WO2021129530A1 - Procédé et appareil d'affichage d'élément virtuel, dispositif informatique et support de stockage - Google Patents

Procédé et appareil d'affichage d'élément virtuel, dispositif informatique et support de stockage Download PDF

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Publication number
WO2021129530A1
WO2021129530A1 PCT/CN2020/137512 CN2020137512W WO2021129530A1 WO 2021129530 A1 WO2021129530 A1 WO 2021129530A1 CN 2020137512 W CN2020137512 W CN 2020137512W WO 2021129530 A1 WO2021129530 A1 WO 2021129530A1
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Prior art keywords
gene
behavior
fitness
display
virtual item
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PCT/CN2020/137512
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English (en)
Chinese (zh)
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杨键
林麟
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百果园技术(新加坡)有限公司
杨键
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Publication of WO2021129530A1 publication Critical patent/WO2021129530A1/fr

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/47—End-user applications
    • H04N21/478—Supplemental services, e.g. displaying phone caller identification, shopping application
    • H04N21/4788—Supplemental services, e.g. displaying phone caller identification, shopping application communicating with other users, e.g. chatting
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
    • H04N21/431—Generation of visual interfaces for content selection or interaction; Content or additional data rendering
    • H04N21/4312—Generation of visual interfaces for content selection or interaction; Content or additional data rendering involving specific graphical features, e.g. screen layout, special fonts or colors, blinking icons, highlights or animations
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
    • H04N21/442—Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk
    • H04N21/44204—Monitoring of content usage, e.g. the number of times a movie has been viewed, copied or the amount which has been watched
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
    • H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
    • H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
    • H04N21/442—Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk
    • H04N21/44213—Monitoring of end-user related data
    • H04N21/44218—Detecting physical presence or behaviour of the user, e.g. using sensors to detect if the user is leaving the room or changes his face expression during a TV program

Definitions

  • the embodiments of the present application relate to live broadcast technology, such as a method, device, computer equipment, and storage medium for displaying virtual items.
  • the live broadcast is usually hosted by the host user.
  • the viewer user can usually send virtual items. This behavior can be referred to as giving gifts and rewarding the host.
  • the code to implement the animation special effects is usually less, resulting in fewer forms of animation special effects. If you want to make changes to the animation special effects, you often need to release a new version of the application However, the iteration efficiency of the version is low, resulting in a relatively single form of animation special effects.
  • the embodiments of the present application provide a method, device, computer device, and storage medium for displaying virtual items, so as to avoid the situation that the form of playing the animation special effects of virtual items in a live broadcast scene is relatively single.
  • an embodiment of the present application provides a method for displaying virtual items, including:
  • an embodiment of the present application also provides a virtual item display device, including:
  • the live room display module is set to display the live room of the host user
  • a virtual item determining module configured to determine the virtual item received by the anchor user
  • a live broadcast feature determination module configured to determine the live broadcast feature associated with the virtual item
  • a display behavior matching module configured to determine a display behavior matching the virtual item according to the live broadcast feature
  • the display behavior execution module is configured to execute the display behavior on the virtual item in the live broadcast room.
  • an embodiment of the present application also provides a computer device, and the computer device includes:
  • At least one processor At least one processor
  • Memory set to store at least one program
  • the at least one processor When the at least one program is executed by the at least one processor, the at least one processor implements the method for displaying virtual items as described in the first aspect.
  • the embodiments of the present application also provide a computer-readable storage medium having a computer program stored on the computer-readable storage medium.
  • the computer program is executed by a processor, the virtual machine described in the first aspect is implemented. How to display items.
  • FIG. 1 is a flowchart of a method for displaying virtual items according to Embodiment 1 of this application;
  • FIG. 2 is a flowchart of a method for displaying virtual items provided in the second embodiment of the present application
  • FIG. 3 is a schematic diagram of nodes of a behavior tree provided in Embodiment 2 of the present application.
  • FIG. 4 is an example diagram of a behavior tree provided in Embodiment 2 of the present application.
  • FIG. 5 is a schematic structural diagram of a display device for virtual items provided in the third embodiment of the application.
  • FIG. 6 is a schematic structural diagram of a computer device provided in Embodiment 4 of this application.
  • FIG. 1 is a flowchart of a method for displaying virtual items provided in the first embodiment of the application. This embodiment is applicable to the case of adaptively selecting the way of displaying virtual items.
  • the method can be executed by a display device of virtual items.
  • the display device of the virtual item can be implemented by software and/or hardware, and can be configured in a computer device, for example, a personal computer, a mobile terminal (such as a mobile phone, a tablet computer, etc.), a wearable device (such as a smart watch, etc.), etc.
  • the method includes step S101 to step S105.
  • operating systems such as Android (Android), IOS, Windows, etc.
  • applications that support live broadcast such as independent live broadcast applications, short video applications, download tools, instant messaging tools, etc.
  • the page provided by the live broadcast platform is loaded, the live broadcast room is displayed on the page, and the live broadcast program hosted by the host user is displayed in the live broadcast room.
  • the anchor user can be represented by a user identifier, such as a user ID, user account, and so on.
  • the virtual item received by the host user is determined.
  • the live broadcast platform provides one or more virtual items, such as light sticks, hot pot, books, rockets, etc., which can be displayed in the live broadcast room.
  • virtual items such as light sticks, hot pot, books, rockets, etc.
  • a certain application in the live broadcast room When a certain application in the live broadcast room receives a virtual item sending operation from a viewer user, it notifies the live broadcast platform, and the live broadcast platform verifies the legitimacy of the viewer user. When the legitimacy verification is passed, the virtual item is sent to The host user, and notify all applications that log in to the live broadcast room to display the virtual item locally.
  • the application program installed in the current computer device may be an application program that initiates the behavior of sending virtual items, and other applications except the application program that initiates the behavior of sending virtual items, which is not limited in this embodiment.
  • live broadcast platforms generally provide membership services. Therefore, viewer users who send virtual items to anchor users are usually registered users in the live broadcast platform.
  • the virtual items provided by the live broadcast platform are generally equipped with the value of virtual tokens. , The value can be 0 (that is, free) or other values.
  • the live broadcast platform deducts the price of the virtual item from the viewer user’s account.
  • the live broadcast feature associated with the virtual item is determined.
  • the application program may receive the live broadcast feature associated with the virtual item sent by the live broadcast platform, that is, the feature associated with the virtual item in the live broadcast.
  • the live broadcast feature includes at least one of the feature of the host user, the feature of the viewer user, and the interaction feature between the host user and the viewer user.
  • the characteristics of the host user are information that can be reflected in the live broadcast room and the characteristics of the host user.
  • the characteristics of the anchor user include:
  • the offline characteristics of the anchor user are the characteristics of the anchor user during the non-live broadcast time, such as registration time, average active time, historical start time, number of followers, total revenue, and so on.
  • the real-time characteristics of the host user are the characteristics of the host user during the live broadcast time, for example, real-time popularity, gender, country, language, live broadcast type, and so on.
  • the characteristics of the audience user are information that can be reflected in the live broadcast room and the characteristics of the audience user.
  • the live broadcast characteristics of the viewer user include:
  • the offline characteristics of the audience user are the characteristics of the audience user during the non-live broadcast time, such as the average viewing time, the total number of historical gifts, and so on.
  • the real-time characteristics of the audience user are the characteristics of the audience user during the live broadcast time, for example, online duration, gender, country, language, and so on.
  • the interactive feature between the host user and the viewer user is information that can reflect the feature of the host user's interaction with the viewer user when the host user hosts a live program.
  • the viewer user's historical viewing time for the host user For example, the viewer user's historical viewing time for the host user, the total number of virtual items gifted by the viewer user history to the host user, whether the viewer user pays attention to the host user, and so on.
  • a display behavior matching the virtual item is determined according to the live broadcast feature.
  • the application program provides multiple independent display behaviors for virtual items, and each display behavior has a specific style, and the virtual item can be displayed according to the style.
  • the display behavior includes “running in a circle”, “calling to speak”, “delaying response for n seconds”, and so on.
  • the live broadcast feature after determining the live broadcast feature related to the virtual item, the live broadcast feature may be used as a filtering condition, and at least one suitable display behavior can be selected from all the display behaviors as the current display behavior for displaying the virtual item.
  • the live broadcast platform can deliver different combinations of display behaviors for different applications. For example, the live broadcast platform delivers 1 display behavior to an application, and the live broadcast platform delivers 2 to another application. Display behavior, the live broadcast platform sends 3 display behaviors to another application, etc. Therefore, in different applications, you can choose different display behaviors, and the same virtual item may have different display behaviors in different applications. Style to display.
  • the virtual item is displayed in the live broadcast room.
  • the display behavior can be performed on the virtual item in the live broadcast room, so as to display the virtual item according to the style specified by the display behavior, so as to realize the sending of the virtual item to the host user.
  • the live broadcast room of the host user is displayed, the virtual items received by the host user are determined, the live broadcast feature associated with the virtual item is determined, and the display behavior matching the virtual item is determined according to the live broadcast feature.
  • Perform display behaviors by pre-defining the display behaviors of virtual items and matching them with live broadcast characteristics, realize the intelligent control of adaptive selection of display behaviors according to the characteristics of live broadcasts, frame the selection of display behaviors, and do not need to display the code of virtual items
  • the display behaviors in the framework can be fixed and updated, with low coupling and strong scalability, which not only greatly enriches the ways of displaying virtual items, but also reduces the workload of application development.
  • FIG. 2 is a flowchart of a method for displaying virtual items provided in the second embodiment of the application. This embodiment is based on the foregoing embodiment and is refined, and the genetic algorithm (Genetic Algorithm, GA) is used to screen and display behaviors and pass behaviors.
  • the tree executes the processing operation of the display behavior, and the method includes step S201 to step S211.
  • the live broadcast feature associated with the virtual item is determined.
  • the behavior tree is determined.
  • a behavior tree (Behavior Tree) is set in advance for each type of virtual item in the application, and the behavior tree has a root node (root) and a control node (the control node is "control" and its child nodes).
  • the child node can be a leaf node, that is, a behavior node, or a control node.
  • execution control node is to execute its defined control logic
  • the behavior node represents a display behavior.
  • this embodiment can also set the display behavior through a finite state machine (Finite-state machine, FSM), which is not limited in this embodiment.
  • FSM Finite-state machine
  • the behavior tree is through a tree structure. Every time it is updated, it starts from the root node of the tree, and confirms the state switch to be operated and the actual action according to the type and state of the child node.
  • each node has an execution state, and after each execution is completed, the execution result is passed to the parent node. Coupled with various internal special nodes, artificial intelligence (AI) with certain complex behaviors can be realized.
  • AI artificial intelligence
  • the behavior tree sets some special nodes on the basis of the base node (BaseNode) (that is, the root node). These special nodes are used to assemble logic.
  • the design of these special nodes is as follows:
  • Action node Define a specific behavior by inheriting it; for example, for display behavior, it can be "patrol”, “received”, “escape”, etc.;
  • Composite node By inheriting it, it can organize a group of behaviors and determine the branch direction. For example, Sequence (Sequence, executes all its child nodes in sequence, that is, after the current one returns to the "complete" state, then run the next one Child node), selection (Selector, select one of its child nodes to execute), parallel (Parallel, run all of its child nodes once), etc.;
  • Decorator By inheriting it, define a constraint that acts on the behavior; for example, execute NUM (NUM is a custom variable and a positive integer) second child node, change the return state of the child node, etc.;
  • Condition node By inheriting it, define a condition for returning success or failure; for example, judging the popularity of the anchor user, judging the current blood volume, and so on.
  • a behavior tree is configured to achieve the desired intelligent effect.
  • behavior nodes in the behavior tree can be defined according to the actual situation.
  • sequential nodes, selection nodes, and parallel nodes are control nodes, behavior A, behavior B , Behavior C, Behavior D, Behavior E, Behavior F, and Behavior G belong to behavior nodes.
  • Behavior nodes are predefined display behaviors that display virtual items. For example, virtual items execute display logic in circles, and virtual items execute calling and speaking The display logic of the virtual item, the display logic of the virtual item's response delay for n seconds, and so on.
  • At least one gene is determined, and each of the genes represents at least one manifestation behavior.
  • the viewer user When the viewer user sends a virtual item to the anchor user, it is necessary to decide the display behavior performed by the current virtual item. At this time, the behavior tree is searched from top to bottom to determine the behavior node (display behavior) and execute it. Through this characteristic design, the decision logic is visualized, the control node can be reused, and the logic and realization of low coupling.
  • the extended and inherited display behaviors can be exchanged with each other. Therefore, after the logic of the behavior tree is edited in product planning, an optimal solution for intelligent display of virtual items can be obtained.
  • genetic algorithm iteration is used to obtain an optimal behavior tree. Compared with traditional logic implementation or state machine implementation, it can clearly organize behavioral decision-making, reduce the amount of program development, give product design to product personnel to think, what you see is what you get, and get the optimal solution, thereby optimizing products and improving product quality .
  • Genetic algorithm is a computational model that simulates the biological evolution process of natural selection and genetic mechanism of biological evolution theory. It is a method of searching for the optimal solution by simulating the natural evolution process.
  • a genetic algorithm is used to search for the display behavior that best matches the live broadcast feature.
  • the genetic algorithm can be used to encode display behaviors, such as binary encoding, floating-point encoding, symbol encoding, etc. That is, the object of genetic algorithm is the symbol string that represents the display behavior.
  • the genetic algorithm is an evolutionary operation on the population. You can prepare some initial population data representing the initial search point by random setting and other methods.
  • At least one performance of the display behavior can be randomly generated in the combination form, and display
  • Each performance of the behavior is used as a gene of the initial population, and each performance of the display behavior includes at least one display behavior, that is, each gene is used to represent at least one display behavior.
  • a live broadcast platform delivers a combination of two display behaviors to an application, and let one display behavior x 1 ⁇ 1,2,3,4,5,6,7 ⁇ , and the other display behavior x 2 ⁇ 1, 2, 3, 4, 5, 6, 7 ⁇ , the display behaviors x 1 and x 2 are encoded as a symbol string.
  • the display behaviors x 1 and x 2 can be represented by 3-bit unsigned binary integers respectively, and the 6-bit unsigned binary number formed by connecting them together forms an individual Gene represents a feasible solution.
  • the performance x of the display behavior and the gene X can be converted mutually through encoding and decoding.
  • the size of the population size is taken as 4, that is, the population is composed of 4 individuals, and each individual can be generated by a random setting method, such as: 011101, 101011, 011100, 111001.
  • the fitness of at least one current gene is calculated based on the live broadcast feature.
  • the genetic algorithm uses the size of individual fitness to evaluate the pros and cons of each individual, thereby determining the size of their genetic opportunities.
  • the live broadcast feature is used as a condition for gene screening, and the live broadcast feature is used for design to calculate the fitness of the gene.
  • a genetic algorithm usually requires multiple genetic operations, that is, multiple iterations. In each iteration, genes may change, and fitness is calculated for the genes of the current iteration.
  • the live broadcast feature includes the first number of times each current gene is used within a preset time period, and the audience user expresses positive emotions (such as likes, support, flowers, etc.) when the virtual item is displayed.
  • the second time the weight of the positive emotion (can be set as the total number of viewer users in the current live broadcast room multiplied by a coefficient, such as 0.1), and the revenue value of each current gene is used within a preset time period.
  • calculate the first ratio between the first number of times and the preset time period calculate the second ratio between the second number of times and the weight of positive emotions, and calculate the revenue value and the preset time period
  • calculate the first ratio calculate the sum of the second ratio and the third ratio, as the fitness of at least one current gene.
  • the above method of calculating fitness is just an example.
  • other methods of calculating fitness can be set according to the actual situation. For example, if the staying situation of viewers is inclined, the per capita viewing time and per capita attention rate will be increased. Such live broadcast features, if the revenue of the anchor user is inclined, can increase the live broadcast features such as the per capita gift of virtual items and the consumption of virtual tokens by the viewer user, and so on. This embodiment does not impose restrictions on this.
  • those skilled in the art can also use other methods of calculating fitness according to actual needs, and this embodiment does not limit this.
  • S207 it is determined whether the fitness of the at least one current gene meets the preset stopping condition; in the case that the fitness of the at least one current gene meets the preset stopping condition, S208 is executed, and the If the fitness of at least one current gene does not meet the preset stopping condition, S209 is executed.
  • a stopping condition for inheritance can be set in advance. If the stopping condition is met, the inheritance is stopped and a suitable gene is selected, and if the stopping condition is not met, the gene is continued to be inherited.
  • the stopping condition includes that the third number of iterations of at least one current gene reaches a preset first threshold, and the maximum value of the current fitness of at least one gene reaches a preset second threshold.
  • the third number of iterations of at least one current gene is counted, and the third number of iterations of at least one current gene is compared with a preset first threshold, or the current at least one The maximum value of the fitness of the gene is compared with the preset second threshold.
  • stopping conditions are just examples.
  • other stopping conditions can be set according to the actual situation, for example, the iteration time exceeds a preset threshold, and the difference between the maximum fitness value in every two iterations Less than a preset threshold, and so on.
  • This embodiment does not impose restrictions on this.
  • those skilled in the art can also adopt other stopping conditions according to actual needs, and this embodiment does not limit this.
  • one gene of the at least one current gene is selected according to the fitness of the at least one current gene, and the at least one display behavior represented by the one gene is used as the display behavior matching the virtual item.
  • the gene with the largest fitness value is selected, and the display behavior represented by it is used as the display behavior matching the virtual item.
  • the fitness of the at least one current gene is sorted in descending order according to the fitness value, and at least one display behavior represented by the gene associated with the fitness in the first position is selected as the matching virtual item Show behavior.
  • At least one of a selection operation, a crossover operation, and a mutation operation is performed on the at least one current gene to obtain at least one new gene, and the execution of S206 is returned.
  • the gene of the current iteration As the gene of the parent population, perform at least one of the selection operation, crossover operation and mutation operation on it, and inherit part or all of the gene in the parent to the gene of the offspring population, continue Iterate.
  • selection operation can be executed individually or in combination. When combined, they can be executed serially or in parallel, etc., which is not limited in this embodiment.
  • a combination of genetic operations is performed serially, a selection operation is performed on the at least one current gene, a crossover operation is performed on the gene after the selection operation, and a mutation operation is performed on the gene after the crossover operation to obtain at least one new gene. gene.
  • the genetic operation includes at least one of a selection operation, a crossover operation, and a mutation operation.
  • the selection operation (or copy operation) is used to determine how to select individuals from the parent population in a certain way so that they can be inherited into the offspring population.
  • the selection operation inherits the higher fitness individuals in the current parent population into the offspring population according to a certain rule or model, and the higher fitness individuals will have more chances to inherit to the next generation.
  • the probability of selecting the at least one current gene is calculated based on the fitness of the at least one current gene, and the probability is positively correlated with the fitness of the at least one current gene, that is, the higher the fitness, The greater the probability, on the contrary, the lower the fitness, the smaller the probability.
  • x i and x j are genes
  • f() is the fitness of the genes
  • N is the total number of genes
  • i is the i-th gene
  • j is the j-th gene
  • P() is the probability of the gene.
  • the first value r ⁇ [0,1] is randomly generated as the third threshold.
  • At least one current gene From the at least one current gene, at least one gene whose probability of selecting a gene is greater than the third threshold is selected, and then the at least one gene is selected and inherited to the next generation.
  • the selection operations are as follows:
  • Crossover operation refers to the exchange of some genes between two paired individuals in a certain way to form two new individuals.
  • two current genes are selected as a pair of candidate genes, and a second value is generated for each pair of candidate genes as the crossover probability, where the second value is a random probability value greater than 0 and less than 1.
  • the crossover probability is greater than the preset fourth threshold (the fourth threshold P c ⁇ (0, 1)), then the data located after the designated crossover point in each pair of candidate genes are exchanged with each other.
  • the crossover operation is as follows:
  • the fitness of the newly generated individuals 111101 and 111011 after the crossover operation is higher than the fitness of the original two individuals.
  • Mutation operation refers to changing at least one data in an individual code string with a small probability to form a new individual.
  • the crossover operation and mutation operation cooperate with each other to jointly complete the global search and local search of the search space.
  • a third value is randomly generated for each current gene as the mutation probability.
  • the mutation probability of a gene is greater than the preset fifth threshold (the fifth threshold P m ⁇ (0, 0.2)), the data at the designated mutation point in the gene is changed.
  • the basic bit mutation operator refers to the mutation operation of a certain bit or a few genes randomly designated by an individual code string. For the individual represented by the binary code string, the original gene value is reversed. If the original gene value of a gene undergoing mutation operation is 0, it will be changed to 1; otherwise, if the original gene value is 1 , Then change it to 0.
  • the mutation operation is as follows:
  • the individual comfort level of No. 4 is 98, which exceeds 95 (the second threshold), and the combination of display behavior 7 and display behavior 2 can be selected.
  • a behavior node is executed to perform a display behavior on the virtual item in the live broadcast room.
  • the display behavior represented by the behavior node is executed, and the virtual items are displayed in the screen of the live room according to the style represented by the display behavior, so that the virtual items are sent to the anchor user.
  • a controller can be set in advance, and the controller has control nodes that match all the behavior nodes one by one.
  • the control node is the code that realizes the display behavior represented by the behavior node, and the coupling between the control nodes is low.
  • adjust the control nodes accordingly (such as adding or deleting), which can improve scalability.
  • a controller When determining the behavior node that matches the live broadcast feature, a controller may be determined, and the controller has a control node, and the control node configured for the behavior node is called to execute the behavior node.
  • the life cycle of the behavior tree ends.
  • the virtual item can be deleted in the live broadcast room to complete the delivery of the virtual item to the host user.
  • the display behavior is represented by the behavior node in the behavior tree, and the behavior node matching the live broadcast feature is searched from the behavior tree by genetic algorithm.
  • the behavior tree organizes complex display behaviors very intuitively.
  • the nodes in the network have high reusability and strong scalability, which greatly reduces the threshold and amount of application development.
  • the genetic algorithm is simple and can be implemented locally on computer equipment. Genetic algorithm provides fast and unrelated business. Random search capability makes it easy to search and display behaviors using live features as conditions. Genetic algorithms are scalable and easy to combine with behavior trees.
  • FIG. 5 is a schematic structural diagram of a virtual item display device provided in the third embodiment of the application.
  • the device may include the following modules:
  • the live room display module 501 is configured to display the live room of the host user.
  • the virtual item determining module 502 is configured to determine the virtual item received by the host user.
  • the live broadcast feature determination module 503 is configured to determine the live broadcast feature associated with the virtual item.
  • the display behavior matching module 504 is configured to determine a display behavior matching the virtual item according to the live broadcast feature.
  • the display behavior execution module 505 is configured to execute the display behavior on the virtual item in the live broadcast room.
  • the live broadcast feature determination module 503 includes:
  • a behavior tree determination sub-module set to determine a behavior tree, the behavior tree has a behavior node, and the behavior node represents a display behavior;
  • the gene determination sub-module is configured to determine at least one gene, and each gene represents at least one display behavior
  • the fitness calculation sub-module is set to calculate the fitness of at least one current gene based on the live broadcast feature
  • the stopping condition judgment submodule is configured to judge whether the fitness of the at least one current gene meets the preset stopping condition; when the fitness of the at least one current gene meets the preset stopping condition, call the display A behavior selection sub-module, when the fitness of the at least one current gene does not meet a preset stopping condition, call the genetic operation sub-module;
  • the display behavior selection submodule is configured to select one of the at least one current gene according to the fitness of the at least one current gene, and use the at least one display behavior represented by the one gene as the The display behavior of virtual item matching;
  • the genetic operation submodule is configured to perform at least one genetic operation among selection operations, crossover operations, and mutation operations on the at least one current gene to obtain at least one new gene, and return to call the fitness calculation submodule.
  • the live broadcast feature includes the first number of times each current gene is used within a preset time period, and the second time that the audience user expresses positive emotions when the virtual item is displayed. The number of times, the weight of the positive emotion, and the revenue value of using each current gene within a preset time period;
  • the fitness calculation sub-module includes:
  • a first ratio calculation unit configured to calculate a first ratio between the first number of times and the preset time period
  • a second ratio calculation unit configured to calculate a second ratio between the second number of times and the weight of the positive emotion
  • a third ratio calculation unit configured to calculate a third ratio between the revenue value and the preset time period
  • the sum calculation unit is configured to calculate the sum of the first ratio, the second ratio and the third ratio as the fitness of at least one current gene.
  • the stop condition judgment submodule includes:
  • the comparing unit is configured to compare the third number of iterations of the at least one current gene with a preset first threshold, and compare the maximum value of the fitness of the at least one current gene with the preset second threshold ;
  • the condition satisfaction determination unit is configured to determine that if the third number of times is greater than or equal to the first threshold, or the maximum value of the fitness of the at least one current gene is greater than or equal to the second threshold, then it is determined that the stop is satisfied. condition;
  • the condition unsatisfied determining unit is configured to determine that if the third number of times is less than the first threshold and the maximum value of the fitness of the at least one current gene is less than the second threshold, it is determined that the stopping condition is not met.
  • the genetic manipulation submodule includes:
  • a probability calculation unit configured to calculate a probability of selecting the at least one current gene based on the fitness of the at least one current gene, and the probability is positively correlated with the fitness of the at least one current gene;
  • the first value generating unit is configured to randomly generate the first value as the third threshold
  • the gene selection unit is configured to select at least one gene whose probability of a gene is greater than the third threshold value from the at least one current gene.
  • the probability calculation unit includes:
  • the total fitness calculation subunit is set to calculate the sum of all fitness of the at least one current gene as the total fitness
  • the fitness ratio calculation subunit is set to calculate a fourth ratio between the fitness of the gene and the total fitness for a certain gene, as the probability of selecting the gene.
  • the genetic manipulation submodule includes:
  • the candidate gene selection unit is set to select two current genes as a pair of candidate genes
  • a second value generating unit configured to generate a second value for each pair of candidate genes as a crossover probability
  • the data exchange unit is configured to exchange data located after the designated intersection in each pair of candidate genes if the crossover probability is greater than a preset fourth threshold.
  • the genetic manipulation submodule includes:
  • the third value generating unit is set to randomly generate a third value for each current gene as the mutation probability
  • the data changing unit is configured to change the data at the designated mutation point in the gene if the mutation probability of a certain gene is greater than the preset fifth threshold.
  • the genetic manipulation submodule includes:
  • a selection operation unit configured to perform a selection operation on the at least one current gene
  • the crossover operation unit is set to perform crossover operations on the genes after the selection operation
  • the mutation operation unit is set to perform mutation operation on the gene after the crossover operation to obtain at least one new gene.
  • the display behavior selection submodule includes:
  • a descending sorting unit configured to sort the fitness of the at least one current gene in descending order
  • the first selection unit is set to select at least one display behavior represented by the fitness-related gene in the first position as the display behavior matching the virtual item.
  • the display behavior is a behavior node in a behavior tree
  • the display behavior execution module 505 includes:
  • a behavior node execution submodule configured to execute the behavior node, so as to perform the display behavior on the virtual item in the live broadcast room;
  • the display end submodule is set to end the behavior tree if the execution is completed, and delete the virtual item in the live broadcast room.
  • the behavior node execution submodule includes:
  • the controller determining unit is configured to determine the controller, and the controller has a control node;
  • the control node invoking unit is configured to invoke the control node configured on the behavior node to execute the behavior node.
  • the virtual item display device provided in the embodiment of the present application can execute the virtual item display method provided in any embodiment of the present application, and has a function module corresponding to the execution method.
  • FIG. 6 is a schematic structural diagram of a computer device provided in Embodiment 4 of this application.
  • the computer device includes a processor 600, a memory 601, a communication module 602, an input device 603, and an output device 604; the number of processors 600 in the computer device may be at least one.
  • one processor 600 is used.
  • the processor 600, the memory 601, the communication module 602, the input device 603, and the output device 604 in the computer equipment may be connected by a bus or other means. In FIG. 6, the connection by a bus is taken as an example.
  • the memory 601 can be configured to store software programs, computer-executable programs, and modules, such as the modules corresponding to the virtual item display method in this embodiment (for example, the virtual item shown in FIG. 5).
  • the processor 600 executes various functional applications and data processing of the computer device by running the software programs, instructions, and modules stored in the memory 601, that is, realizes the above-mentioned method for displaying virtual items.
  • the memory 601 may mainly include a program storage area and a data storage area.
  • the program storage area may store an operating system and an application program required by at least one function; the data storage area may store data created according to the use of a computer device.
  • the memory 601 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices.
  • the memory 601 may include a memory remotely provided with respect to the processor 600, and these remote memories may be connected to a computer device through a network. Examples of the aforementioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.
  • the communication module 602 is configured to establish a connection with the display screen and realize data interaction with the display screen.
  • the input device 603 can be configured to receive input digital or character information, and generate key signal input related to user settings and function control of the computer equipment, and can also be a camera configured to obtain images and a sound pickup device to obtain audio data.
  • the output device 604 may include audio equipment such as a speaker.
  • composition of the input device 603 and the output device 604 can be set according to actual conditions.
  • the processor 600 executes various functional applications and data processing of the device by running software programs, instructions, and modules stored in the memory 601, that is, realizes the above-mentioned connection node control method of the electronic whiteboard.
  • the computer device provided in this embodiment can execute the virtual item display method provided in any embodiment of the present application, and has corresponding functions.
  • the fifth embodiment of the present application also provides a computer-readable storage medium on which a computer program is stored, and when the computer program is executed by a processor, a method for displaying virtual items is realized, the method includes:
  • the computer program of the computer-readable storage medium provided in the embodiment of the present application is not limited to the method operations described above, and may also perform related operations in the virtual item display method provided in any embodiment of the present application.
  • the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding function can be realized;
  • the names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application.

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Abstract

L'invention concerne un procédé et un appareil d'affichage d'élément virtuel, un dispositif informatique et un support de stockage. Ledit procédé comprend les étapes consistant : à afficher une salle de diffusion en continu en direct d'un diffuseur en continu en direct ; à déterminer un élément virtuel reçu par le diffuseur en continu en direct ; à déterminer une caractéristique de diffusion en continu en direct associée à l'élément virtuel ; à déterminer un comportement d'affichage correspondant à l'élément virtuel selon la caractéristique de diffusion en continu en direct ; et à exécuter le comportement d'affichage sur l'élément virtuel dans la salle de diffusion en continu en direct.
PCT/CN2020/137512 2019-12-26 2020-12-18 Procédé et appareil d'affichage d'élément virtuel, dispositif informatique et support de stockage WO2021129530A1 (fr)

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