CN108171160B - Task result identification method and device, storage medium and electronic equipment - Google Patents
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Abstract
The application provides a task result identification method and device, a storage medium and electronic equipment. The method comprises the following steps: sending the target task data to the client; carrying out image recognition on an image frame sent by a client, and recognizing target content data related to the target task data; and obtaining a completion result of the target task according to the matching degree of the target content data and the target task data. The aim is to reduce the cost of task result identification.
Description
Technical Field
The present application relates to the field of internet, and in particular, to a method and an apparatus for identifying a task result in live broadcast, a storage medium, and an electronic device.
Background
With the development of the internet live broadcast industry, the form of internet live broadcast is more and more, wherein game live broadcast is loved by vast users, and the task is a mode for guiding a main broadcast to present specified live broadcast content.
Disclosure of Invention
The application provides a task result identification method and device, a storage medium and electronic equipment. The aim is to reduce the cost of task result identification.
Specifically, the method is realized through the following technical scheme:
a method of task result identification, the method comprising:
sending the target task data to the client;
carrying out image recognition on an image frame sent by a client, and recognizing target content data related to the target task data;
and obtaining a completion result of the target task according to the matching degree of the target content data and the target task data.
In some examples, the targeted live content data includes any one of: action characteristic data and attribute data of the target key object;
the target key object comprises an anchor image or an avatar image.
In some examples, performing image recognition on an image frame sent by a client to identify target content data related to the target task data includes:
inputting an image frame sent by a client into a neural network model, and acquiring an output result of the neural network model;
acquiring target content data according to the output result;
the neural network model includes: a convolutional neural network model, a deep full convolutional neural network model, a cyclic neural network model, a full convolutional neural network model, and a deep convolutional neural network model.
In some examples, performing image recognition on an image frame sent by a client to identify target content data related to the target task data includes:
acquiring characteristic data according to the target task data;
according to the characteristic data, image recognition is carried out on the image frame sent by the client side, and a key image frame is obtained;
target content data related to the target task data is identified from the key image frames.
In some examples, the method is performed by a live server, the client being a primary client;
the target task is generated based on the anchor information and/or audience information of the online anchor of the anchor client;
the anchor information includes any one of: the method comprises the steps that the popularity value of the anchor, the completion condition of the historical tasks of the anchor, the identity information of the anchor, the subscribed information of the anchor, the shared information of the anchor, the live broadcast duration information of the anchor, the positioning information of an anchor client and the broadcast mode information of the anchor client are obtained;
the audience information includes at least any one of: viewer preference information, recorded information of a live broadcast watched by a viewer, identity information of the viewer, and gender information of the viewer.
In some examples, the method is performed by a live server, the client being a primary client;
after obtaining the completion result of the target task, the method comprises the following steps:
according to the result, the resources corresponding to the target task data are distributed to the corresponding audience client;
the corresponding viewer client is randomly generated, or determined by the anchor client, or preset.
A task result recognition apparatus comprising:
the sending module is used for sending the target task data to the client;
the processing module is used for carrying out image recognition on the image frame sent by the client and identifying target content data related to the target task data; and obtaining a completion result of the target task according to the matching degree of the target content data and the target task data.
An electronic device, comprising:
a processor; a memory for storing the processor-executable instructions;
wherein the processor is configured to perform the following operations:
sending the target task data to the client;
carrying out image recognition on an image frame sent by a client, and recognizing target content data related to the target task data;
and obtaining a completion result of the target task according to the matching degree of the target content data and the target task data.
A storage medium having stored thereon a computer program for execution by a processor to:
sending the target task data to the client;
carrying out image recognition on an image frame sent by a client, and recognizing target content data related to the target task data;
and obtaining a completion result of the target task according to the matching degree of the target content data and the target task data.
The method comprises the steps of sending target task data to a client; carrying out image recognition on an image frame sent by a client, and recognizing target content data related to the target task data; and obtaining a completion result of the target task according to the matching degree of the target content data and the target task data. Because the image frame can reflect the content data, the labor cost of the operation staff can be greatly liberated in an image identification mode.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.
FIG. 1 is a partial flow diagram of a method for identifying task results provided by an exemplary embodiment of the present application;
FIG. 2 is a diagram of a live scene shown in an exemplary embodiment of the present application;
FIG. 3 is a partial flow diagram illustrating another live task result recognition method according to an exemplary embodiment of the present application;
FIG. 4 is a partial flow diagram of another method for task result identification shown in an exemplary embodiment of the present application;
FIG. 5 is a schematic diagram illustrating an anchor client interface in accordance with an exemplary embodiment of the present application;
FIG. 6 is a partial flow diagram of another method for task result identification shown in an exemplary embodiment of the present application;
FIG. 7 is a schematic diagram of another anchor client interface shown in an exemplary embodiment of the present application;
FIG. 8 is a logical block diagram of an electronic device shown in an exemplary embodiment of the present application;
FIG. 9 is a logical block diagram of a task result recognition device according to an exemplary embodiment of the present application;
fig. 10 is a logic block diagram of another task result recognition device according to an exemplary embodiment of the present application.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. As used in this application and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It is to be understood that although the terms first, second, third, etc. may be used herein to describe various information, such information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of the present application. The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination", depending on the context.
Referring to fig. 1, a partial flowchart of a task result identification method according to an exemplary embodiment of the present application is shown, where partial steps are as follows:
s110: sending the target task data to the client;
s120: carrying out image recognition on an image frame sent by a client, and recognizing target content data related to the target task data;
s130: and obtaining a completion result of the target task according to the matching degree of the target content data and the target task data.
In some examples, the method may be applied to the fields of internet live broadcast, games, and the like, and the method may be executed by a server for internet live broadcast or games, where the "server" provided in this embodiment of the present application may be a server device, or may be a generic term of a server system, or may be at least one piece of software installed on the server device. The "client" proposed in the embodiments of the present application may be software running on an electronic device.
The "electronic device" proposed by the embodiments of the present application includes both a device with a wireless signal receiver, which is only a device with a wireless signal receiver without transmission capability, and a device with receiving and transmitting hardware, which is a device with receiving and transmitting hardware capable of two-way communication over a two-way communication link. Such a device may include: a cellular or other communication device having a single line display or a multi-line display or a cellular or other communication device without a multi-line display; PCS (Personal Communications Service), which may combine voice, data processing, facsimile and/or data communication capabilities; a PDA (Personal Digital Assistant), which may include a radio frequency receiver, a pager, internet/intranet access, a web browser, a notepad, a calendar and/or a GPS (Global Positioning System) receiver; a conventional laptop and/or palmtop computer or other device having and/or including a radio frequency receiver. As used herein, a "terminal" or "terminal device" may be portable, transportable, installed in a vehicle (aeronautical, maritime, and/or land-based), or situated and/or configured to operate locally and/or in a distributed fashion at any other location(s) on earth and/or in space. The "electronic Device" used herein may also be a communication terminal, a web terminal, a music/video playing terminal, such as a PDA, an MID (Mobile Internet Device) and/or a Mobile phone with music/video playing function, and may also be a smart tv, a set-top box, and the like.
The "target content data" provided in the embodiment of the present application may include motion characteristic data of target key objects in the image frame, such as singing and dancing, and may also include attribute data of the target key objects, such as identities and statuses (such as survival and death) of the target key objects; the target key object may be an anchor, a character, a virtual character, or the like in the image frame, and the virtual character may be hero in the game screen. For example, the target content data may be: the data of dance or singing of a host (target key object) in an image frame, the data of victory or death of a virtual character in a game, the data of the number of the target key objects in the image frame and the like. It is to be understood that the present application is not limited to the type of the target content data.
In some examples, in step S120, the target content data may be acquired from the image frame by using a machine learning technique; specifically, the image frame may be input into a neural network model, and an output result of the neural network model is obtained; acquiring target content data according to the output result; the neural network model is formed by sample training. The neural network model includes: a convolutional neural network model, a deep full convolutional neural network model, a cyclic neural network model, a full convolutional neural network model, a deep convolutional neural network model, and the like.
In some examples, in step S120, feature information may also be acquired according to the target task data, a target image frame may be acquired according to the feature information, and target content data may be acquired from the target image frame. For example, the target tasks are: the method comprises the steps of obtaining a win of a game, carrying out image recognition on an image frame, recognizing the type of the game according to the picture of the video image frame, calling the characteristic information corresponding to the win or loss of the game, considering the video image frame as a target image frame when the characteristic information exists in the image frame, and considering that the win of the game is obtained if the target content data recognized in the target image frame is the win. The present application does not limit the manner of image recognition.
Taking the method provided by the embodiment of the present application as an example for internet live broadcast, referring to fig. 2, which is an application scene schematic diagram of live broadcast in the embodiment of the present application, a first viewer client 211, a second viewer client 221, and an anchor client 231 are respectively installed on electronic devices 210, 220, and 230, and the anchor client 231 may call a camera to record a video, take a photo, or make a live video stream through other methods such as screen capture, and then send the live video stream to the server 200 through a network. The server 200 is configured to provide background services of internet live broadcast, for example, store a corresponding relationship between each anchor client and each viewer client, and distribute live broadcast video streams. When the first viewer client 211, the second viewer client 221 and the anchor client 231 are in the same live broadcast room, the video image frames produced by the anchor client 231 may be displayed on the interfaces of the first viewer client 211 and the second viewer client 221, and the video image frames may reflect live broadcast content. When the method provided by the embodiment of the application is applied to the field of internet live broadcast, the image frames can be called video image frames.
The 'live broadcast room' provided by the embodiment of the application refers to a social network platform, an instant messaging platform and the like which are aggregated by a plurality of users, the users enter the live broadcast room in a client logging mode, the users exist in the live broadcast room in the identity of members, and the members with various identities, such as audiences and anchor broadcasters and the like, are contained in the same live broadcast room. The user can log in or out of the live room at will. For users with certain rights (e.g., the anchor), they can add or delete live room members, and can also create or dismiss live rooms. Within the live room, any number of members may interact using chat (e.g., chat using pop-up messages), talk, video, or push electronic gifts. The "live room" may also be a tag that may be associated with the ID of the anchor.
The "anchor client" and "viewer client" may refer to software installed on an electronic device, and in some cases, the anchor client is integrated with the viewer client on one piece of software, which may be referred to as the anchor client when the identity of the user is anchor, and the viewer client when the identity of the user is viewer.
Referring to fig. 3, a partial flowchart of a live broadcasting method provided in an exemplary embodiment of the present application is shown, where the live broadcasting method may be executed by a server, and some steps are as follows:
s310: sending the target task data to the anchor client;
s320: carrying out image recognition on a video image frame sent by a main broadcasting client, and recognizing target content data related to the target task data;
s330: and obtaining a completion result of the target task according to the matching degree of the target content data and the target task data.
This application obtains the target content data in the live broadcast through image recognition's technique, can to a great extent liberation operation staff's human cost to can obtain the completion result of the target task of any form, greatly degree ground has richened the kind of task in the live broadcast, has increased the interest of live broadcast.
In some examples, the target task data may be generated based on the anchor information and/or audience information of the online anchor of the anchor client, and referring to fig. 4, which is a partial flowchart of another live broadcasting method provided by an exemplary embodiment of the present application, before step S310, step S410 may further be performed: target task data is generated based on the anchor information and/or audience information of the online anchor of the anchor client. In some examples, the anchor information may include at least any one of: historical live broadcast information of the anchor, popularity value of the anchor, completion condition of historical tasks of the anchor, identity information of the anchor, subscribed information of the anchor, shared information of the anchor, live broadcast duration information of the anchor, positioning information of an anchor client, broadcast mode information of the anchor client and the like; the live broadcast has many forms of positioning, and the positioning information of the anchor client can be the live broadcast form positioning of the anchor client, such as talent show, game live broadcast, outdoor live broadcast and the like. The audience information may include at least any one of: the information of the preference of the audience, the recorded information of the live broadcast watched by the audience, the identity information of the audience, the sex information of the audience and the like.
In some examples, task data may be generated based on audience information, and target task data may be selected from the task data based on anchor information. Because the audience information can reflect the preference of the audience, the task data generated according to the audience information can guide the anchor to execute the favorite behaviors of the audience or produce the direct broadcast content popular with the audience, and then the target task data suitable for the anchor can be selected from the task data according to the anchor data so as to ensure the reasonability of the task distribution. For example, a plurality of task data are generated according to audience information, a task one, namely ' dancing a dance a in live broadcasting today ' and a task two, namely winning a game c by using a role b today ', and according to the anchor information of an online anchor, such as the anchor history live broadcasting information, if the anchor is a game anchor, the task two can be distributed to the anchor; of course, the target task can also be allocated to the anchor according to the location information of the anchor, and if the anchor is located in the category of songs and dances, the task can be allocated to the anchor.
In some examples, the target task may be displayed on an interface of the anchor client or may be displayed on an interface of the corresponding viewer client; in some examples, the task may be presented on the viewer client's interface in response to a selection by the anchor, such as: when the target task is displayed on the interface of the anchor client, a selection control can be displayed, when the anchor clicks the selection control, an instruction is sent to the server, and after receiving the instruction, the server sends the target task data to the corresponding audience client. In some examples, the anchor may choose to display the target task on the viewer client's interface once every ten minutes. For example, referring to fig. 5, which is an interface schematic diagram of an anchor client shown in an exemplary embodiment of the present application, the anchor client runs on an electronic device 510, an interface 520 may show target task data 521 sent by a server, and may also show a control 523 "show a target task at a viewer client", where when the anchor clicks the control, the target task data may be shown on an interface of a corresponding viewer client. The display mode can be dynamic display or static display. The dynamic presentation may be a scrolling presentation. The associated client may be a chairman-designated viewer client of the chairman client or all viewer clients within the live room.
Referring to fig. 6, to further increase interactivity, in some examples, after step S330, step S340 may be performed: and according to the result, the resources corresponding to the target task data are distributed to the corresponding audience client. The corresponding viewer client is randomly generated, or determined by the anchor client, or preset. The determination by the anchor client may be: after the anchor completes the task, the anchor can distribute the resource corresponding to the target task to the audience selected by the anchor client; the pre-reservation may be that after the anchor completes the task, the resource corresponding to the target task is issued to any audience in the live broadcast room, so as to increase the enthusiasm of audience participation in the live broadcast room. Referring to fig. 7, which is a schematic diagram illustrating an anchor client interface according to an exemplary embodiment of the present application, the anchor client runs on an electronic device 510, the interface 520 may show target task data 521 sent by a server, and when a target task is completed, a "release reward" control 522 may be shown on the interface, so that a corresponding viewer client obtains a resource corresponding to the target task. After the anchor completes the task, the resource corresponding to the task is distributed to the audience, so that an interactive mode of 'anchor → audience' is formed, and the interest and the interactivity of live broadcast are increased.
In some examples, when the resource corresponding to the target task data is issued to the corresponding viewer client, information of the viewer client obtaining the corresponding resource may be displayed in the live broadcast.
Corresponding to the embodiment of the task result identification method, the application also provides an embodiment of the task result identification device.
The embodiment of the task result identification device can be applied to electronic equipment. The device embodiments may be implemented by software, or by hardware, or by a combination of hardware and software. Taking a software implementation as an example, as a logical device, the device is formed by reading, by a processor of the electronic device where the device is located, a corresponding computer program instruction in the nonvolatile memory into the memory for operation. From a hardware aspect, as shown in fig. 8, the hardware structure diagram of the electronic device where the task result identification apparatus is located in the present application is shown, except for the processor, the memory, the network interface, and the nonvolatile memory shown in fig. 8, the electronic device where the apparatus is located in the embodiment may also include other hardware generally according to the actual function of the task result identification apparatus, which is not described again. Referring to fig. 8, the present application further discloses an electronic device, including: a memory storing processor-executable instructions; wherein the processor is coupled to the memory for reading program instructions stored by the memory and, in response, performing the following:
sending the target task data to the client;
carrying out image recognition on an image frame sent by a client, and recognizing target content data related to the target task data;
and obtaining a completion result of the target task according to the matching degree of the target content data and the target task data.
Referring to fig. 9, a task result recognition apparatus 900 disclosed for the present application includes:
a sending module 910, configured to send target task data to a client;
the processing module 920 is configured to perform image recognition on an image frame sent by a client, and identify target content data related to the target task data; and obtaining a completion result of the target task according to the matching degree of the target content data and the target task data.
In some examples, the target content data includes: behavior data of target key objects in the image frame.
In some examples, the processing module 920 performs image recognition on an image frame sent by a client to identify target content data related to the target task data, and the processing module 920 may also be configured to input the image frame sent by the client into a neural network model to obtain an output result of the neural network model;
acquiring target content data according to the output result;
the neural network model includes: a convolutional neural network model, a deep full convolutional neural network model, a cyclic neural network model, a full convolutional neural network model, and a deep convolutional neural network model.
In some examples, the processing module 920 performs image recognition on an image frame sent by a client to identify target content data related to the target task data, and the processing module 920 may further be configured to obtain feature data according to the target task data;
according to the characteristic data, image recognition is carried out on the image frame sent by the client side, and a key image frame is obtained;
target content data related to the target task data is identified from the key image frames.
Referring to fig. 10, in some examples, the client may be an anchor client; the apparatus 900 further comprises a task generation module 930 for generating target task data based on the anchor information and/or audience information of the online anchor of the anchor client;
the anchor information includes any one of: the method comprises the steps that the popularity value of the anchor, the completion condition of the historical tasks of the anchor, the identity information of the anchor, the subscribed information of the anchor, the shared information of the anchor, the live broadcast duration information of the anchor, the positioning information of an anchor client and the broadcast mode information of the anchor client are obtained;
the audience information includes at least any one of: viewer preference information, recorded information of a live broadcast watched by a viewer, identity information of the viewer, and gender information of the viewer.
In some examples, the client may be an anchor client; after the processing module 920 obtains the completion result of the target task, the processing module 920 is configured to, according to the result, issue the resource corresponding to the target task data to the corresponding viewer client;
the corresponding viewer client is randomly generated, or determined by the anchor client, or preset.
Embodiments of the present application may take the form of a computer program product embodied on one or more storage media including, but not limited to, disk storage, CD-ROM, optical storage, and the like, in which program code is embodied. Computer-usable storage media include permanent and non-permanent, removable and non-removable media, and information storage may be implemented by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of the storage medium of the computer include, but are not limited to: phase change memory (PRAM), Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), Read Only Memory (ROM), Electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technologies, compact disc read only memory (CD-ROM), Digital Versatile Discs (DVD) or other optical storage, magnetic tape storage or other magnetic storage devices, or any other non-transmission medium, may be used to store information that may be accessed by a computing device.
Other embodiments of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the invention following, in general, the principles of the application and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.
It will be understood that the present application is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.
The above description is only exemplary of the present application and should not be taken as limiting the present application, as any modification, equivalent replacement, or improvement made within the spirit and principle of the present application should be included in the scope of protection of the present application.
Claims (10)
1. A task result identification method is applied to a server side, and is characterized by comprising the following steps:
sending the target task data to the anchor client;
carrying out image recognition on an image frame sent by a main broadcasting client, and recognizing target content data related to the target task data;
and obtaining a completion result of the target task according to the matching degree of the target content data and the target task data.
2. The method of claim 1, wherein the target live content data comprises any one of: action characteristic data and attribute data of the target key object;
the target key object comprises an anchor image or an avatar image.
3. The method of claim 1, wherein performing image recognition on an image frame sent by a client to identify target content data related to the target task data comprises:
inputting an image frame sent by a client into a neural network model, and acquiring an output result of the neural network model;
acquiring target content data according to the output result;
the neural network model includes any one of: a convolutional neural network model, a deep full convolutional neural network model, a cyclic neural network model, a full convolutional neural network model, and a deep convolutional neural network model.
4. The method of claim 1, wherein performing image recognition on an image frame sent by a client to identify target content data related to the target task data comprises:
acquiring characteristic data according to the target task data;
according to the characteristic data, image recognition is carried out on the image frame sent by the client side, and a key image frame is obtained;
target content data related to the target task data is identified from the key image frames.
5. The method of claim 1,
the target task is generated based on the anchor information and/or audience information of the online anchor of the anchor client;
the anchor information includes at least any one of: the method comprises the steps that the popularity value of the anchor, the completion condition of the historical tasks of the anchor, the identity information of the anchor, the subscribed information of the anchor, the shared information of the anchor, the live broadcast duration information of the anchor, the positioning information of an anchor client and the broadcast mode information of the anchor client are obtained;
the audience information includes at least any one of: viewer preference information, recorded information of a live broadcast watched by a viewer, identity information of the viewer, and gender information of the viewer.
6. The method of claim 1,
after obtaining the completion result of the target task, the method comprises the following steps:
according to the result, the resources corresponding to the target task data are distributed to the corresponding audience client;
the corresponding viewer client is randomly generated, or determined by the anchor client, or preset.
7. A task result recognition device is applied to a server side and is characterized by comprising:
the sending module is used for sending the target task data to the anchor client;
the processing module is used for carrying out image recognition on the image frame sent by the anchor client and identifying target content data related to the target task data; and obtaining a completion result of the target task according to the matching degree of the target content data and the target task data.
8. The apparatus of claim 7, further comprising:
the task generating module is used for generating target task data based on the anchor information and/or audience information of the online anchor of the anchor client;
the anchor information includes any one of: the method comprises the steps that the popularity value of the anchor, the completion condition of the historical tasks of the anchor, the identity information of the anchor, the subscribed information of the anchor, the shared information of the anchor, the live broadcast duration information of the anchor, the positioning information of an anchor client and the broadcast mode information of the anchor client are obtained;
the audience information includes at least any one of: viewer preference information, recorded information of a live broadcast watched by a viewer, identity information of the viewer, and gender information of the viewer.
9. An electronic device, comprising:
a processor; a memory for storing the processor-executable instructions;
wherein the processor is configured to perform the following operations:
sending the target task data to the anchor client;
carrying out image recognition on an image frame sent by a main broadcasting client, and recognizing target content data related to the target task data;
and obtaining a completion result of the target task according to the matching degree of the target content data and the target task data.
10. A storage medium having a computer program stored thereon, the program being executable by a processor to perform operations comprising:
sending the target task data to the anchor client;
carrying out image recognition on an image frame sent by a main broadcasting client, and recognizing target content data related to the target task data;
and obtaining a completion result of the target task according to the matching degree of the target content data and the target task data.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711448937.5A CN108171160B (en) | 2017-12-27 | 2017-12-27 | Task result identification method and device, storage medium and electronic equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711448937.5A CN108171160B (en) | 2017-12-27 | 2017-12-27 | Task result identification method and device, storage medium and electronic equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108171160A CN108171160A (en) | 2018-06-15 |
| CN108171160B true CN108171160B (en) | 2021-03-23 |
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| CN109446349B (en) * | 2018-09-28 | 2021-02-23 | 阿里巴巴（中国）有限公司 | Multimedia content auditing method and device |
| CN109286822A (en) * | 2018-10-19 | 2019-01-29 | 广州虎牙科技有限公司 | Interactive approach, device, equipment and storage medium based on live video identification |
| CN109561348B (en) * | 2018-12-27 | 2021-12-07 | 广州虎牙信息科技有限公司 | Service processing method, device, equipment and storage medium based on live broadcast |
| CN112307299A (en) * | 2019-08-20 | 2021-02-02 | 北京字节跳动网络技术有限公司 | Information publishing method and device, computer equipment and storage medium |
| CN111757131B (en) * | 2020-04-03 | 2021-06-11 | 北京达佳互联信息技术有限公司 | Task target setting method, device and system applied to live broadcast and electronic equipment |
| CN114245223B (en) * | 2022-01-27 | 2023-06-13 | 广州方硅信息技术有限公司 | Live broadcasting room task loading method, system, device and computer equipment |
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