View networking method and device, equipment and medium

Abstract

The invention discloses a view networking method and device, equipment and a medium. The method comprises the following steps: receiving a plurality of pieces of face data pushed by a lower-level data end; determining a clock accuracy index, a data uniqueness index and a picture availability index according to the face data; and according to the clock accuracy index, the data uniqueness index and the picture availability index, quantifying the data pushing quality between the receiving terminal and the subordinate data end. The invention belongs to the field of data transmission monitoring. The data pushing quality between the receiving terminal and the lower-level data end can be quantified through the clock accuracy index, the data uniqueness index and the picture availability index, and the problems that during deployment according to a traditional ministry label picture networking protocol, monitoring means are lacked in the cascading process, the data quality cannot be guaranteed, and the data pushing quality cannot be guaranteed are solved. A series of problems of data delay, incapability of checking pictures, large number of repeated snapshots and the like in the prior art are solved, and the data transmission quality is guaranteed.

Description

Technical Field

[0001] The present invention relates to data transmission monitoring, and in particular to a visual networking method, device, equipment and medium. Background Art

[0002] The transmission process of face data usually involves multiple steps, from data collection to final data reception and processing. It can be divided into the following stages: data collection, data preparation, data compression, data transmission, data reception, data storage, monitoring and maintenance, etc.

[0003] During the process of cascading facial data from the upper level to the lower level, the cascading data protocol follows the traditional ministry-standard image networking protocol. There is a lack of monitoring measures during the cascading process, and the quality of data transmission cannot be guaranteed. There are quality issues such as data delays, inability to view images, and a large number of repeated captures, which seriously affect the use of data. Summary of the invention

[0004] The embodiments of the present invention solve the technical problem of low quality of face data transmission in the prior art by providing a view networking method, device, equipment and medium, and achieve the technical effect of improving the quality of face data transmission.

[0005] In a first aspect, the present invention provides a view networking method, the method comprising:

[0006] Receive some facial data pushed by the lower-level data terminal;

[0007] Determine the clock accuracy index, data uniqueness index, and image availability index based on each face data;

[0008] The data push quality between the receiving terminal and the lower-level data terminal is quantified based on the clock accuracy index, data uniqueness index, and image availability index.

[0009] Furthermore, according to each face data, the clock accuracy index is determined, including:

[0010] Determine the preset clock error range;

[0011] Get the capture time of any face data;

[0012] Record the time when any facial data is received by the receiving terminal;

[0013] When the time difference between the capture time of the facial data and the reception time of the facial data from the lower-level data terminal is within the preset clock error range, or when the capture time of the facial data is earlier than the reception time, the clock accuracy index is qualified.

[0014] Furthermore, it also includes:

[0015] When the time difference between the capture time of the facial data and the receiving time of the facial data from the lower-level data terminal is not within the preset clock error range and the capture time of the facial data is not earlier than the receiving time, the capture device with an inverted clock corresponding to the facial data is determined based on the facial data.

[0016] Furthermore, based on each face data, data uniqueness indicators are determined, including:

[0017] Obtain the capture time of the face data and the capture device number of the face data;

[0018] Constructing a data identifier corresponding to the facial data according to the capturing device number and capturing time of the facial data;

[0019] determining whether any data identifier in any receiving terminal is repeated, the receiving terminal being at least used to receive the data identifier;

[0020] If there are repeated data identifiers of the same type, the receiving terminal is marked, and the number of all marked receiving terminals is counted.

[0021] Further, determining a feature score of the facial data based on the facial data includes:

[0022] Determine the face thumbnail data corresponding to the face data from the pushed face data;

[0023] A feature score of the face thumbnail data is determined based on the clarity and visibility of the face thumbnail data.

[0024] Furthermore, based on the face data of each person, image availability indicators are determined, including:

[0025] Determine whether the information of the capture time, capture location, captured face thumbnail, and captured face large image of the face data in the receiving terminal is missing and whether the thumbnail and large image data corresponding to the face data are accessible;

[0026] If yes, then determine whether the capture time and capture name information superimposed on the image of the face data can be recognized; if not, the face data is unavailable;

[0027] If the capture time and capture name information superimposed on the large face image data can be identified, then it is determined whether the feature score corresponding to the face data is higher than a preset threshold. If not, the face data is unavailable;

[0028] If the feature score corresponding to the face data is higher than the preset threshold, it is determined whether the similarity between the face thumbnail data in the lower-level data terminal and the face thumbnail data parsed from the face large image data in the receiving terminal is higher than the preset threshold. If not, the face data is unavailable.

[0029] If the similarity between the small face image data in the lower-level data terminal and the small face image data parsed from the large face image data in the receiving terminal is higher than a preset threshold, the face data is available; otherwise, the face data is unavailable.

[0030] Furthermore, the data push quality between the receiving terminal and the lower-level data terminal is quantified according to the clock accuracy index, the data uniqueness index, and the picture availability index, including:

[0031] If the clock accuracy index, data uniqueness index and picture availability index are all qualified, the data push quality between the corresponding receiving terminal and the lower-level data terminal is qualified.

[0032] In a second aspect, the present invention provides a view networking device, the device comprising:

[0033] A receiving module is used to receive a number of face data pushed by the lower-level data terminal;

[0034] An indicator determination module, used to determine a clock accuracy indicator, a data uniqueness indicator, and an image availability indicator based on each face data;

[0035] The push quality quantification module is used to quantify the data push quality between the receiving terminal and the lower-level data terminal based on the clock accuracy index, the data uniqueness index and the image availability index.

[0036] In a third aspect, the present invention provides an electronic device, comprising:

[0037] processor;

[0038] a memory for storing processor-executable instructions;

[0039] The processor is configured to execute to implement a view networking method as provided in the first aspect.

[0040] In a fourth aspect, the present invention provides a non-temporary computer-readable storage medium. When instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to implement a view networking method as provided in the first aspect.

[0041] One or more technical solutions provided in the embodiments of the present invention have at least the following technical effects or advantages:

[0042] The present invention provides a view networking method, the method comprising: receiving a number of face data pushed by a subordinate data terminal; determining a clock accuracy index, a data uniqueness index, and a picture availability index according to each face data; and quantifying the data push quality between a receiving terminal and a subordinate data terminal according to the clock accuracy index, the data uniqueness index, and the picture availability index. The present invention can quantify the data push quality between a receiving terminal and a subordinate data terminal through the clock accuracy index, the data uniqueness index, and the picture availability index, and solves the problems that when following the traditional departmental standard picture networking protocol, there is a lack of monitoring means in the cascade process, the quality of data transmission cannot be guaranteed, there are data delays, the inability to view pictures, a large number of repeated snapshots, and the like, and the quality of data transmission is guaranteed. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0044] Figure 1 A schematic diagram of a flow chart of a view networking method provided by the present invention;

[0045] Figure 2 A schematic diagram of the structure of a visual networking device provided by the present invention;

[0046] Figure 3 The present invention provides a schematic structural diagram of an electronic device. DETAILED DESCRIPTION

[0047] The embodiment of the present invention solves the technical problem of low quality of face data transmission in the prior art by providing a view networking method.

[0048] The technical solution of the embodiment of the present invention is to solve the above technical problems, and the overall idea is as follows:

[0049] A view networking method, the method comprising: receiving a number of face data pushed by a subordinate data terminal; determining a clock accuracy index, a data uniqueness index and a picture availability index according to each face data; and quantifying the data push quality between a receiving terminal and the subordinate data terminal according to the clock accuracy index, the data uniqueness index and the picture availability index.

[0050] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0051] First of all, the term "and / or" in this article is only a description of the association relationship of the associated objects, indicating that there can be three relationships. For example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0052] The present invention provides Figure 1 A view networking method shown includes steps S11-S13:

[0053] It should be noted that the purpose of the present invention is to evaluate the quality of face data push between the lower-level data terminal and the receiving terminal. Both the lower-level data terminal and the receiving terminal can store face data and data related to the face data.

[0054] Regarding step S11, a number of face data pushed by the lower-level data terminal are received.

[0055] The lower-level data terminal can collect facial data from cameras or sensors at different locations. After the facial data is collected, the lower-level data terminal can further process the facial data or push it to the receiving terminal.

[0056] Furthermore, processing the facial data includes: determining the facial thumbnail data corresponding to the facial data from the pushed facial data; and determining the feature score of the facial thumbnail data based on the clarity and visibility of the facial thumbnail data.

[0057] It is understandable that the face data collected by the subordinate data terminal includes the surrounding environment. In other words, the face data in the present invention can refer to the environmental data containing the face. An extraction instruction can be sent to the subordinate data terminal to extract the face thumbnail data in the face data, and the face thumbnail data only includes the target face information.

[0058] After obtaining the face thumbnail data, the feature score of the face thumbnail data can also be determined according to the clarity and visibility of the face thumbnail data, including:

[0059] F=A×G+B×L M -C×L S

[0060] Among them, F is the feature score of the face thumbnail data, A, B, and C are all preset weight coefficients, G is the gradient change (the larger the gradient, the clearer the image is, which is used to measure clarity), L M is the average brightness of the face image data (used to measure visibility), L S is the preset brightness standard deviation.

[0061] The face thumbnail data, face data, capture time, capture device number and feature score of the face thumbnail data (which is also the feature score of the face data) can be packaged together and sent to a receiving terminal, and the number of receiving terminals is at least 1.

[0062] Regarding step S12, a clock accuracy index, a data uniqueness index, and a picture availability index are determined based on each face data.

[0063] Determine the clock accuracy index based on each facial data, including: determine the preset clock error range; obtain the capture time of any facial data; when the time difference between the capture time of the facial data and the receiving time of the facial data received from the lower-level data terminal is within the preset clock error range, or (and), the capture time of the facial data is earlier than the receiving time, then the clock accuracy index is qualified.

[0064] The preset clock error range can be determined according to actual conditions. The capture time refers to the time when the facial data is captured. It is understandable that since the camera equipment may be inconsistent with the standard time, the time when the facial data is captured is also inconsistent with the standard time.

[0065] Generally speaking, after the facial data is collected at the lower-level data end, it is packaged and sent to the receiving terminal. The receiving terminal is connected to the Internet (clock server), and the receiving time can be considered as the standard time.

[0066] For example, the receiving time of the facial data is 10:35, the capture time is 10:36, and the preset clock error range is 30s. Then the time difference between the capture time of the facial data and the receiving time of the facial data from the lower-level data terminal is not within the preset clock error range and the capture time of the facial data is not earlier than the receiving time.

[0067] When the time difference between the capture time of the facial data and the receiving time of the facial data from the lower-level data terminal is not within the preset clock error range and the capture time of the facial data is not earlier than the receiving time, the clock inverted capture device corresponding to the facial data is determined based on the facial data (the capture device time is much slower than the actual time, and even a device with reverse time).

[0068] Based on each facial data, determine the data uniqueness index, including: obtain the capture time of the facial data and the capture device number of the facial data; determine the feature score of the facial data based on the facial data; construct a data identifier corresponding to the facial data based on the capture device number and the capture time of the facial data; determine whether any data identifier in any receiving terminal is repeated, and the receiving terminal is at least used to receive the data identifier; if there is a repeated data identifier of the same type, mark the receiving terminal, and count the number of all marked receiving terminals.

[0069] It should be noted that the step of "determining the feature score of the facial data based on the facial data" can be executed by the receiving terminal. In other words, the receiving terminal determines the face thumbnail data corresponding to the facial data from the pushed facial data; and determines the feature score of the face thumbnail data based on the clarity and visibility of the face thumbnail data.

[0070] The capture device number and capture time constitute the unique data identifier corresponding to the facial data. It can be understood that there are more than one receiving terminals, and the same facial data may be sent twice to the same receiving terminal. If so, the data uniqueness index corresponding to the receiving terminal is unqualified, and the receiving terminal is marked.

[0071] Determining the image availability index according to each face data includes: determining whether the face data in the receiving terminal and the small face image data and the large face image data corresponding to the face data are accessible;

[0072] If the face data in the receiving terminal and the small face image data and large face image data corresponding to the face data can be accessed, then determine whether the capture time and capture name information superimposed on the image by the large face image data can be identified; if the face data in the receiving terminal and the small face image data and large face image data corresponding to the face data cannot be accessed, then the face data is unavailable and the image availability index fails;

[0073] If the capture time and capture name information superimposed on the face image data can be identified, then it is determined whether the feature score corresponding to the face data is higher than the preset threshold. If the capture time and capture name information of the face data cannot be identified, then the face data is unavailable and the image availability index fails.

[0074] If the feature score corresponding to the face data is higher than the preset threshold, it is determined whether the similarity between the face thumbnail data in the subordinate data terminal and the face thumbnail data parsed from the face large image data in the receiving terminal is higher than the preset threshold; if the feature score corresponding to the face data is not higher than the preset threshold, the face data is unavailable and the image availability index is unqualified;

[0075] If the similarity between the thumbnail data of the face in the lower-level data terminal and the thumbnail data of the face parsed from the large image data of the face in the receiving terminal is higher than the preset threshold, the face data is available; if the similarity between the thumbnail data of the face in the lower-level data terminal and the thumbnail data of the face in the receiving terminal is not higher than the preset threshold, the face data is unavailable.

[0076] Regarding step S13, the data push quality between the receiving terminal and the lower-level data terminal is determined according to the clock accuracy index, the data uniqueness index and the picture availability index.

[0077] If the clock accuracy index, data uniqueness index and picture availability index are all qualified, the data push quality between the corresponding receiving terminal and the lower-level data terminal is qualified.

[0078] In summary, the present invention provides a method for visual networking, the method comprising: receiving a number of face data pushed by a subordinate data terminal; determining a clock accuracy index, a data uniqueness index, and a picture availability index according to each face data; quantifying the data push quality between the receiving terminal and the subordinate data terminal according to the clock accuracy index, the data uniqueness index, and the picture availability index. The present invention can quantify the data push quality between the receiving terminal and the subordinate data terminal through the clock accuracy index, the data uniqueness index, and the picture availability index, solving the problems of lack of monitoring means in the cascade process, inability to guarantee data transmission quality, data delay, inability to view pictures, and a large number of repeated snapshots when following the traditional departmental standard picture networking protocol, thereby ensuring the quality of data transmission.

[0079] Based on the same inventive concept, the present invention provides Figure 2 A view networking device is shown, the device comprising:

[0080] The acquisition module 21 is used to receive a number of face data pushed by the lower-level data terminal;

[0081] An index determination module 22, used to determine a clock accuracy index, a data uniqueness index, and a picture availability index according to each face data;

[0082] The push quality determination module 23 is used to quantify the data push quality between the receiving terminal and the lower-level data terminal according to the clock accuracy index, the data uniqueness index and the picture availability index. Based on the same inventive concept, the present invention also provides the following Figure 3 An electronic device as shown includes:

[0083] Processor 31;

[0084] A memory 32 for storing instructions executable by the processor 31;

[0085] The processor 31 is configured to execute to implement a view networking device as provided above.

[0086] Based on the same inventive concept, the present invention also provides a non-temporary computer-readable storage medium. When the instructions in the storage medium are executed by the processor 31 of the electronic device, the electronic device can execute and implement a view networking device as provided above.

[0087] Since the electronic device introduced in this embodiment is an electronic device used to implement the information processing method in the embodiment of the present invention, based on the information processing method introduced in the embodiment of the present invention, a person skilled in the art can understand the specific implementation of the electronic device of this embodiment and its various variations, so how the electronic device implements the method in the embodiment of the present invention is not described in detail here. As long as the electronic device used by a person skilled in the art to implement the information processing method in the embodiment of the present invention, it belongs to the scope of protection of the present invention.

[0088] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0089] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0090] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0091] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0092] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0093] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A view networking method, characterized in that: The method comprises: Receive some facial data pushed by the lower-level data terminal; Determine the clock accuracy index, data uniqueness index, and image availability index based on each face data; The data push quality between the receiving terminal and the lower-level data terminal is quantified according to the clock accuracy index, the data uniqueness index and the picture availability index.

2. A method for networking views as claimed in claim 1, characterized in that: Based on each person’s face data, determine the clock accuracy indicators, including: Determine the preset clock error range; Get the capture time of any face data; Record the time when any facial data is received by the receiving terminal; When the time difference between the capture time of the facial data and the reception time of the facial data from the subordinate data terminal is within the preset clock error range, or when the capture time of the facial data is earlier than the reception time, the clock accuracy index is qualified.

3. A view networking method as claimed in claim 2, characterized in that: Also includes: When the time difference between the capture time of the facial data and the receiving time of the facial data from the lower-level data terminal is not within the preset clock error range and the capture time of the facial data is not earlier than the receiving time, the capture device with an inverted clock corresponding to the facial data is determined based on the facial data.

4. A method for networking views as claimed in claim 1, characterized in that: According to each face data, determine the data uniqueness indicators, including: Obtain the capture time of the face data and the capture device number of the face data; Constructing a data identifier corresponding to the facial data according to the capturing device number and capturing time of the facial data; determining whether any data identifier in any receiving terminal is repeated, the receiving terminal being at least used to receive the data identifier; If there are repeated data identifiers of the same type, the receiving terminal is marked, and the number of all marked receiving terminals is counted.

5. A method for networking views as claimed in claim 4, characterized in that: Determining the feature score of the facial data according to the facial data includes: Determine the face thumbnail data corresponding to the face data from the pushed face data; A feature score of the face thumbnail data is determined based on the clarity and visibility of the face thumbnail data.

6. A method for networking views as claimed in claim 1, characterized in that: Based on the face data of each person, determine the image usability indicators, including: Determine whether the information of the capture time, capture location, captured face thumbnail, and captured face large image of the face data in the receiving terminal is missing and whether the thumbnail and large image data corresponding to the face data are accessible; If yes, then determine whether the capture time and capture name information superimposed on the image of the face data can be recognized; if not, the face data is unavailable; If the capture time and capture name information superimposed on the large face image data can be identified, then it is determined whether the feature score corresponding to the face data is higher than a preset threshold. If not, the face data is unavailable; If the feature score corresponding to the face data is higher than the preset threshold, it is determined whether the similarity between the face thumbnail data in the lower-level data terminal and the face thumbnail data parsed from the face large image data in the receiving terminal is higher than the preset threshold; if not, the face data is unavailable; If the similarity between the small face image data in the lower-level data terminal and the small face image data parsed from the large face image data in the receiving terminal is higher than the preset threshold, the face data is available; otherwise, the face data is unavailable.

7. A method for networking views as claimed in claim 1, characterized in that: The quantifying the data push quality between the receiving terminal and the lower-level data terminal according to the clock accuracy index, the data uniqueness index and the picture availability index includes: If the clock accuracy index, the data uniqueness index and the picture availability index are all qualified, the data push quality between the corresponding receiving terminal and the lower-level data terminal is qualified.

8. A view networking device, characterized in that: The device comprises: A receiving module is used to receive a number of face data pushed by the lower-level data terminal; An indicator determination module, used to determine a clock accuracy indicator, a data uniqueness indicator, and an image availability indicator based on each face data; The push quality quantification module is used to quantify the data push quality between the receiving terminal and the lower-level data terminal according to the clock accuracy index, the data uniqueness index and the picture availability index.

9. An electronic device, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute to implement a view networking method as described in any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium, characterized in that: When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device is enabled to implement a view networking method as described in any one of claims 1 to 7.

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