Information processing method, information processing program, and information processing apparatus

Abstract

To ensure the quality of creative work data created by a user.SOLUTION: An information processing method according to the present application comprises determining, by a computer, based on existing primary creative work data disclosed to the public and and secondary creative work data created by a user of the primary creative work data, similarity between the primary creative work data and the secondary creative work data.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an information processing method, an information processing program, and an information processing device. [Background technology]

[0002] In recent years, CG (computer graphics) software for creating three-dimensional images has become widespread. By using such CG software, even amateur creators with insufficient experience can now easily create image data such as characters.

[0003] In recent years, technologies have become known that provide creators with an opportunity to release creative data they have created to the world and sell the creative data to customers who desire it. For example, a technology is known in which the creative data created by a creator is edited, product data is generated, and the generated product data is presented to customers. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Japanese Patent Application Laid-Open No. 2002-169970 Summary of the Invention [Problem to be solved by the invention]

[0005] However, the above-mentioned conventional technology does not necessarily guarantee the quality of the creative data created by users. For example, the above-mentioned conventional technology merely edits the creative data created by a creator, generates product data, and presents the generated product data to customers, and does not necessarily guarantee the quality of the creative data created by users.

[0006] Therefore, the present disclosure proposes an information processing method, an information processing program, and an information processing device that can guarantee the quality of creative data created by a user.

[0007] In order to solve the above problem, one form of information processing method according to the present disclosure is one in which a computer determines the similarity between existing publicly available original creative data and secondary creative data created by a user of the original creative data. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram for explaining a video content production process according to an embodiment of the present disclosure. [Figure 2] FIG. 2 is a diagram illustrating an example of a video production platform according to the embodiment. [Figure 3] FIG. 2 is a diagram illustrating an example of the configuration of an information processing system according to the embodiment. [Figure 4] FIG. 2 is a block diagram showing a configuration of an information processing device according to the embodiment. [Figure 5] 10 is a flowchart illustrating an example of information processing according to the embodiment. [Figure 6] 10 is a flowchart illustrating an example of information processing according to the embodiment. [Figure 7] FIG. 10 is a diagram illustrating an example in which the types of video content are diversified. [Figure 8] FIG. 10 is a diagram illustrating an example of an asset according to the embodiment. [Figure 9] FIG. 1 is a diagram illustrating personalization of video content through real-time rendering. [Figure 10] 10 is a diagram for explaining a mechanism for generating a derivative version of video content using the video production platform according to the embodiment. FIG. [Figure 11] FIG. 10 is a diagram showing the stakeholders and monetization mechanism related to the video production platform according to the embodiment. [Figure 12] FIG. 10 is a diagram showing a method for managing creation data in the video production platform according to the embodiment. [Figure 13] FIG. 10 is a diagram showing the effects brought about by the video production platform according to the embodiment. [Figure 14] FIG. 2 is a hardware configuration diagram illustrating an example of a computer that realizes the functions of the information processing device. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, embodiments of the present disclosure will be described in detail with reference to the drawings. In the following embodiments, the same components are designated by the same reference numerals, and redundant description will be omitted.

[0010] The present disclosure will be described in the following order: 1. Introduction 2. Embodiment 2-1.Video content production process 2-2. Example of a video production platform configuration 2-3. Example of information processing system configuration 2-4. Example of information processing device configuration 2-5. An example of information processing 2-6.Other 3. Effects of this disclosure 4. Hardware Configuration

[0011] [1. Introduction] As various technologies advance and each step of video production becomes more efficient, video production is expected to become more personalized, just as it has been in music production. This personalization is expected to lead to an increase in video works produced independently by amateur creators with insufficient experience. Unlike music, video works are narrative-based, so newly produced video works are likely to be based on some motif, such as an existing film. Therefore, newly produced video works must be consistent and coherent with the viewer's preconceptions (e.g., information about existing films or characters). Furthermore, some preconceptions held by viewers are nationally or regionally specific. For example, viewer preconceptions may stem from social conventions, current events, or religious or ethnically related phenomena, and consistency and coherence with these are also required.

[0012] On the other hand, it is difficult to determine whether a newly produced video work is consistent or coherent with the viewer's existing concepts. For example, if a commonly used rule-based system with conditional branching were used, an enormous number of conditional branching would be required. Therefore, it is considered difficult to ensure consistency or coherence with the viewer's existing concepts using a rule-based system. Furthermore, even when a large number of people are mobilized to make subjective judgments, it is highly likely that each individual's judgment will not be consistent with a uniform standard, making it difficult to ensure consistency or coherence with the viewer's existing concepts.

[0013] Therefore, an information processing device according to one embodiment of the present disclosure determines the similarity between creative data created by a user (e.g., video content personally produced by a mature creator) and existing creative data based on publicly available existing information. This allows the information processing device to determine whether or not there is consistency or consistency between the creative data created by the user and existing concepts held by viewers. Therefore, the information processing device can ensure the quality of the creative data created by the user.

[0014] [2. Embodiment] [2-1. Video content production process] Next, a video content production process according to an embodiment will be described with reference to FIG. 1. FIG. 1 is a diagram for explaining a video content production process according to an embodiment. As shown in FIG. 1, video production such as movies and dramas generally involves numerous steps and is considered to be labor-intensive. Specifically, video content is completed through ideation, which is the process of creating a concept and script, visualization, which is the process of creating video for each scene based on the script, and animation / motion, which is the process of editing each scene. Next, once the video content is completed, it is distributed to movie theaters around the country, on disc media such as DVDs, Blu-rays, and UHD Blu-rays, via terrestrial or satellite broadcasting, network distribution, and the like, and revenue from the distribution of the video content is earned.

[0015] The upper part of Figure 1 shows the production process for live-action video using conventional methods and the production process for synthetic video. It is expected that in the future, video production using conventional methods shown in the upper part of Figure 1 will shift to digital video production that actively uses 3D CG models, etc., shown in the lower part of Figure 1. Furthermore, the shift to digital video production is expected to make the production process simpler and more efficient. The lower part of Figure 1 shows the production process for video content according to an embodiment. Each of the video content production processes shown in the lower part of Figure 1 is realized by an information processing device 100 according to an embodiment. Specifically, in the ideation process, the information processing device 100 uses trained artificial intelligence (AI) to propose a concept and a script (also called a scenario) to the user. The user selects a desired scenario from the scenarios proposed by the information processing device 100.

[0016] Furthermore, in the visualization process, the information processing device 100 provides users with assets (also called virtual assets), such as data on 3D CG of characters, sets, scenery, and props, as well as data on audio, sound effects, background music, and so on. For example, the information processing device 100 manages the assets using a blockchain mechanism. Users use the assets to generate visuals for each scene. Furthermore, the information processing device 100 uses trained AI to automatically generate optimal facial expressions for characters in line with a scenario, for example.

[0017] Furthermore, in the animation / motion process, the information processing device 100 supports the editing and production of animation, camerawork, VFX, and the like. Specifically, the information processing device 100 creates scenes based on a script in a virtual space, adds actions to 3D CG of characters, etc., and performs virtual camerawork within that space to create a real-life image. Note that data related to these virtual spaces, actions, camerawork, and other technologies is also a type of asset. Users utilize these assets to generate video content by adding movement and sound to the visuals of each scene. For example, the information processing device 100 uses trained AI to generate optimal scenes from a scenario. This allows, for example, even inexperienced creators to easily create video content.

[0018] Here, assets according to this embodiment will be described in detail with reference to FIG. 8. FIG. 8 is a diagram illustrating an example of assets according to this embodiment. The word "asset" is an English word that generally means property, property, resource, etc. Assets according to this embodiment refer to material data that are components of video content. Specifically, as shown on the left side of FIG. 8, assets according to this embodiment include objects such as 3D CG sets and objects, cast, object sounds, and layouts. Furthermore, as shown in the center of FIG. 8, assets according to this embodiment include data related to movements and effects such as the movements of objects and people, visual effects, audio, and sound effects. Furthermore, as shown on the right side of FIG. 8, assets according to this embodiment include data related to editing techniques such as camerawork, lighting, time adjustment, scenarios, and scenario branching.

[0019] [2-2. Example of a video production platform configuration] Next, a video production platform according to an embodiment will be described with reference to FIG. 2. FIG. 2 is a diagram illustrating an example of a video production platform according to an embodiment. The video production platform illustrated in FIG. 2 is provided by an information processing device 100 according to an embodiment. As illustrated on the left side of FIG. 2, the information processing device 100 holds data acquired from an IP holder who holds the rights to intellectual property data (IP DATA), such as assets protected by intellectual property rights (specifically, copyrights). The information processing device 100 also holds intellectual property data (New IP DATA) newly created by professional creators. The information processing device 100 also holds video content (MOVIE DATA) produced by movie production companies. Note that video content is a copyrighted work and is therefore included in intellectual property data; however, in FIG. 2, the video content and intellectual property data other than the video content (e.g., assets) are distinguished from each other in the description.

[0020] Here, copyright is a right granted by law to an author, who is the person who creates a work. Therefore, hereinafter, assets and video content may be referred to as "creative data," meaning that they are data created by an author. Specifically, hereinafter, existing assets and existing video content created by IP holders, professional creators, and movie production companies may be referred to as "primary creative data." In contrast, new assets and new video content created by amateur creators may be referred to as "secondary creative data."

[0021] The information processing device 100 can diversify the types of video content by selecting assets according to the preferences of the viewer from among the many assets it owns and customizing the video content. Here, an example of diversifying the types of video content will be described with reference to FIG. 7. FIG. 7 is a diagram for explaining an example of diversifying the types of video content. FIG. 7 shows an example in which the information processing device 100 reconstructs video content using assets such as 3D CG according to the preferences of the viewer and delivers the reconstructed video content to the viewer.

[0022] For example, as shown in the upper left of FIG. 7, the information processing device 100 changes the playback time of video content in accordance with the viewer's preferences. Furthermore, as shown in the upper center of FIG. 7, the information processing device 100 changes the characters appearing in the video content in accordance with the viewer's preferences, for example, by including the viewer's family members as characters. Furthermore, as shown in the upper right of FIG. 7, the information processing device 100 changes the movements (actions) of the characters appearing in the video content in accordance with the viewer's preferences. Furthermore, as shown in the lower left of FIG. 7, the information processing device 100 changes the scenario of the video content in accordance with, for example, the viewer's daily activities or events. Furthermore, as shown in the lower center of FIG. 7, the information processing device 100 changes the playlist of the video content in accordance with the viewer's purpose for viewing the video content. Furthermore, as shown in the lower right of FIG. 7, the information processing device 100 changes the level of violent expression or sexual depiction in accordance with the viewer's preferences.

[0023] Furthermore, the information processing device 100 performs real-time rendering by combining assets according to the viewer's preferences. This allows the information processing device 100 to perform optimal playback in consideration of the various conditions of each individual viewer, thereby enabling personalization of video content according to the viewer's preferences. Here, personalization of video content through real-time rendering will be described with reference to FIG. 9. FIG. 9 is a diagram for explaining personalization of video content through real-time rendering.

[0024] In the example shown in FIG. 9, for example, an amateur creator uses assets to create content related to the worldview of a video work in the ideation process. Next, in the content created in the visualization process, a viewer changes an actor. Next, in the content created in the animation / motion process, the voice of the actor changed by the viewer is automatically changed. Next, the viewer selects a desired scenario from among the branching scenarios. In this way, the information processing device 100 makes it possible to provide video content customized for each viewer through real-time rendering.

[0025] Returning to the explanation of Figure 2, as shown in the upper right of Figure 2, the information processing device 100 provides amateur creators with primary creation data, which is existing assets and existing video content acquired from IP holders, etc. The amateur creators create secondary creation data, which is new assets and new video content, based on the primary creation data acquired from the information processing device 100. For example, an amateur creator creates secondary creation data, which is new video content related to a specific character, based on primary creation data such as images related to a specific character or 3D CG of sets and props. Naturally, as mentioned above, other elements in three-dimensional space, such as the script, character movements, camerawork, lighting, and sounds such as voices and inserted songs, can also be primary creation data.

[0026] An issue that arises in this case is security, such as the various rights related to the original creation data. As shown in FIG. 2, the information processing device 100 provides the original creation data to amateur creators through Data Asset Management, a system for protecting the intellectual property rights of the original creation data. The amateur creators independently process the original creation data received through Data Asset Management or use it as a reference to create secondary creation data. The amateur creators also transmit the secondary creation data they have created to the information processing device 100. The information processing device 100 also acquires the secondary creation data, which is new assets and new video content created by the amateur creators.

[0027] As shown in FIG. 2, the information processing device 100 acquires derivative work data created by amateur creators through an AI filter mechanism that ensures consistency and consistency with viewers' preconceived notions. For example, when amateur creators create assets, video content, etc., the newly created assets and video content (derivative data) are likely to be based on motifs (primary data) from existing video works, such as existing movies and TV dramas. Alternatively, since it is assumed that the creators have certain preconceived notions about the existing works, consistency and consistency between the newly created assets and video content (derivative data) and the preconceived notions is required. Furthermore, consistency and consistency between the newly created assets and video content (derivative data) and social norms, current affairs, and religious and ethnic phenomena, which are characteristic of each country or region, is also required. The AI ​​filter plays a role in ensuring this consistency and consistency. Figure 2 shows a video production platform equipped with an AI filter that judges the acceptability of derivative work data created by amateur creators based on certain criteria.

[0028] In addition, the information processing device 100 distributes video content, which is secondary creative data created by amateur creators, to viewers through a Data Right Management system equipped with various digital content protection technologies and blockchain technology.

[0029] [2-3. Example of information processing system configuration] Next, the configuration of an information processing system according to an embodiment will be described with reference to FIG. 3. FIG. 3 is a diagram showing an example of the configuration of an information processing system according to an embodiment. As shown in FIG. 3, an information processing system 1 according to this embodiment includes an owner terminal 10, a creator terminal 20, a viewer terminal 30, and an information processing device 100. Note that the information processing system 1 may also include an external information processing device such as a terminal device used by a system administrator. These various devices are connected to each other via a network N (e.g., the Internet) so as to be able to communicate with each other via wired or wireless communication. Note that the information processing system 1 shown in FIG. 3 may include any number of owner terminals 10, any number of creator terminals 20, any number of viewer terminals 30, and any number of information processing devices 100.

[0030] The owner terminal 10 is an information processing device used by an owner who holds the intellectual property rights of primary creation data, which is existing creative data that has been made public. Here, the owner refers to an owner (IP holder) who holds the intellectual property rights of assets, etc., a professional creator (Pro Creator) who created assets or video content, or a movie production company (Movie Production) that produces video content. Furthermore, primary creation data refers to assets or video content whose intellectual property rights the owner holds that have been made public. Furthermore, the owner terminal 10 transmits the primary creation data to the information processing device 100 in accordance with the owner's operation.

[0031] The producer terminal 20 is an information processing device used by an amateur creator (hereinafter also referred to as a producer) who creates secondary creation data, which is new creation data. Here, the secondary creation data is data that is not publicly available until, for example, the producer makes it available on a video production platform. The producer terminal 20 transmits a distribution request for primary creation data to the information processing device 100 in accordance with the producer's operation. In addition, the producer terminal 20 receives primary creation data from the information processing device 100.

[0032] Furthermore, the creator terminal 20 transmits secondary creation data created by the creator to the information processing device 100 in accordance with the creator's operation. For example, the creator terminal 20 transmits secondary creation data created by the creator based on primary creation data to the information processing device 100 in accordance with the creator's operation.

[0033] The viewer terminal 30 is an information processing device used by a viewer who views video content. The viewer terminal 30 transmits a distribution request for video content, which is secondary creation data created by a producer, to the information processing device 100 in accordance with the viewer's operation. The viewer terminal 30 also receives the video content, which is secondary creation data, from the information processing device 100. Subsequently, upon receiving the video content, which is secondary creation data, the viewer terminal 30 displays the received video content on the screen of the viewer terminal 30.

[0034] The information processing device 100 acquires the original creation data from the owner terminal 10. When the information processing device 100 acquires the original creation data from the owner terminal 10, the information processing device 100 stores the acquired original creation data in a storage unit.

[0035] Furthermore, the information processing device 100 acquires a distribution request for the primary creation data from the creator terminal 20. Upon acquiring the distribution request, the information processing device 100 transmits the primary creation data to the creator terminal 20 in response to the distribution request. Specifically, the information processing device 100 transmits the primary creation data to the creator terminal 20 through the data asset management described in FIG. 2 .

[0036] Furthermore, the information processing device 100 acquires secondary creation data from the creator terminal 20. For example, the information processing device 100 acquires secondary creation data created by a creator based on primary creation data from the creator terminal 20. Next, upon acquiring the secondary creation data, the information processing device 100 passes the acquired secondary creation data through the AI ​​filter described in FIG. 2 to determine whether there is consistency or coherence between the acquired secondary creation data and the viewer's preconceived notions.

[0037] Specifically, the information processing device 100 uses a trained AI (equivalent to an AI filter) based on publicly available existing information to determine the similarity between the derivative work data created by the creator and the original work data. For example, the information processing device 100 inputs the derivative work data created by the creator into the trained AI and calculates the similarity between the derivative work data and the original work data. Next, if the similarity between the derivative work data and the original work data exceeds a predetermined threshold, the information processing device 100 determines that there is similarity between the derivative work data and the original work data. Next, if the information processing device 100 determines that there is similarity between the derivative work data and the original work data, it determines that there is consistency or consistency between the derivative work data and the viewer's preconceived notions. Next, if the information processing device 100 determines that there is consistency or consistency between the derivative work data and the viewer's preconceived notions, it acquires the derivative work data as new creation data.

[0038] On the other hand, if the similarity between the secondary creation data and the primary creation data is equal to or less than a predetermined threshold, the information processing device 100 determines that there is no similarity between the secondary creation data and the primary creation data. If the information processing device 100 determines that there is no similarity between the secondary creation data and the primary creation data, it determines that there is no consistency or consistency between the secondary creation data and the viewer's preconceived notions. Next, if the information processing device 100 determines that there is no consistency or consistency between the secondary creation data and the viewer's preconceived notions, it presents the creator with the reason for determining that there is no similarity. Next, after presenting the reason for determining that there is no similarity, the information processing device 100 presents the creator with examples of data determined to be similar to the primary creation data.

[0039] Furthermore, the information processing device 100 acquires a distribution request for video content, which is secondary creation data, from the viewer terminal 30. Upon acquiring the distribution request for the video content, the information processing device 100 distributes the video content, which is secondary creation data, to the viewer terminal 30 in response to the distribution request. Specifically, the information processing device 100 distributes the video content, which is secondary creation data, to the viewer terminal 30 through Data Right Management described in FIG. 2 .

[0040] [2-4. Example of configuration of information processing device] Next, the configuration of the information processing device according to the embodiment will be described with reference to Fig. 4. Fig. 4 is a block diagram showing the configuration of the information processing device according to the embodiment. As shown in Fig. 4, the information processing device 100 includes a communication unit 110, a storage unit 120, and a control unit 130. Note that the information processing device 100 may also include an input unit (for example, a keyboard, a mouse, etc.) that accepts various operations from an administrator of the information processing device 100, etc.

[0041] (Communication unit 110) The communication unit 110 is realized by, for example, a network interface card (NIC) etc. The communication unit 110 is connected to the network N by wire or wirelessly, and transmits and receives information to and from the owner terminal 10, the creator terminal 20, and the viewer terminal 30 via the network N.

[0042] (Storage unit 120) The storage unit 120 is realized by, for example, a semiconductor memory element such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk. As shown in FIG. 4, the storage unit 120 has a creation data storage unit 121.

[0043] (Creation data storage unit 121) The creation data storage unit 121 stores information related to creation data. Specifically, the creation data storage unit 121 stores information related to assets or video content, which are primary creation data.

[0044] The creative product data storage unit 121 also stores information about assets or video content that are derivative work data. More specifically, the creative product data storage unit 121 stores the derivative work data, the similarity calculated by the AI ​​filter, and information that identifies the copyright holder of the derivative work data, in association with each other. For example, the creative product data storage unit 121 stores the derivative work data, the similarity to the primary work data calculated by the AI ​​filter, and information that identifies the amateur creator who created the secondary work data, in association with each other. Furthermore, for derivative work data created based on primary work data, the creative product data storage unit 121 also stores the similarity to the primary work data calculated by the AI ​​filter and information that identifies the copyright holder of the primary work data, in association with each other.

[0045] (control unit 130) The control unit 130 is a controller, and is reproduced by, for example, a CPU (Central Processing Unit) or an MPU (Micro Processing Unit) executing various programs (corresponding to examples of information processing programs) stored in a storage device inside the information processing device 100 using RAM as a work area. The control unit 130 is also a controller, and is reproduced by, for example, an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

[0046] 4, control unit 130 has an acquisition unit 131, a determination unit 132, a distribution unit 133, and a decision unit 134, and reproduces or executes the information processing action described below. Note that the internal configuration of control unit 130 is not limited to the configuration shown in FIG. 4, and other configurations may be used as long as they perform the information processing described below.

[0047] (Acquisition part 131) The acquisition unit 131 acquires the original creation data from the owner terminal 10. Upon acquiring the original creation data from the owner terminal 10, the acquisition unit 131 stores the acquired original creation data in the creation data storage unit 121. Specifically, the acquisition unit 131 associates the original creation data with information that can identify the owner who holds the copyright of the original creation data, and stores the associated data in the creation data storage unit 121. More specifically, the acquisition unit 131 associates the original creation data with information that can identify the owner who is the sender of the original creation data, and stores the associated data in the creation data storage unit 121.

[0048] For example, the acquisition unit 131 associates an asset with information that can identify an IP holder who holds the copyright of the asset, and stores the associated assets in the creation data storage unit 121. Also, for example, the acquisition unit 131 associates an asset or video content with information that can identify a professional creator (Pro Creator) who holds the copyright of the asset or video content, and stores the associated assets in the creation data storage unit 121. Also, for example, the acquisition unit 131 associates video content with information that can identify a movie production company (Movie Production) who holds the copyright of the video content, and stores the associated assets in the creation data storage unit 121.

[0049] Furthermore, the acquisition unit 131 acquires a distribution request for the primary creation data from the creator terminal 20. Upon acquiring the distribution request, the acquisition unit 131 transmits the primary creation data to the creator terminal 20 in response to the distribution request. Specifically, the acquisition unit 131 refers to the creation data storage unit 121 and extracts the primary creation data in response to the distribution request. Next, the acquisition unit 131 transmits the extracted primary creation data to the creator terminal 20 through a data asset management mechanism.

[0050] (Judgment unit 132) The determination unit 132 acquires secondary creation data from the creator terminal 20. For example, the determination unit 132 acquires secondary creation data created by a creator based on primary creation data from the creator terminal 20. Next, upon acquiring the secondary creation data, the determination unit 132 uses an AI filter to determine whether or not there is consistency or coherence between the acquired secondary creation data and the viewer's preconceived notions.

[0051] Specifically, the determination unit 132 determines the similarity between existing information and the creative data (secondary creative data) based on existing information, which is information about socially accepted customs, practices, ethics, religious views, historical views, laws, or government ordinances in the distribution region of the creative data. More specifically, the determination unit 132 uses existing information such as scenarios, scripts (dialogue), audio, and video content of banned movies, dramas, and music videos, as well as text data from newspaper articles on current affairs such as recent accidents, crimes, and trends, as well as video news content and radio audio data, and trains the AI ​​of the AI ​​filter by narrowing it down to the country or region of the distribution region. For example, the determination unit 132 trains a machine learning model based on the characteristics of the existing information described above.

[0052] Furthermore, the determination unit 132 determines the similarity between existing creative data, which is an existing video work, and creative data created based on the existing video work, based on existing information about the existing video work. For example, the determination unit 132 determines the similarity between existing creative data, which is an existing video work, and creative data created based on the existing video work, based on existing information about the existing video work, which is information about the existing video work, including existing video works, video series including the existing video work, video works derived from the existing video work, and works that are the original work of the existing video work. More specifically, the determination unit 132 trains the AI ​​of the AI ​​filter using existing information, such as the scenario, video content, script (dialogue) audio, background music sound data, text and illustrations from books such as original novels and manga that serve as the basis, text and evaluation results from reviews and introductory articles that feature the target work, and numerical data such as box office revenue rankings, amounts, and audience numbers. For example, the determination unit 132 trains a machine learning model based on the characteristics of the existing information.

[0053] Furthermore, the determination unit 132 determines the similarity between existing creative data of an existing character and creative data created based on the existing character based on existing information that is information about the existing character. For example, the determination unit 132 determines the similarity between existing creative data of an existing character and creative data created based on the existing character based on existing information that is information about the existing character, such as the profile of the existing character or information about the relationship between the existing character and other existing characters. More specifically ... character data of the profile contents of actors and characters and sentence data of magazine articles obtained by crawling the Internet. The AI ​​filter's AI is trained using existing information, such as the screenplays, video content (from DVDs and online videos) of films, dramas, and stage productions in which the actor has previously appeared or voiced, scripts (dialogue), background music, interview article text, inserted photos, video interview content, spoken content, and audio data, as well as character profiles set from the above, or data representing relationships between characters and related past events (such as a break in friendship or divorce) using a tree, etc., and big data-based AI profiling of characters performed by real people. Data between the lines about characters not depicted in the work, original work, or related articles is used as existing information. For example, the determination unit 132 trains a machine learning model to learn the characteristics of the above-mentioned existing information.

[0054] Next, the determination unit 132 uses the AI ​​of the AI ​​filter that has been trained based on existing information to determine the similarity between the derivative work data created by the amateur creator and the existing creative work data. For example, the determination unit 132 inputs the derivative work data created by the creator into the trained AI and calculates the similarity between the derivative work data and the existing creative work data. Next, if the similarity between the derivative work data and the existing creative work data exceeds a predetermined threshold, the determination unit 132 determines that there is similarity between the derivative work data and the existing creative work data. Next, if the determination unit 132 determines that there is similarity between the derivative work data and the existing creative work data, it determines that there is consistency or consistency between the derivative work data and the viewer's preconceived notions. Next, if the determination unit 132 determines that there is consistency or consistency between the derivative work data and the viewer's preconceived notions, it stores the derivative work data in the creative work data storage unit 121 as new creative work data.

[0055] On the other hand, if the similarity between the secondary creation data and the existing creation data is equal to or less than a predetermined threshold, the determination unit 132 determines that there is no similarity between the secondary creation data and the existing creation data. If the determination unit 132 determines that there is no similarity between the secondary creation data and the existing creation data, it determines that there is no consistency or consistency between the secondary creation data and the viewer's preconceived notions. Next, if the determination unit 132 determines that there is no consistency or consistency between the secondary creation data and the viewer's preconceived notions, it presents the creator with the reason for determining that there is no similarity. Next, after presenting the reason for determining that there is no similarity, the determination unit 132 presents the creator with examples of data that are determined to be similar to the existing creation data.

[0056] The determination unit 132 also determines the similarity between each piece of creative data created at each stage of video production and existing creative data. Specifically, the determination unit 132 determines the similarity between creative data created at a predetermined stage of video production and existing creative data, which is creative data created at an earlier stage. For example, the determination unit 132 determines the similarity between video content created at a predetermined stage of video production by an amateur creator and existing creative data, which is video content created at an earlier stage. For example, the determination unit 132 inputs the video content created at the predetermined stage into a trained AI and calculates the similarity between the video content created at the predetermined stage and the video content created at an earlier stage. Next, if the similarity between the video content created at the predetermined stage and the video content created at an earlier stage exceeds a predetermined threshold, the determination unit 132 determines that there is similarity between the two pieces of content. Next, if the determination unit 132 determines that there is similarity between the two pieces of content, it determines that there is consistency or coherence between the two pieces of content. Next, if the determining unit 132 determines that there is consistency or coherence between the two contents, it notifies the creator that it is OK to proceed to the next step following the predetermined step.

[0057] On the other hand, if the similarity between video content created in a predetermined process and video content created in a process prior to the predetermined process is equal to or less than a predetermined threshold, the determination unit 132 determines that there is no similarity between the two contents. If the determination unit 132 determines that there is no similarity between the two contents, it determines that there is no consistency or inconsistency between the two contents. Next, if the determination unit 132 determines that there is no consistency or inconsistency between the two contents, it presents the creator with the reason for determining that there is no consistency or inconsistency between the two contents. Next, after presenting the reason for determining that there is no similarity, the determination unit 132 presents the creator with examples of data that are determined to be similar to video content created in a process prior to the predetermined process.

[0058] In this way, the determination unit 132 determines the similarity between the creative data created by the user and the existing creative data based on existing publicly available information. For example, the determination unit 132 determines the similarity between the creative data, which is video content or an asset created by the user, and the existing creative data.

[0059] (Distribution Section 133) The distribution unit 133 distributes creative data, which is video content, based on the similarity determined by the determination unit 132. Specifically, the distribution unit 133 distributes creative data determined to have similarity by the determination unit 132. For example, the distribution unit 133 acquires a distribution request for video content, which is derivative creative data, from the viewer terminal 30. Upon acquiring the distribution request for the video content, the distribution unit 133 refers to the creative data storage unit 121 and extracts the similarity stored in association with the derivative creative data corresponding to the distribution request. After extracting the similarity, the distribution unit 133 determines whether the extracted similarity exceeds a predetermined threshold. If the distribution unit 133 determines that the extracted similarity exceeds the predetermined threshold, the distribution unit 133 distributes the video content, which is derivative creative data, to the viewer terminal 30 in response to the distribution request. Specifically, the distribution unit 133 then distributes the video content, which is the secondary creation data, to the viewer terminal 30 through the Data Right Management described with reference to FIG.

[0060] On the other hand, if the distribution unit 133 determines that the extracted similarity is equal to or less than the predetermined threshold, it transmits to the viewer terminal 30 a notification that the video content that is the subject of the distribution request will not be distributed.

[0061] (Decision unit 134) The determination unit 134 determines a distribution ratio of the distribution revenue for the creative data, which is video content, based on the similarity determined by the determination unit 132. Specifically, the determination unit 134 determines a distribution ratio of the distribution revenue to be distributed to the owner who holds the rights to the existing creative data and the user who created the creative data, which is video content, based on the existing creative data. For example, the lower the similarity between the creative data determined by the determination unit 132 and the existing creative data, the higher the user's contribution to the creation of the creative data is considered to be. Therefore, the determination unit 134 determines the distribution ratio of the distribution revenue to be distributed to the user to be higher than the distribution ratio of the distribution revenue to be distributed to the owner, the lower the similarity between the creative data created by the user and the existing creative data. On the other hand, the higher the similarity between the creative data determined by the determination unit 132 and the existing creative data, the more the creative data relies on the existing creative data, and therefore the lower the user's contribution to the creation of the creative data is considered to be. Therefore, the determination unit 134 determines that the distribution ratio of distribution revenues to be distributed to the owner is higher than the distribution ratio of distribution revenues to be distributed to the user, the higher the similarity between the creative data created by the user and the existing creative data.

[0062] Furthermore, while the source of monetization is thought to be subscription fees to viewers, an example of a method for distributing distribution revenues obtained from the distribution of derivative work data is shown in Figure 11. Figure 11 is a diagram for explaining the stakeholders and monetization mechanism related to the video production platform according to the embodiment. Figure 11 also shows a comparison with monetization methods used in general video works up to now. In Figure 11, the amount paid by consumers who have viewed the video content, which is derivative work data, varies depending on the level of reputation of the video content. The amount paid by consumers is the distribution revenues for the derivative work data. Distribution revenues are distributed to each creator and the IP holder who owns the original IP content.

[0063] At this time, the video production platform shown in Fig. 2 determines the distribution ratio of the distribution revenue. Specifically, the determination unit 134 determines the distribution ratio of the distribution revenue based on the judgment level of the AI ​​filter (such as whether there were many NGs due to the judgment, or whether the score indicating the similarity with existing creative work data was high).

[0064] [2-5. An example of information processing] Next, the flow of information processing according to the embodiment will be described with reference to Fig. 5. Fig. 5 is a flowchart showing an example of information processing according to the embodiment. As shown in Fig. 5, the information processing device 100 presents primary creation data (step S101). For example, the information processing device 100 displays the primary creation data on the producer terminal 20 of an amateur creator. Furthermore, the amateur creator creates secondary creation data based on the primary creation data.

[0065] Next, the information processing device 100 acquires secondary creation data (step S102). For example, the information processing device 100 acquires secondary creation data created by an amateur creator from the creator terminal 20.

[0066] Next, when the information processing device 100 acquires the derivative product data, it determines the similarity between the acquired derivative product data and the existing original product data, which is the original product data, based on existing information (step S103).

[0067] When the information processing device 100 determines that there is similarity between the secondary creation data and the primary creation data (step S103; Yes), it registers the secondary creation data as new creation data (step S104).

[0068] On the other hand, if the information processing device 100 determines that there is no similarity between the secondary creation data and the primary creation data (step S103; No), it presents the reason why it has determined that there is no similarity (step S105). For example, the information processing device 100 displays the reason why it has determined that there is no similarity to the creator terminal 20 of the amateur creator.

[0069] Next, the information processing device 100 presents the reason for determining that there is no similarity, and then presents examples of data that are determined to have similarity to the primary creation data (step S106). For example, the information processing device 100 displays examples of data that are determined to have similarity to the primary creation data on the producer terminal 20 of the amateur creator.

[0070] Next, a flow of information processing according to the embodiment will be described with reference to Fig. 6. Fig. 6 is a flowchart showing an example of information processing according to the embodiment. As shown in Fig. 6, the information processing device 100 receives a content distribution request (step S201). For example, the information processing device 100 receives a content distribution request for a video work, which is secondary creation data created by an amateur creator, from the viewer terminal 30 of the viewer.

[0071] Next, the information processing device 100 distributes the content (step S202). For example, the information processing device 100 distributes the content of a video work, which is secondary creation data created by an amateur creator, to the viewer terminal 30 of the viewer.

[0072] Next, the information processing device 100 determines the distribution ratio of the distribution revenue according to the similarity (step S203). For example, the information processing device 100 determines the ratio of the distribution revenue to be distributed to the owner who holds the rights to the primary creation data and the amateur creator who created the secondary creation data based on the primary creation data, based on the similarity between the primary creation data and the secondary creation data created based on the primary creation data.

[0073] [2-6.Other] Video works created on the video production platform shown in FIG. 2 can also be managed for each upgraded or derivative version at the time of software release, as shown in FIGS. 10 and 13. FIG. 10 illustrates a mechanism for generating derivative versions of video content using a video production platform according to an embodiment. FIG. 13 illustrates the effects of the video production platform according to an embodiment. Specifically, when creating a test release of a pre-release beta version on the video production platform shown in FIG. 2, followed by the official version, upgraded versions, and derivative versions, it is believed that production efficiency can be improved if operations similar to those performed on source code version control systems such as CVS (Concurrent Versions System), VSS (Visual SourceSafe), and GitHub can be performed, as shown in FIG. 12. FIG. 12 illustrates a method for managing creation data on the video production platform according to an embodiment. This enables a mechanism for easily achieving division of labor across locations when considering the personalization of video production.

[0074] [3. Effects of this disclosure] As described above, the information processing device 100 according to an embodiment of the present disclosure includes the determination unit 132. The determination unit 132 determines the similarity between creative data created by a user and existing creative data based on existing publicly available information.

[0075] This allows the information processing device to determine whether there is consistency or consistency between the creative data created by the user and existing creative data. Furthermore, since the information processing device can determine whether there is consistency or consistency between the creative data created by the user and existing creative data, it is possible to ensure consistency or consistency with existing concepts held by viewers. Therefore, the information processing device can ensure the quality of the creative data created by the user.

[0076] In addition, the judgment unit 132 judges the similarity between the existing information and the creative data based on existing information, which is information regarding socially accepted customs, practices, ethical views, religious views, historical views, laws, or government ordinances in the distribution area of ​​the creative data.

[0077] This allows the information processing device 100 to determine whether there is consistency or consistency between the creative data created by the user and the socially accepted customs, etc. in the distribution area of ​​the creative data. Furthermore, since the information processing device can determine whether there is consistency or consistency between the creative data created by the user and the socially accepted customs, etc. in the distribution area of ​​the creative data, it can determine whether there is consistency or consistency with the viewer's preconceived notions, etc.

[0078] Furthermore, the determination unit 132 determines the similarity between existing creative data that is an existing video work and creative data created based on an existing video work, based on existing information that is information about the existing video work. For example, the determination unit 132 determines the similarity between existing creative data that is an existing video work and creative data created based on an existing video work, based on existing information that is information about the existing video work, such as information about the existing video work, a series of video works including the existing video work, a video work derived from the existing video work, or an original work of the existing video work.

[0079] This allows the information processing device 100 to determine whether there is consistency or consistency between the creative data created by the user and the existing video work.

[0080] Furthermore, the determination unit 132 determines the similarity between existing creative data that is an existing character and creative data created based on an existing character based on existing information that is information about the existing character. For example, the determination unit 132 determines the similarity between existing creative data that is an existing character and creative data created based on an existing character based on existing information that is information about the existing character, such as a profile of the existing character or information about the relationship between the existing character and other existing characters.

[0081] This allows the information processing device 100 to determine whether there is consistency or consistency between the creative data created by the user and an existing person or character.

[0082] Furthermore, the determination unit 132 determines the similarity between each piece of creative data created in each process of video production and existing creative data.

[0083] This allows the information processing device 100 to determine whether there is consistency or consistency with each piece of creative data created in each step of video production.

[0084] Furthermore, the determination unit 132 determines the similarity between creative data created in a predetermined process of video production and existing creative data that is creative data created in a process prior to the predetermined process.

[0085] This allows the information processing device 100 to determine whether there is consistency or integrity between creative data created in a specified process of video production and creative data created in a process prior to the specified process.

[0086] Furthermore, the determination unit 132 determines the similarity between creative data, which is video content or assets created by a user, and existing creative data.

[0087] This allows the information processing device 100 to determine whether there is consistency or consistency between the video content or asset created by the user and the existing creative data.

[0088] The information processing device 100 further includes a distribution unit 133. Based on the similarity determined by the determination unit 132, the distribution unit 133 distributes creative data that is video content.

[0089] This allows the information processing device 100 to ensure the quality of the video content to be distributed.

[0090] The information processing device 100 further includes a determination unit 134. The determination unit 134 determines a distribution ratio of distribution revenues for the creative data, which is video content, based on the similarity determined by the determination unit 132. For example, the determination unit 134 determines a distribution ratio of distribution revenues to be distributed to a holder who holds the rights to the existing creative data and a user who created the creative data, which is video content, based on the existing creative data.

[0091] This allows the information processing device 100 to distribute distribution revenue to the owner of the rights to the existing creative data and the user who created the creative data, which is video content, based on the existing creative data, in accordance with the degree of contribution to the creation of the creative data.

[0092] [4. Hardware Configuration] An information device such as the information processing device 100 according to the embodiment described above is realized by a computer 1000 having a configuration as shown in FIG. 14, for example. FIG. 14 is a hardware configuration diagram showing an example of the computer 1000 that reproduces the functions of an information processing device such as the information processing device 100. The information processing device 100 according to the embodiment will be described below as an example. The computer 1000 has a CPU 1100, a RAM 1200, a ROM (Read Only Memory) 1300, a HDD (Hard Disk Drive) 1400, a communication interface 1500, and an input / output interface 1600. The components of the computer 1000 are connected by a bus 1050.

[0093] The CPU 1100 operates and controls each unit based on programs stored in the ROM 1300 or the HDD 1400. For example, the CPU 1100 loads the programs stored in the ROM 1300 or the HDD 1400 into the RAM 1200 and executes processing corresponding to the various programs.

[0094] The ROM 1300 stores boot programs such as a Basic Input Output System (BIOS) executed by the CPU 1100 when the computer 1000 is started, and programs that depend on the hardware of the computer 1000 .

[0095] HDD 1400 is a computer-readable recording medium that non-temporarily records programs executed by CPU 1100 and data used by such programs. Specifically, HDD 1400 is a recording medium that records an information processing program according to the present disclosure, which is an example of program data 1450.

[0096] The communication interface 1500 is an interface for connecting the computer 1000 to an external network 1550 (e.g., the Internet). For example, the CPU 1100 receives data from other devices and transmits data generated by the CPU 1100 to other devices via the communication interface 1500.

[0097] The input / output interface 1600 is an interface for connecting the input / output device 1650 and the computer 1000. For example, the CPU 1100 receives data from an input device such as a keyboard or a mouse via the input / output interface 1600. The CPU 1100 also transmits data to an output device such as a display, a speaker, or a printer via the input / output interface 1600. The input / output interface 1600 may also function as a media interface for reading programs and the like recorded on a predetermined recording medium. Examples of media include optical recording media such as a DVD (Digital Versatile Disc) or a PD (Phase Change Rewritable Disk), magneto-optical recording media such as an MO (Magneto-Optical disk), tape media, magnetic recording media, and semiconductor memories.

[0098] For example, when the computer 1000 functions as the information processing device 100 according to the embodiment, the CPU 1100 of the computer 1000 executes an information processing program loaded onto the RAM 1200 to reproduce the functions of the control unit 130, etc. The information processing program according to the present disclosure and data in the storage unit 120 are stored in the HDD 1400. The CPU 1100 reads and executes program data 1450 from the HDD 1400, but as another example, the CPU 1100 may obtain these programs from another device via an external network 1550.

[0099] The present technology can also be configured as follows. (1) a determination unit that determines the similarity between creative data created by a user and existing creative data based on existing publicly available information; An information processing device comprising: (2) The determination unit Further determining the similarity between the existing information and the creative data based on the existing information, which is information regarding socially accepted customs, practices, ethics, religious views, historical views, laws, or government ordinances in the distribution area of ​​the creative data; The information processing device according to (1) above. (3) The determination unit determining a similarity between the existing creative data, which is the existing video work, and the creative data created based on the existing video work, based on the existing information, which is information related to the existing video work; The information processing device according to (1) or (2). (4) The determination unit determining the similarity between the existing creative work data, which is the existing visual work, and the creative work data created based on the existing visual work, based on the existing information, which is information about the existing visual work and a series of visual works including the existing visual work, a visual work derived from the existing visual work, or a work that is the original of the existing visual work; The information processing device according to (3) above. (5) The determination unit determining, based on the existing information that is information about an existing character, a similarity between the existing creative data that is the existing character and the creative data created based on the existing character; The information processing device according to any one of (1) to (4). (6) The determination unit determining the similarity between the existing creative data, which is the existing character, and the creative data created based on the existing character, based on the existing information, which is information about the existing character, such as a profile of the existing character or information about a relationship between the existing character and another existing character; The information processing device according to (5) above. (7) The determination unit determining the similarity between each of the creative data created in each process of video production and the existing creative data; The information processing device according to any one of (1) to (6). (8) The determination unit determining the similarity between the creative data created in a predetermined process of the video production and the existing creative data, which is creative data created in a process prior to the predetermined process; The information processing device according to (7) above. (9) The determination unit determining a similarity between the creative data, which is video content or assets created by the user, and the existing creative data; The information processing device according to any one of (1) to (8). (10) a distribution unit that distributes the creative data, which is video content, based on the similarity determined by the determination unit; The information processing device according to any one of (1) to (9) above, further comprising: (11) a determination unit that determines a distribution ratio of the distribution revenue of the creative work data, which is video content, based on the similarity determined by the determination unit; The information processing device according to any one of (1) to (10) above, further comprising: (12) The determination unit determining a distribution ratio of the distribution revenue to be distributed between a right holder of the existing creative data and a user who created the creative data, which is the video content, based on the existing creative data; The information processing device according to (11) above. (13) The computer Determine the similarity between the creative data created by the user and existing creative data based on existing publicly available information; Information processing methods. (14) a determination process for determining the similarity between creative data created by a user and existing creative data based on existing publicly available information; An information processing program that causes a computer to execute the above. [Explanation of symbols]

[0100] 1. Information Processing Systems 10 Owner's Terminal 20 Creator terminal 30 Viewer terminal 100 Information processing device 110 Communications Department 120 Storage section 121 Creative Works Data Storage Unit 130 Control Unit 131 Acquisition Department 132 Judgment section 133 Distribution Department 134 Decision Section

Claims

1. The computer determining the similarity between the primary creation data and the secondary creation data based on existing primary creation data that has been made public and secondary creation data created by a user of the primary creation data; Information processing methods.

2. the secondary creation data is input into a machine learning model trained based on the primary creation data, thereby determining the similarity between the primary creation data and the secondary creation data; The information processing method according to claim 1 .

3. Further determining the similarity between the primary creation data and the secondary creation data based on the primary creation data, which is information about socially accepted customs, practices, ethics, religious views, historical views, laws, or government ordinances in the distribution area of ​​the primary creation data; The information processing method according to claim 2 .

4. determining, based on the primary creation data which is information relating to the existing video work, a similarity between the primary creation data which is the existing video work and the secondary creation data which is created based on the existing video work; The information processing method according to claim 2 .

5. determining the similarity between the primary creation data, which is the existing video work, and the secondary creation data created based on the existing video work, based on the primary creation data, which is information about the existing video work, a series of video works including the existing video work, a video work derived from the existing video work, or a work that is the original of the existing video work; The information processing method according to claim 4.

6. determining, based on the primary creation data which is information about an existing character, the similarity between the primary creation data which is the existing character and the secondary creation data which is created based on the existing character; The information processing method according to claim 2 .

7. determining the similarity between the primary creation data of the existing character and the secondary creation data created based on the existing character, based on the primary creation data being information about the existing character, which is information about a profile of the existing character or a relationship between the existing character and another existing character; The information processing method according to claim 6.

8. determining the similarity between each of the secondary creation data created in each step of the video production and the primary creation data; The information processing method according to claim 2 .

9. determining the similarity between the secondary creation data created in a predetermined process of the video production and the primary creation data, which is creation data created in a process prior to the predetermined process; The information processing method according to claim 8.

10. determining the similarity between the secondary creation data, which is content or assets created by the user, and the primary creation data; The information processing method according to claim 2 .

11. When the determined similarity is calculated to be higher than a predetermined threshold, the derivative work data is distributed.

3. The information processing method according to claim 2, further comprising:

12. determining a distribution ratio of the revenue from the distribution of the derivative work data based on the determined similarity; 3. The information processing method according to claim 2, further comprising:

13. determining a distribution ratio of the distribution revenue to be distributed between the owner of the rights to the primary creation data and the user who created the secondary creation data based on the primary creation data; The information processing method according to claim 12.

14. If it is determined that there is no consistency or integrity between the secondary creation data and the primary creation data based on the similarity, the reason for the determination is presented to the user, and examples of data that are determined to be similar to the primary creation data are presented to the user. The information processing method according to claim 2 .

15. If it is determined based on the similarity that there is consistency or coherence between the secondary creation data created in a predetermined production step and data created in a step prior to the predetermined step, permission is given to proceed to the next step in the predetermined step related to the secondary creation data. The information processing method according to claim 2 .

16. If it is determined based on the similarity that there is no consistency or integrity between the secondary creation data created in a predetermined production process and data created in a process prior to the predetermined process, examples of content data determined to be similar to the data created in a process prior to the predetermined process are presented to the user. The information processing method according to claim 15.

17. The lower the determined similarity, the higher the distribution revenue share to be distributed to the user rather than to the owner is determined; or determining a distribution revenue distribution ratio to be distributed to the owner rather than the user, the higher the determined similarity; The information processing method according to claim 13.

18. Acquire information about reputations from viewers who have viewed the secondary creation data; fluctuating the amount of money paid by the viewer for the derivative work data based on the acquired information on the reputation; The information processing method according to claim 11.

19. Changing the level of violent or sexual depictions contained in the derivative work data according to the viewer's preferences; 19. The information processing method according to claim 18.

20. a determination process for determining the similarity between the primary creation data and the secondary creation data based on existing primary creation data that has been made public and secondary creation data created by a user of the primary creation data; An information processing program that causes a computer to execute the above.

21. a determination unit that determines the similarity between the primary creation data and the secondary creation data based on existing primary creation data that has been made public and secondary creation data created by a user of the primary creation data; An information processing device comprising:

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