, the identity information may be one item or at least two items. For example, the identity information is an identification number, or the identity information is an identification number and a mobile phone number. The contact information refers to information that can communicate with the participants. Optionally, the contact information may be a mobile phone number, a WeChat signal, or an IP address. Specifically, the personal information of all participants can be generated into a participant information data table, and a target instruction information field is added to the participant information data table. After the server obtains the target instruction information of the participants, it The participant's target instruction information is stored in the corresponding position in the participant information data table. In this way, by querying and counting the participant information data table, it can be determined whether the target instruction information of all participants is obtained within the valid time.

Specifically, when generating the participant information data table, the target instruction information of each participant is preset to an initial value, and the initial value may be a number, a letter, a symbol, or other computer-recognizable characters. The initial values of all participants are set to the same, such as 0, none, or left blank. After obtaining the target instruction information of each participant, the server will update the corresponding position of the participant information data table.

When the valid time arrives, the number of initial values in the target instruction information field in the participant information data table can be counted. If the number of initial values is 0, it means that the target instruction information of all participants has been obtained. If the number of initial values is not 0, it means that target instruction information of all participants has not been obtained.

S30: If the target instruction information of all participants is not obtained within the valid time, the participants who have not obtained the target instruction information are allocated random instruction information.

When the valid time arrives, there may be a delay or omission of information due to network delay or system instability. If the target instruction information of a participant is not obtained, random instruction information is allocated to the participant who has not obtained the target instruction information. The random instruction information refers to instruction information generated by a random function. Exemplarily, if the target instruction information is three types of scissors, rock, and cloth, the server can calibrate the three types of target instruction information with 1, 2, and 3 respectively, and then fail to obtain the target instruction for each of the valid time. The participants of the information use the random function rand () to randomly generate integers of 1-3 to obtain the random instruction information of the participants who did not obtain the target instruction information.

S40: Obtain a gesture picture of the decision maker, and recognize the gesture picture of the decision maker, and obtain decision information of the decision maker.

Among them, a decision maker refers to a user who provides a gesture picture to assist in matching the participants' instructions. After the effective time is reached, the gesture picture of the decision maker begins to be acquired. Specifically, the gesture picture of the decision maker can be collected through an image acquisition terminal, which can be a video camera, a camera, a scanner, or another device with a photographing function .

After the image acquisition terminal obtains the instruction for acquiring the current gesture from the server, the image acquisition terminal acquires the image of the decision maker's location, and then sends the image of the decision maker's location to the server. After the server obtains the image of the decision-maker's location, it can obtain a gesture-picture of the decision-maker by taking a screenshot. After the server obtains the gesture picture of the decision maker, it detects the gesture picture, extracts the gesture area from the gesture picture of the decision maker, obtains the gesture area picture, and enters the gesture area picture into a pre-trained gesture picture recognition model. Identify and output decision information of decision makers. Understandably, the decision instruction information is also instruction information representing different gesture actions, and the decision instruction information corresponds to the target instruction information. If the target instruction information represents scissors, stone, or cloth, the decision instruction information also represents scissors, Stone or cloth.

S50: Match the target instruction information or random instruction information of each participant with the decision instruction information of the decision maker through a mapping relationship table to obtain the instruction matching result of each participant.

The mapping relationship table is a preset table, and the mapping relationship table can be matched with the decision instruction information of the decision maker according to the participant's target instruction information or random instruction information, and the corresponding relationship can be found in the mapping relationship table. Instruction match result.

In this step, by matching the target instruction information or random instruction information of each participant with the decision instruction information of the decision maker through a mapping relationship table, the instruction matching result of each participant can be obtained.

In this embodiment, the target instruction information of the participants is obtained first. If the target instruction information of all participants is not obtained within the valid time, the participants who have not obtained the target instruction information are assigned random instruction information, which can avoid subsequent follow-up. Participants who have not obtained the target instruction information cannot obtain a matching instruction result. Then, the gesture picture of the decision maker is obtained, and the gesture picture of the decision maker is identified, and the decision instruction information of the decision maker is obtained. The target instruction information or random instruction information of each participant is matched with the decision instruction information of the decision maker through a mapping relationship table to obtain the instruction matching result of each participant. The user instruction matching method judges whether the target instruction information of all participants is obtained within a valid time, and assigns random instruction information to the participants who have not obtained the target instruction information to ensure that each participant can obtain an instruction matching result. Moreover, assigning random instruction information to participants who have not obtained the target instruction information can also ensure the fairness of the data, avoiding being in the waiting stage due to incomplete instructions, and improving the efficiency of user instruction matching.

In an embodiment, as shown in FIG. 3, step S10, obtaining target instruction information of a participant, specifically includes the following steps:

S11: Send a selection instruction to the client, and receive the identity information and initial instruction information of the participant returned by the client.

The initial instruction information refers to instruction information input by a participant through a client. After the server connects with the client, the server sends a selection instruction link to the client. The selection instruction link may be, but is not limited to, a lottery page, two-dimensional code, or public account. After the client obtains the selection instruction link, the participant inputs identity information and initial instruction information through the client. After the client obtains the identity information and initial instruction information input by the participant, the client sends the identity information and initial instruction information of the participant to the server.

Preferably, this step further includes obtaining the name of the participant, and after obtaining the name of the participant, associating the name of the participant with the identity information, so that the participant's name can be added later when the information of the participant is required. One display item to better identify participants.

S12: Verify the identity information. If the identity information verification is successful, determine the initial instruction information as the target instruction information.

After obtaining the identity information of the participant, the server verifies the identity information of the participant. Specifically, after obtaining the identity information of the participants, the server sends a verification request to the client, and the participants need to verify their identity information. Specifically, the authentication can be performed by entering a verification password corresponding to the identity information. After receiving the verification password, the server matches the verification password with a pre-stored login password in the database. Password is the same), the identity information verification is successful. If the matching fails (that is, the authentication password and the login password are different), the authentication of the identity information fails.

Further, if the authentication of the identity information is passed, the server will send a token to the corresponding client. The valid time of the token can be set uniformly in advance, for example, setting the valid time and the valid time to be the same, or customize Set to another value. The token is a string generated by the server. As a token requested by the client, the server generates a token and returns the token to the client. It is necessary to bring this token to request data, and there is no need to verify identity information again, which improves the efficiency of subsequent user instruction matching.

In this embodiment, when the target instruction information of the participant is obtained, the identity information of the participant is verified, and after the identity information verification is successful, the initial instruction information is determined as the target instruction information, which ensures that the user instruction matches safety.

In an embodiment, as shown in FIG. 4, after the step of obtaining target instruction information of the participants and before the step of determining whether the target instruction information of all participants is obtained within a valid time, the user instruction matching method It also includes the following steps:

S21: Determine whether the target instruction information of all participants is obtained within a preset time, wherein the preset time is less than the valid time.

The preset time is a time limit set according to the valid time, and the preset time is less than the valid time. For example, if the valid time is 5 minutes, the preset time can be set to 3 minutes or 4 minutes. By setting a preset time, it is judged in advance whether the target instruction information of all participants is obtained before the effective time is reached. The specific judgment method is similar to step S20, and is not repeated here.

S22: If target instruction information of all participants is not obtained within a preset time, contact information of participants who have not obtained target instruction information is obtained.

If target instruction information of all participants is not obtained within a preset time, contact information of participants who have not obtained target instruction information is obtained. Specifically, the contact information can also be obtained in the participant information data table. When the participant information data table is generated, the participant information data table also includes the contact information of the participant.

S23: Send prompt information according to the contact information.

After the contact information is obtained, a prompt message is sent according to the contact information. The prompt information is used to remind participants to send target instruction information as soon as possible. Specifically, the prompt information may further include a reason for failure in obtaining the target instruction information, for example, the target instruction information is not received, the target instruction information is invalid, or the identity information verification fails. In this way, it is convenient for participants to make targeted adjustments after receiving the prompt information, thereby improving acquisition efficiency.

Optionally, the server communicates with the client through the TCP / IP protocol or the UDP protocol, and sends a prompt message to the participant who has not obtained the target instruction information through a specific data packet. The meaning of the specific data packet is in each data packet. There will be a specific field indicating the purpose of the packet (such as sending interactive content, connection requests, warnings, or reminders). You only need to set this field to prompt information. When the client receives the data packet with the prompt information After that, you can perform corresponding operations according to the prompt information.

In this embodiment, by setting a preset time that is shorter than the valid time, it is determined in advance whether the target instruction information of all participants is obtained before the valid time reaches, and it is a participant who has not obtained the target instruction information. Send prompt information to better ensure the efficiency of target instruction information acquisition.

In an embodiment, as shown in FIG. 5, step S40 is to obtain a gesture picture of a decision maker, identify the gesture picture of a decision maker, and obtain decision information of the decision maker, which specifically includes the following steps:

S41: Acquire a gesture picture of a decision maker, and capture a gesture area picture from the gesture picture.

The gesture picture of the decision maker is acquired. Since the gesture picture of the decision maker is obtained, the gesture picture may have a relatively large area, which is not conducive to subsequent recognition processing. Therefore, the gesture area needs to be extracted from the gesture picture to obtain a gesture area picture. Specifically, an edge detection algorithm can be used to obtain the edge image of the gesture picture, and then each knuckle point and two wrist points in the gesture picture are found according to the curvature of the edge image. Optionally, the edge detection algorithm may use a differential edge detection algorithm, a Sobel edge detection algorithm, or a Reborts edge detection algorithm. After finding each knuckle point and two wrist points in the gesture picture, a gesture region is obtained according to each knuckle point and two wrist points, and finally a gesture region picture is obtained according to the gesture region. Specifically, a fixed area may be determined according to each knuckle point and two wrist points. The fixed area may be a rectangle or a circle, and the fixed area includes a gesture area. Optionally, the fixed area is set to a circle, and the center of the circle is determined according to the two wrist points and one of the knuckle points, and then multiplied by a certain distance according to the distance between the wrist point and one of the knuckle points. The radius of the circle is determined by the ratio of the ratio. The ratio can be set according to actual needs, and is not specifically limited here. After obtaining the gesture area, you can use the imageclipper tool to capture the gesture area picture. The imageclipper tool can quickly capture the gesture area picture from the gesture picture.

S42: The gesture area picture is input into a gesture picture recognition model for recognition, and decision instruction information of a decision maker is obtained.

By inputting a gesture area picture into a gesture picture recognition model, the output of the gesture recognition model can be used to obtain decision instruction information corresponding to the gesture zone picture. Among them, the gesture picture recognition model is a pre-trained recognition model. Through the gesture picture recognition model, the types of pictures in the gesture area can be quickly identified, and the decision instruction information of the decision maker is output to facilitate subsequent matching.

In this embodiment, by capturing a gesture area picture including a gesture area, and then inputting the gesture area picture into the gesture picture recognition model, the current gesture type is identified, and the decision instruction information of the decision maker is obtained accordingly, thereby improving the accuracy of gesture recognition Sex and efficiency.

In an embodiment, as shown in FIG. 6, before the step of inputting the gesture area picture into the gesture picture recognition model for recognition, the user instruction matching method further includes the following steps:

S421: Obtain original pictures, classify and mark each original picture to form a gesture training picture.

Among them, the original picture is a pre-collected picture containing different gestures. Pictures of different gestures can be obtained through the camera, or can be obtained through the existing data set on the network. By obtaining a large number of original pictures of different gestures, and classifying each original picture, for example: "stone", "scissors" or "cloth". After classifying and labeling the original images, each original image contains corresponding labeling data, and the original image containing the labeling data is used as a gesture training image.

S422: Use a gesture training picture to train the convolutional neural network model to obtain a gesture picture recognition model.

By inputting a gesture training picture into a convolutional neural network model for training, a gesture picture recognition model can be obtained. Among them, the Convolutional Neural Network (CNN) model is a feed-forward neural network. Its artificial neurons can respond to a part of the surrounding cells in the coverage area, and are often applied to the processing of large images. Convolutional neural networks usually include at least two non-linearly trainable convolutional layers, at least two non-linear pooling layers, and at least one fully connected layer, that is, including at least five hidden layers, in addition to an input layer and an output Floor. The gesture picture recognition model obtained by training the convolutional neural network model through the gesture training pictures can more accurately classify the gesture training pictures.

By obtaining the original pictures of different gestures and classifying the original pictures of each gesture, the original training pictures of the current gesture are obtained, and then the convolutional neural network model is trained by using the gesture training pictures to obtain a gesture picture recognition model. The current gesture picture is input to the gesture picture recognition model for recognition, and the current gesture type corresponding to the current gesture picture is obtained.

In this embodiment, by acquiring original pictures, each original picture is classified and labeled to form a gesture training picture. Then, the convolutional neural network model is trained with gesture training pictures to obtain a gesture picture recognition model, which better guarantees the recognition efficiency and accuracy of subsequent gesture area pictures.

In one embodiment, as shown in FIG. 7, step S50: match the target instruction information or random instruction information of each participant with the decision instruction information of the decision maker through a mapping relationship table to obtain the instruction of each participant. The matching result includes the following steps:

S51: The target instruction information or random instruction information of each participant is converted into a participant label.

The participant label refers to the numerical or symbolized information obtained by converting the participant's target instruction information or random instruction information. For example, if the participant ’s target instruction information or random instruction information includes stones, scissors, and cloth, the three instruction information are correspondingly converted into numerical or symbolized information to facilitate subsequent processing, such as: “Stone” instruction The mapping is "1", the "scissors" instruction is mapped to "2", and the "cloth" instruction is mapped to "3".

S52: The decision instruction information of the decision maker is converted into a decision maker label.

Among them, the decision maker label refers to the numerical or symbolized information obtained by converting the decision instruction information of the decision maker. Understandably, the decision instruction information of the decision maker corresponds to the target instruction information or random instruction information of the participants, such as: stone, scissors, and cloth. The specific conversion method is also the same as step S51, and is not repeated here.

S53: Match each participant's label and decision-maker's label through a mapping relationship table to obtain the instruction matching result of each participant.

After obtaining the participant labels and decision maker labels, matching is performed through the mapping relationship table, and the instruction matching result of each participant can be obtained. Specifically, a mapping table between participant labels and decision maker labels can be set in advance, and corresponding instruction matching results can be queried in the mapping relationship table according to different participant labels and different decision maker labels. For example: if the match result of the instruction includes three cases of win, draw, and negative, X, Y, and Z can be used to represent the three cases, respectively.

In this embodiment, the instruction matching result of each participant is obtained by converting the corresponding instruction information into a label, and then obtaining the instruction matching result of each participant through a preset mapping relationship table, thereby improving the efficiency of obtaining the instruction matching result.

It should be understood that the size of the sequence numbers of the steps in the above embodiments does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

In one embodiment, a user instruction matching device is provided. The user instruction matching device corresponds to the user instruction matching method in the foregoing embodiment. As shown in FIG. 8, the user instruction matching device includes a participant information acquisition module 10, a target instruction information determination module 20, a random instruction information allocation module 30, a decision instruction information acquisition module 40, and an instruction matching result acquisition module 50. The detailed description of each function module is as follows:

Participant information acquisition module 10, configured to acquire target instruction information of a participant;

A target instruction information determining module 20, configured to determine whether the target instruction information of all participants has been obtained within a valid time;

The random instruction information allocation module 30 is configured to allocate random instruction information to participants who have not obtained the target instruction information if the target instruction information of all participants has not been obtained within the valid time;

The decision instruction information obtaining module 40 is configured to obtain a gesture picture of a decision maker, and recognize a gesture picture of a decision maker, to obtain decision information of the decision maker;

The instruction matching result acquisition module 50 is configured to match the target instruction information or random instruction information of each participant with the decision instruction information of the decision maker through a mapping relationship table to obtain the instruction matching result of each participant.

Preferably, the participant information acquisition module 10 includes a participant information receiving unit and a target instruction information determination unit.

The participant information receiving unit is configured to send a selection instruction to the client, and receive the identity information and initial instruction information of the participant returned by the client.

The target instruction information determining unit is configured to verify identity information. If the identity information is successfully verified, the initial instruction information is determined as the target instruction information.

Preferably, the user instruction matching device further includes a pre-judgment module 21, a contact information acquisition module 22, and a prompt information sending module 23.

The pre-judgment module 21 is configured to determine whether target instruction information of all participants is obtained within a preset time, wherein the preset time is less than the valid time.

The contact information acquisition module 22 is configured to acquire contact information of a participant who has not acquired the target instruction information if the target instruction information of all the participants has not been acquired within a preset time.

The prompt information sending module 23 is configured to send prompt information according to the contact information.

Preferably, the decision instruction information acquisition module 40 includes a gesture area picture acquisition unit and a decision instruction information acquisition unit.

A gesture area picture obtaining unit is used to obtain a gesture picture of a decision maker, and capture a gesture area picture from the gesture picture.

A decision instruction information acquisition unit is configured to input a gesture area picture into a gesture picture recognition model for recognition, and obtain decision information of a decision maker.

Preferably, the decision instruction information acquisition unit includes a gesture training picture acquisition subunit and a gesture picture recognition model acquisition subunit.

A gesture training picture acquisition subunit is used to obtain original pictures, classify each original picture, and form a gesture training picture.

A gesture picture recognition model acquisition subunit is used to train a convolutional neural network model with a gesture training picture to obtain a gesture picture recognition model.

Preferably, the instruction matching result acquisition module 50 includes a participant label conversion unit, a decision maker label conversion unit, and an instruction matching result acquisition unit.

The participant label conversion unit is configured to convert target instruction information or random instruction information of each participant into a participant label.

A decision maker label conversion unit is used to convert decision information of a decision maker into a decision maker label.

The instruction matching result obtaining unit is configured to match each participant label and decision maker label through a mapping relationship table to obtain an instruction matching result of each participant.

For the specific limitation of the user instruction matching device, refer to the foregoing limitation on the user instruction matching method, and details are not described herein again. Each module in the above-mentioned user instruction matching device may be implemented in whole or in part by software, hardware, and a combination thereof. The above-mentioned modules may be embedded in the hardware form or independent of the processor in the computer device, or may be stored in the memory of the computer device in the form of software, so that the processor calls and performs the operations corresponding to the above modules.

In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as shown in FIG. 9. The computer device includes a processor, a memory, a network interface, and a database connected through a system bus. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer-readable instructions, and a database. The internal memory provides an environment for operating the operating system and computer-readable instructions in a non-volatile storage medium. The database of the computer equipment is used to store target instruction information of participants, gesture pictures of decision makers, and gesture picture recognition models. The network interface of the computer device is used to communicate with an external terminal through a network connection. The computer-readable instructions are executed by a processor to implement a user instruction matching method.

In one embodiment, a computer device is provided, including a memory, a processor, and computer-readable instructions stored on the memory and executable on the processor. When the processor executes the computer-readable instructions, the following steps are implemented:

Obtain target instruction information of participants;

In one embodiment, one or more non-volatile readable storage media storing computer-readable instructions are provided, and when the computer-readable instructions are executed by one or more processors, the one or more Each processor performs the following steps:

Obtain target instruction information of participants;

Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be implemented by computer-readable instructions to instruct related hardware. The computer-readable instructions can be stored in a non-volatile computer. In the readable storage medium, the computer-readable instructions, when executed, may include the processes of the embodiments of the methods described above. Wherein, any reference to the memory, storage, database or other media used in the embodiments provided in this application may include non-volatile and / or volatile memory. Non-volatile memory may 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 various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous chain Synchlink DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

Those skilled in the art can clearly understand that, for the convenience and brevity of the description, only the above-mentioned division of functional units and modules is used as an example. In practical applications, the above functions can be allocated by different functional units according to needs. Module completion, that is, dividing the internal structure of the device into different functional units or modules to complete all or part of the functions described above.

The above-mentioned embodiments are only used to describe the technical solution of the present application, but are not limited thereto. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still implement the foregoing implementations. The technical solutions described in the examples are modified, or some of the technical features are equivalently replaced; and these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the application, and should be included in Within the scope of this application.

Claims

A user instruction matching method, comprising:

Obtain target instruction information of participants;

Judging whether target instruction information of all the participants is obtained within a valid time;

If the target instruction information of all the participants is not obtained within the valid time, assigning random instruction information to the participants who have not obtained the target instruction information;

Acquiring a gesture picture of a decision maker, identifying the gesture picture of the decision maker, and obtaining decision instruction information of the decision maker;

Match the target instruction information or the random instruction information of each participant with the decision instruction information of the decision maker through a mapping relationship table to obtain the instruction matching result of each participant.
The user instruction matching method according to claim 1, wherein the acquiring the target instruction information of the participant specifically comprises:

Sending a selection instruction to the client, and receiving the identity information and initial instruction information of the participant returned by the client;

Verify the identity information, and if the identity information verification is successful, determine the initial instruction information as the target instruction information.
The user instruction matching method according to claim 1, wherein after the step of obtaining target instruction information of a participant, and after the determining whether target instructions of all the participants are obtained within a valid time Before the step of information, the method for matching user instructions further includes:

Determining whether target instruction information of all the participants is obtained within a preset time, wherein the preset time is less than the valid time;

If target instruction information of all the participants is not obtained within a preset time, contact information of a participant who does not obtain target instruction information is obtained;

Send prompt information according to the contact information.
The user instruction matching method according to claim 1, wherein the acquiring a gesture picture of a decision maker and identifying the gesture picture of the decision maker to obtain the decision instruction information of the decision maker specifically comprises:

Obtaining a gesture picture of a decision maker, and capturing a gesture area picture from the gesture picture;

The picture of the gesture area is input into a gesture picture recognition model for recognition, and decision instruction information of the decision maker is obtained.
The user instruction matching method according to claim 4, wherein before the step of inputting the gesture area picture into a gesture picture recognition model for recognition, the user instruction matching method further comprises:

Obtaining original pictures, classifying and labeling each of the original pictures to form a gesture training picture;

The convolutional neural network model is trained by using the gesture training picture to obtain a gesture picture recognition model.
The user instruction matching method according to claim 1, wherein the target instruction information or the random instruction information of each of the participants is mapped to the decision instruction information of the decision maker through a mapping relationship The table is matched to obtain the instruction matching result of each participant, including:

Converting the target instruction information or the random instruction information of each participant into a participant label;

Converting the decision instruction information of the decision maker into a decision maker label;

Match each participant label and the decision maker label through a mapping relationship table to obtain an instruction matching result for each participant.
A user instruction matching device, comprising:

Participant information acquisition module, which is used to acquire target instruction information of participants;

A target instruction information judging module, configured to determine whether the target instruction information of all the participants is obtained within a valid time;

A random instruction information allocation module, configured to allocate random instruction information to participants who have not obtained the target instruction information if the target instruction information of all the participants has not been obtained within a valid time;

A decision instruction information acquisition module, configured to obtain a gesture picture of a decision maker, and identify the gesture picture of the decision maker, to obtain the decision instruction information of the decision maker;

The instruction matching result acquisition module is configured to match the target instruction information or the random instruction information of each participant with the decision instruction information of the decision maker through a mapping relationship table to obtain the information of each participant. Instruction match result.
The user instruction matching device according to claim 7, wherein the user instruction matching device further comprises:

A pre-judgment module for determining whether target instruction information of all the participants is obtained within a preset time, wherein the preset time is less than the valid time;

A contact information obtaining module, configured to obtain contact information of a participant who has not obtained the target instruction information if the target instruction information of all the participants has not been obtained within a preset time;

The prompt information sending module is configured to send prompt information according to the contact information.
A computer device includes a memory, a processor, and computer-readable instructions stored in the memory and executable on the processor, wherein the processor implements the computer-readable instructions as follows: step:

Obtain target instruction information of participants;

Judging whether target instruction information of all the participants is obtained within a valid time;

If the target instruction information of all the participants is not obtained within the valid time, assigning random instruction information to the participants who have not obtained the target instruction information;

Acquiring a gesture picture of a decision maker, identifying the gesture picture of the decision maker, and obtaining decision instruction information of the decision maker;

Match the target instruction information or the random instruction information of each participant with the decision instruction information of the decision maker through a mapping relationship table to obtain the instruction matching result of each participant.
The computer device according to claim 9, wherein the acquiring the target instruction information of the participants specifically comprises:

Sending a selection instruction to the client, and receiving the identity information and initial instruction information of the participant returned by the client;

Verify the identity information, and if the identity information verification is successful, determine the initial instruction information as the target instruction information.
The computer device according to claim 9, characterized in that after the step of obtaining target instruction information of the participants, and in the judging whether the target instruction information of all the participants is obtained within a valid time Before the steps, when the processor executes the computer-readable instructions, the following steps are also implemented:

Determining whether target instruction information of all the participants is obtained within a preset time, wherein the preset time is less than the valid time;

If target instruction information of all the participants is not obtained within a preset time, contact information of a participant who does not obtain target instruction information is obtained;

Send prompt information according to the contact information.
The computer device according to claim 9, wherein the acquiring a gesture picture of a decision maker and identifying the gesture picture of the decision maker to obtain the decision instruction information of the decision maker specifically comprises:

Obtaining a gesture picture of a decision maker, and capturing a gesture area picture from the gesture picture;

The picture of the gesture area is input into a gesture picture recognition model for recognition, and decision instruction information of the decision maker is obtained.
The computer device according to claim 12, wherein before the step of inputting the gesture area picture into a gesture picture recognition model for recognition, the processor further implements the following steps when executing the computer-readable instruction:

Obtaining original pictures, classifying and labeling each of the original pictures to form a gesture training picture;

The convolutional neural network model is trained by using the gesture training picture to obtain a gesture picture recognition model.
The computer device according to claim 9, characterized in that the mapping of the target instruction information or the random instruction information of each of the participants with the decision instruction information of the decision maker through a mapping relationship table Match to get the instruction matching result of each participant, including:

Converting the target instruction information or the random instruction information of each participant into a participant label;

Converting the decision instruction information of the decision maker into a decision maker label;

Match each participant label and the decision maker label through a mapping relationship table to obtain an instruction matching result for each participant.
One or more non-volatile readable storage media storing computer-readable instructions, which when executed by one or more processors, cause the one or more processors to perform the following steps:

Obtain target instruction information of participants;

Judging whether target instruction information of all the participants is obtained within a valid time;

If the target instruction information of all the participants is not obtained within the valid time, assigning random instruction information to the participants who have not obtained the target instruction information;

Acquiring a gesture picture of a decision maker, identifying the gesture picture of the decision maker, and obtaining decision instruction information of the decision maker;

Match the target instruction information or the random instruction information of each participant with the decision instruction information of the decision maker through a mapping relationship table to obtain the instruction matching result of each participant.
The non-volatile readable storage medium according to claim 15, wherein the acquiring the target instruction information of the participant specifically comprises:

Sending a selection instruction to the client, and receiving the identity information and initial instruction information of the participant returned by the client;

Verify the identity information, and if the identity information verification is successful, determine the initial instruction information as the target instruction information.
The non-volatile readable storage medium according to claim 15, characterized in that after the step of obtaining target instruction information of a participant, and during the judging whether all the participations are obtained within a valid time Before the steps of the target instruction information of the user, when the computer-readable instructions are executed by the processor, the following steps are also implemented:

Determining whether target instruction information of all the participants is obtained within a preset time, wherein the preset time is less than the valid time;

If target instruction information of all the participants is not obtained within a preset time, contact information of a participant who does not obtain target instruction information is obtained;

Send prompt information according to the contact information.
The non-volatile readable storage medium according to claim 15, wherein the acquiring a gesture picture of a decision maker, identifying the gesture picture of the decision maker, and obtaining the decision instruction information of the decision maker, specifically include:

Obtaining a gesture picture of a decision maker, and capturing a gesture area picture from the gesture picture;

The picture of the gesture area is input into a gesture picture recognition model for recognition, and decision instruction information of the decision maker is obtained.
The non-volatile readable storage medium of claim 18, wherein before the step of inputting the gesture area picture into a gesture picture recognition model for recognition, the computer-readable instructions are further executed by a processor. To achieve the following steps:

Obtaining original pictures, classifying and labeling each of the original pictures to form a gesture training picture;

The convolutional neural network model is trained by using the gesture training picture to obtain a gesture picture recognition model.
The non-volatile readable storage medium according to claim 15, wherein the target instruction information or the random instruction information of each of the participants and the decision instruction of the decision maker The information is matched through the mapping relationship table to obtain the instruction matching result of each participant, including:

Converting the target instruction information or the random instruction information of each participant into a participant label;

Converting the decision instruction information of the decision maker into a decision maker label;

Match each participant label and the decision maker label through a mapping relationship table to obtain an instruction matching result for each participant.