WO2023000831A1 - Structured information extraction method and apparatus, and device, and storage medium - Google Patents

Abstract

The present disclosure provides a structured information extraction method and apparatus, a device, a storage medium, and a program product, and relates to the field of artificial intelligence, more particularly to the fields of computer vision and deep learning. A specific implementation comprises: extracting a target sporting event video frame from a sporting event video; performing target detection on the target sporting event video frame to obtain designated target information in the sporting event; and aggregating the designated target information to obtain sporting event structured information. The present disclosure can efficiently extract key information from a sporting event video, form structured data, provide high quality material for sporting event highlights, and aid in completing rapid content creation for sporting events.

Description

Structured information extraction method, device, equipment and storage medium

This patent application claims the priority of the Chinese patent application filed on July 23, 2021 with the application number 202110838170.7 and the title of the invention is "Structural Information Extraction Method, Device, Equipment and Storage Medium", the full text of which is cited incorporated into this application.

technical field

The present disclosure relates to the field of artificial intelligence, in particular to the fields of computer vision and deep learning, and specifically relates to a structured information extraction method, device, device, and storage medium.

Background technique

With the rise of the short video craze, people have a strong demand for short and refined video content. For sports game videos, more people choose to complete the information reception of video content by watching video highlights, compared to the complete and lengthy original sports game video content. Taking the table tennis game as an example, it has a round system, process repetition, sports process and broadcast scene specification and has obvious rules, which is especially suitable for extracting rounds, obtaining structured information of the game process, and providing high-quality materials for game highlights , to complete the rapid content creation of sports events.

At present, table tennis highlights are mainly produced by manual editing. The editors of table tennis events mark the start and end time points of the round and extract video clips based on personal experience.

Contents of the invention

The disclosure provides a structured information extraction method, device, equipment, storage medium and program product.

According to the first aspect of the present disclosure, a method for extracting structured information is provided, including: extracting a target sports event video frame from a sports event video; performing target detection on the target sports event video frame to obtain specified target information in the sports event ; Aggregate the specified target information to obtain the structured information of sports events.

According to a second aspect of the present disclosure, a device for extracting structured information is provided, including: an extraction module configured to extract a target sports event video frame from a sports event video; a detection module configured to extract the target sports event video frame Target detection is performed to obtain specified target information in sports events; the aggregation module is configured to aggregate the specified target information to obtain structured information of sports events.

According to a third aspect of the present disclosure, an electronic device is provided, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by Executed by at least one processor, so that at least one processor can execute the method described in any implementation manner of the first aspect.

According to a fourth aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause a computer to execute the method described in any implementation manner of the first aspect.

According to a fifth aspect of the present disclosure, a computer program product is provided, including a computer program, and when the computer program is executed by a processor, the method described in any implementation manner of the first aspect is implemented.

It should be understood that what is described in this section is not intended to identify key or important features of the embodiments of the present disclosure, nor is it intended to limit the scope of the present disclosure. Other features of the present disclosure will be readily understood through the following description.

Description of drawings

The accompanying drawings are used to better understand the present solution, and do not constitute a limitation to the present disclosure. in:

FIG. 1 is a flowchart of an embodiment of a method for extracting structured information according to the present disclosure;

Fig. 2 is a flow chart of another embodiment of the method for extracting structured information according to the present disclosure;

Fig. 3 is a schematic structural diagram of a target detection model;

FIG. 4 is a scene diagram of a structured information extraction method that can implement an embodiment of the present disclosure;

Fig. 5 is a schematic structural diagram of an embodiment of a device for extracting structured information according to the present disclosure;

Fig. 6 is a block diagram of an electronic device for implementing the structured information extraction method of the embodiment of the present disclosure.

detailed description

Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and they should be regarded as exemplary only. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.

It should be noted that, in the case of no conflict, the embodiments in the present disclosure and the features in the embodiments can be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings and embodiments.

Fig. 1 shows a flow 100 of an embodiment of a method for extracting structured information according to the present disclosure. The structured information extraction method includes the following steps:

Step 101, extracting target sports event video frames from the sports event video.

In this embodiment, the executing body of the method for extracting structured information may extract target sports event video frames from the sports event video.

Among them, sports events generally refer to regular competitions with a relatively large scale and level. Therefore, sports event videos are generally relatively standardized and have obvious rules. For example, a table tennis event has a round system, process repetition, action process and broadcast scene specification and has obvious rules. Considering the time and calculation efficiency of each round, some sports event video frames can be extracted from the sports event video as the target sports event video frame. For example, the video frame of the target sports event is obtained by extracting one frame per second from the video of the sports event.

Step 102, performing target detection on the video frame of the target sporting event to obtain specified target information in the sporting event.

In this embodiment, the execution subject may perform target detection on the video frame of the target sporting event to obtain specified target information in the sporting event.

Wherein, the specified target in the sports event may be a specified target appearing in the video of the sports event. Taking a table tennis event as an example, the designated targets in the sports event may include but not limited to: table tennis table, scoreboard, athletes, national flag, and so on. The designated target information in the sports event may be the key information of the sports event video, including but not limited to any one or more of field information, scoreboard information, player identity information, midfield statistical information, national flag information, and the like.

Step 103, aggregate the designated target information to obtain structured information about sports events.

In this embodiment, the above-mentioned executive body may aggregate the designated target information to obtain structured information about sports events.

Among them, the structured information of sports events means that the specified target information in sports events can be decomposed into multiple interrelated components after analysis, and each component has a clear hierarchical structure. Usually, at least one type of specified target information in the sports event can be aggregated into one type of structured information about the sports event. For example, a kind of designated target information in sports events can be aggregated into a kind of structured information of sports events. For another example, multiple types of specified target information in sports events may also be aggregated into a type of structured information on sports events.

The disclosure can efficiently extract key information in sports event videos, form structured data, provide high-quality materials for sports event collections, and help complete rapid content creation of sports events.

Continue to refer to FIG. 2 , which shows a flow 200 of another embodiment of the method for extracting structured information according to the present disclosure. The structured information extraction method includes the following steps:

Step 201, extract target sports event video frames from the sports event video.

In this embodiment, the specific operation of step 201 has been introduced in detail in step 101 in the embodiment shown in FIG. 1 , and will not be repeated here.

Step 202: Input the video frame of the target sports event into the pre-trained target detection model to obtain the specified target information in the sports event.

In this embodiment, the executive body of the structured information extraction method may input the target sports event video frame into the pre-trained target detection model to obtain the specified target information in the sports event.

Among them, the target detection model can be used to detect specified target information in sports events. The designated goal information in the sporting event may include the category of the designated goal in the sporting event and/or the location of the designated goal. The target detection model can be a deep learning model to detect effective information in sports event videos. Usually, a target detection model can include multiple concatenated class-position subnets (class+box subnets), a class-position subnet can include a class subnet branch (class subnet) and a position subnet branch (box subnet), and a class subnet The net branch can be used to detect the category of the specified target in the sporting event, and the location subnet branch can be used to detect the location of the specified target in the sporting event.

For ease of understanding, FIG. 3 shows a schematic structural diagram of a target detection model. As shown in Figure 3, the object detection model consists of 3 class+box subnets connected in series. Each class+box subnets includes a class subnet and a box subnet. The class subnet can process the input into a feature map, and finally output the category of the specified target in the sports event. The box subnet can process the output into a feature map, and finally output the position of the specified target in the sports event. where W is the width, H is the height, K is the number of categories, and 4 is the dimension of the position coordinates.

Step 203, clustering the designated target information according to time information to obtain information time series corresponding to the designated target information in sports events.

In this embodiment, the execution subject may cluster the designated target information according to time information to obtain information time series corresponding to the designated target information in sports events. Wherein, time clustering is performed on each designated target information respectively, and the information time series of each designated target is obtained.

Step 204, based on the information time series, obtain the structured information of sports events.

In this embodiment, the execution subject may obtain the structured information of the sports event based on the information time series.

Where the designated target information includes field information, scoreboard information, player identity information, midfield statistics, and national flag information, the details are as follows:

1. Based on the information time series corresponding to the national flag information and the information time series corresponding to the athlete's identity information, obtain the information of the athletes in the competition.

In addition, the preset knowledge graph can be used to store a large number of athletes' pre-stored information. If the competition athlete information exists in the preset knowledge graph, other pre-stored information of the athletes corresponding to the competition athlete information is obtained in the preset knowledge graph, so as to expand the competition athlete information.

2. Obtain game score information based on the information time series corresponding to the midfield statistical information.

3. Use the image difference algorithm to process the information time series corresponding to the scoreboard information to obtain the game score information.

4. Based on the information time series corresponding to the information of the competition venue, the preliminary match fragments are obtained, and the preliminary match fragments are filtered using the match score information and the scoreboard information to obtain the match round time information.

Usually, using game score information can filter non-game sparring clips, such as pre-match warm-up, post-match review, and so on. The scoreboard information can be used to filter non-fighting rounds during the game, such as re-serve, highlight ball playback, etc.

Finally, the structured information of sports events can be obtained based on the player information, game score information, game score information, and match sparring round time information. In addition, in the case of expanding the player information based on the preset knowledge graph, based on the player information, other pre-stored information, game score information, game score information, and game sparring round time information, the structured information of sports events is obtained.

It can be seen from FIG. 2 that, compared with the embodiment corresponding to FIG. 1 , the structured information extraction method in this embodiment highlights the detection step and the aggregation step. Therefore, the solution described in this embodiment can detect effective information in the sports event video by using the target detection model. Time clustering is first performed on the specified target information in sports events, and then the clustering results are integrated to make the structured information of sports events more comprehensive.

Further referring to FIG. 4 , it shows a scene diagram that can implement the structured information extraction method of the embodiment of the present disclosure. As shown in Figure 4, the structured information extraction method includes steps such as data preparation, game key information detection, and game key information aggregation strategy. The specific content is as follows:

1. Data preparation: Extract video frames from the table tennis video to obtain a video sequence.

2. Detection of key information of the game: Input the video sequence into the target detection model to obtain the key information of the table tennis game.

3. Aggregation strategy for key information of the game: firstly, time-aggregate the key information of the table tennis game to obtain national flag information, athlete name information, midfield statistical information, scoreboard information and competition venue information. Then, player information can be generated based on national flag information and player name information, and filled based on KG (Knowledge Graph, knowledge map); midfield statistics can generate game score information; scoreboard information can generate score information by using image difference to obtain score changes ; The competition field information can generate preliminary sparring round information, and use the round score information and scoreboard information to filter the preliminary sparring round information to obtain round time information. Finally, based on player information, game score information, score information and round time information, the structured information of the table tennis game can be obtained.

Further referring to FIG. 5 , as an implementation of the methods shown in the above figures, the present disclosure provides an embodiment of a device for extracting structured information. This device embodiment corresponds to the method embodiment shown in FIG. 1 , and the device Specifically, it can be applied to various electronic devices.

As shown in FIG. 5 , the structured information extraction apparatus 500 of this embodiment may include: an extraction module 501 , a detection module 502 and an aggregation module 503 . Wherein, the extraction module 501 is configured to extract the target sports event video frame from the sports event video; the detection module 502 is configured to perform target detection on the target sports event video frame to obtain specified target information in the sports event; the aggregation module 503 , configured to aggregate the specified target information to obtain structured information about sports events.

In this embodiment, in the structured information extraction device 500: the specific processing of the extraction module 501, the detection module 502 and the aggregation module 503 and the technical effects brought about by them can refer to the steps 101-103 in the corresponding embodiment in Fig. 1 respectively Relevant descriptions will not be repeated here.

In some optional implementations of this embodiment, the detection module 502 is further configured to: input the video frame of the target sports event into a pre-trained target detection model to obtain specified target information in the sports event.

In some optional implementation manners of this embodiment, the designated target information in the sports event includes a category of the designated target and/or a position of the designated target in the sports event.

In some optional implementations of this embodiment, the target detection model includes a plurality of class-position subnets in series, the class-position subnet includes a class subnet branch and a position subnet branch, and the class subnet branch is used to detect The category of the specified object in the sporting event, and the location subnetwork branch is used to detect the location of the specified object in the sporting event.

In some optional implementations of this embodiment, the aggregation module 503 includes: a clustering submodule configured to cluster the specified target information according to time information to obtain information time series corresponding to the specified target information in sports events; The obtaining sub-module is configured to obtain structured information of sports events based on information time series.

In some optional implementation manners of this embodiment, the specified target information includes at least one of the following: playing field information, scoreboard information, athlete identity information, midfield statistical information, and national flag information.

In some optional implementations of this embodiment, when the designated target information includes information about the playing field, scoreboard information, player identity information, midfield statistical information, and national flag information, the acquisition submodule includes: a first acquisition unit , is configured to obtain player information based on the information time series corresponding to the national flag information and the information time series corresponding to the player identity information; the second acquisition unit is configured to obtain game points based on the information time series corresponding to the midfield statistical information Information; the third acquisition unit is configured to use the image difference algorithm to process the information time series corresponding to the scoreboard information to obtain the game score information; the fourth acquisition unit is configured to be based on the information time series corresponding to the game venue information, Obtain the preliminary game sparring segment, and use the game score information and scoreboard information to filter the preliminary game sparring segment to obtain the game sparring round time information; the fifth acquisition unit is configured to Information, game score information and match round time information, to obtain structured information on sports events.

In some optional implementations of this embodiment, the acquisition submodule further includes: a detection unit configured to detect whether the player information exists in the preset knowledge map; the sixth acquisition unit is configured to if the player information exists in the preset knowledge map, then obtain other pre-stored information of the players corresponding to the player information in the preset knowledge map; the fifth acquisition unit is further configured to: based on the player information, other pre-stored information, game score information, Match score information and match round time information to obtain structured information about sports events.

In the technical solution of the present disclosure, the acquisition, storage and application of the user's personal information involved are in compliance with relevant laws and regulations, and do not violate public order and good customs.

According to the embodiments of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium, and a computer program product.

FIG. 6 shows a schematic block diagram of an example electronic device 600 that may be used to implement embodiments of the present disclosure. Electronic device is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. Electronic devices may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are by way of example only, and are not intended to limit implementations of the disclosure described and/or claimed herein.

As shown in FIG. 6, the device 600 includes a computing unit 601 that can execute according to a computer program stored in a read-only memory (ROM) 602 or loaded from a storage unit 608 into a random-access memory (RAM) 603. Various appropriate actions and treatments. In the RAM 603, various programs and data necessary for the operation of the device 600 can also be stored. The computing unit 601, ROM 602, and RAM 603 are connected to each other through a bus 604. An input/output (I/O) interface 605 is also connected to the bus 604 .

Multiple components in the device 600 are connected to the I/O interface 605, including: an input unit 606, such as a keyboard, a mouse, etc.; an output unit 607, such as various types of displays, speakers, etc.; a storage unit 608, such as a magnetic disk, an optical disk, etc. ; and a communication unit 609, such as a network card, a modem, a wireless communication transceiver, and the like. The communication unit 609 allows the device 600 to exchange information/data with other devices over a computer network such as the Internet and/or various telecommunication networks.

The computing unit 601 may be various general-purpose and/or special-purpose processing components having processing and computing capabilities. Some examples of computing units 601 include, but are not limited to, central processing units (CPUs), graphics processing units (GPUs), various dedicated artificial intelligence (AI) computing chips, various computing units that run machine learning model algorithms, digital signal processing processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 601 executes various methods and processes described above, such as the structured information extraction method. For example, in some embodiments, the structured information extraction method may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as storage unit 608 . In some embodiments, part or all of the computer program may be loaded and/or installed on the device 600 via the ROM 602 and/or the communication unit 609. When the computer program is loaded into RAM 603 and executed by computing unit 601, one or more steps of the structured information extraction method described above can be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to execute the structured information extraction method in any other suitable manner (for example, by means of firmware).

Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips Implemented in a system of systems (SOC), load programmable logic device (CPLD), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include being implemented in one or more computer programs executable and/or interpreted on a programmable system including at least one programmable processor, the programmable processor Can be special-purpose or general-purpose programmable processor, can receive data and instruction from storage system, at least one input device, and at least one output device, and transmit data and instruction to this storage system, this at least one input device, and this at least one output device an output device.

Program codes for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special purpose computer, or other programmable data processing devices, so that the program codes, when executed by the processor or controller, make the functions/functions specified in the flow diagrams and/or block diagrams Action is implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of machine-readable storage media would include one or more wire-based electrical connections, portable computer discs, hard drives, random access memory (RAM), read only memory (ROM), erasable programmable read only memory (EPROM or flash memory), optical fiber, compact disk read only memory (CD-ROM), optical storage, magnetic storage, or any suitable combination of the foregoing.

To provide for interaction with the user, the systems and techniques described herein can be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user. ); and a keyboard and pointing device (eg, a mouse or a trackball) through which a user can provide input to the computer. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and can be in any form (including Acoustic input, speech input or, tactile input) to receive input from the user.

The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., as a a user computer having a graphical user interface or web browser through which a user can interact with embodiments of the systems and techniques described herein), or including such backend components, middleware components, Or any combination of front-end components in a computing system. The components of the system can be interconnected by any form or medium of digital data communication, eg, a communication network. Examples of communication networks include: Local Area Network (LAN), Wide Area Network (WAN) and the Internet.

A computer system may include clients and servers. Clients and servers are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, a server of a distributed system, or a server combined with a blockchain.

It should be understood that steps may be reordered, added or deleted using the various forms of flow shown above. For example, each step described in the present disclosure may be executed in parallel, sequentially, or in a different order, as long as the desired result of the technical solution disclosed in the present disclosure can be achieved, no limitation is imposed herein.

The specific implementation manners described above do not limit the protection scope of the present disclosure. It should be apparent to those skilled in the art that various modifications, combinations, sub-combinations and substitutions may be made depending on design requirements and other factors. Any modifications, equivalent replacements and improvements made within the spirit and principles of the present disclosure shall be included within the protection scope of the present disclosure.

Claims (19)

1. A method for extracting structured information, comprising:

   Extract the target sports event video frame from the sports event video;

   Carrying out target detection on the video frame of the target sporting event to obtain specified target information in the sporting event;

   The specified target information is aggregated to obtain structured information about sports events.
2. The method according to claim 1, wherein said performing target detection on said target sports event video frame to obtain specified target information in the sport event, comprising:

   The video frame of the target sporting event is input to a pre-trained target detection model to obtain specified target information in the sporting event.
3. The method according to claim 2, wherein the designated target information in the sporting event includes a category of the designated target in the sporting event and/or a position of the designated target.
4. The method according to claim 3, wherein the object detection model comprises a plurality of class-position subnetworks connected in series, the class-position subnetwork includes a class subnetwork branch and a position subnetwork branch, and the class subnetwork The branch is used to detect the category of the designated target in the sporting event, and the position subnetwork branch is used to detect the position of the designated target in the sporting event.
5. The method according to claim 1, wherein said aggregating said designated target information to obtain structured information of sports events comprises:

   clustering the designated target information according to time information to obtain information time series corresponding to the designated target information in the sports event;

   Based on the information time series, the sports event structured information is obtained.
6. The method according to any one of claims 1-5, wherein the designated target information includes at least one of the following: playing field information, scoreboard information, player identity information, midfield statistical information, national flag information.
7. According to the method according to claim 6, in the case where the specified target information includes field information, scoreboard information, player identity information, midfield statistical information and national flag information,

   The obtaining of the sports event structured information based on the information time series includes:

   Based on the information time series corresponding to the national flag information and the information time series corresponding to the athlete identity information, obtain the information of the athletes in the competition;

   Obtain game score information based on the information time series corresponding to the midfield statistical information;

   Using the image difference algorithm, the information time series corresponding to the scoreboard information is processed to obtain the game score information;

   Based on the information time series corresponding to the competition venue information, obtain the preliminary match sparring segment, and use the game round score information and the scoreboard information to filter the preliminary match sparring segment, and obtain the match sparring round time information;

   The sports event structured information is acquired based on the competition player information, the competition round score information, the competition score information and the competition round time information.
8. The method according to claim 7, said method further comprising:

   Detect whether the player information of the competition exists in the preset knowledge map;

   If the competition player information exists in the preset knowledge graph, then obtain other pre-stored information of the player corresponding to the competition player information in the preset knowledge graph;

   The acquisition of the sports event structured information based on the competition player information, the competition score information, the competition score information and the competition round time information includes:

   The sports event structured information is acquired based on the competition player information, the other pre-stored information, the game score information, the game score information and the competition round time information.
9. A structured information extraction device, comprising:

   The extraction module is configured to extract a target sports event video frame from the sports event video;

   The detection module is configured to perform target detection on the target sports event video frame to obtain specified target information in the sports event;

   The aggregation module is configured to aggregate the specified target information to obtain structured information about sports events.
10. The apparatus according to claim 9, wherein the detection module is further configured to:

    The video frame of the target sporting event is input to a pre-trained target detection model to obtain specified target information in the sporting event.
11. The apparatus according to claim 10, wherein the designated target information in the sporting event includes a category of the designated target in the sporting event and/or a position of the designated target.
12. The apparatus according to claim 11, wherein the object detection model comprises a plurality of class-position subnetworks connected in series, the class-position subnetwork includes a class subnetwork branch and a position subnetwork branch, and the class subnetwork The branch is used to detect the category of the designated target in the sporting event, and the position subnetwork branch is used to detect the position of the designated target in the sporting event.
13. The device according to claim 9, wherein the aggregation module comprises:

    The clustering submodule is configured to cluster the specified target information according to time information, and obtain the information time series corresponding to the specified target information in the sports event;

    The obtaining submodule is configured to obtain the structured information of the sports event based on the information time series.
14. The device according to any one of claims 9-13, wherein the designated target information includes at least one of the following: playing field information, scoreboard information, player identity information, midfield statistical information, national flag information.
15. The device according to claim 14, in the case where the designated target information includes field information, scoreboard information, player identity information, midfield statistical information and national flag information,

    The acquisition submodule includes:

    The first acquisition unit is configured to acquire player information based on the information time series corresponding to the national flag information and the information time series corresponding to the athlete identity information;

    The second obtaining unit is configured to obtain game score information based on the information time series corresponding to the midfield statistical information;

    The third acquisition unit is configured to use an image difference algorithm to process the information time series corresponding to the scoreboard information to obtain game score information;

    The fourth acquisition unit is configured to obtain a preliminary game sparring segment based on the information time series corresponding to the playing field information, and use the game game score information and the scoreboard information to perform the preliminary game sparring segment Filter to get the time information of the sparring round;

    The fifth acquiring unit is configured to acquire the sports event structured information based on the player information, the match score information, the match score information and the match sparring round time information.
16. The device according to claim 15, the acquiring submodule further comprising:

    A detection unit configured to detect whether the player information exists in the preset knowledge map;

    The sixth acquisition unit is configured to acquire other pre-stored information of the player corresponding to the player information in the preset knowledge graph if the player information exists in the preset knowledge graph;

    The fifth acquisition unit is further configured to:

    Based on the competition player information, the other pre-stored information, the competition score information, the competition score information and the competition round time information, the sports event structured information is acquired.
17. An electronic device comprising:

    at least one processor; and

    a memory communicatively coupled to the at least one processor; wherein,

    The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can perform any one of claims 1-8. Methods.
18. A non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to cause the computer to execute the method according to any one of claims 1-8.
19. A computer program product comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-8.

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