WO2023000831A1 - Procédé et appareil d'extraction d'informations structurées, et dispositif et support de stockage - Google Patents

Procédé et appareil d'extraction d'informations structurées, et dispositif et support de stockage Download PDF

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Publication number
WO2023000831A1
WO2023000831A1 PCT/CN2022/096180 CN2022096180W WO2023000831A1 WO 2023000831 A1 WO2023000831 A1 WO 2023000831A1 CN 2022096180 W CN2022096180 W CN 2022096180W WO 2023000831 A1 WO2023000831 A1 WO 2023000831A1
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Prior art keywords
information
target
competition
player
structured
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PCT/CN2022/096180
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English (en)
Chinese (zh)
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唐鑫
叶芷
王冠皓
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北京百度网讯科技有限公司
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Publication of WO2023000831A1 publication Critical patent/WO2023000831A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/70—Information retrieval; Database structures therefor; File system structures therefor of video data
    • G06F16/78—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/783—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
    • G06F16/7844—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content using original textual content or text extracted from visual content or transcript of audio data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/25—Integrating or interfacing systems involving database management systems
    • G06F16/258—Data format conversion from or to a database

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  • 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.
  • 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.
  • the disclosure provides a structured information extraction method, device, equipment, storage medium and program product.
  • a method for extracting structured information 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.
  • a device for extracting structured information 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.
  • an electronic device 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.
  • 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.
  • a computer program product 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.
  • 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.
  • 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.
  • the executing body of the method for extracting structured information may extract target sports event video frames from the sports event video.
  • 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.
  • 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.
  • the specified target in the sports event may be a specified target appearing in the video of the sports event.
  • 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.
  • the above-mentioned executive body may aggregate the designated target information to obtain structured information about sports events.
  • 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.
  • 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.
  • a kind of designated target information in sports events can be aggregated into a kind of structured information of sports events.
  • 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.
  • FIG. 2 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • FIG. 3 shows a schematic structural diagram of a target detection model.
  • 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.
  • W is the width
  • H is the height
  • K is the number of categories
  • 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.
  • 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.
  • the execution subject may obtain the structured information of the sports event based on the information time series.
  • designated target information includes field information, scoreboard information, player identity information, midfield statistics, and national flag information
  • the details are as follows:
  • 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.
  • 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.
  • 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.
  • 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.
  • the structured information of sports events is obtained.
  • 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.
  • FIG. 4 it shows a scene diagram that can implement the structured information extraction method of the embodiment of the present disclosure.
  • 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:
  • Data preparation Extract video frames from the table tennis video to obtain a video sequence.
  • 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.
  • 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.
  • 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.
  • the structured information extraction apparatus 500 of this embodiment may include: an extraction module 501 , a detection module 502 and an aggregation module 503 .
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • the acquisition submodule 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.
  • 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.
  • 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.
  • 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.
  • 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 .
  • the I/O interface 605 includes: 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.
  • 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 .
  • 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.
  • the computer program 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.
  • 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.
  • FPGAs field programmable gate arrays
  • ASICs application specific integrated circuits
  • ASSPs application specific standard products
  • SOC system of systems
  • CPLD load programmable logic device
  • computer hardware firmware, software, and/or combinations thereof.
  • 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.
  • 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.
  • 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.
  • RAM random access memory
  • ROM read only memory
  • EPROM or flash memory erasable programmable read only memory
  • CD-ROM compact disk read only memory
  • magnetic storage or any suitable combination of the foregoing.
  • 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.
  • a display device e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor
  • a keyboard and pointing device eg, a mouse or a trackball
  • 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.
  • steps may be reordered, added or deleted using the various forms of flow shown above.
  • 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.

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Abstract

La présente invention concerne un procédé et un appareil d'extraction d'informations structurées, un dispositif, un support de stockage et un produit-programme, et concerne le domaine de l'intelligence artificielle, et plus particulièrement les domaines de la vision artificielle et de l'apprentissage profond. Un mode de réalisation spécifique comprend : l'extraction d'une image vidéo d'événement sportif cible à partir d'une vidéo d'événement sportif ; la réalisation d'une détection de cible sur l'image vidéo d'événement sportif cible pour obtenir des informations cibles désignées dans l'événement sportif ; et l'agrégation des informations cibles désignées pour obtenir des informations structurées d'événement sportif. La présente invention peut extraire efficacement des informations clé à partir d'une vidéo d'événement sportif, former des données structurées, fournir un contenu de haute qualité pour le résumé d'événement sportif, et aider à achever la création de contenu rapide pour des événements sportifs.
PCT/CN2022/096180 2021-07-23 2022-05-31 Procédé et appareil d'extraction d'informations structurées, et dispositif et support de stockage WO2023000831A1 (fr)

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