WO2023058101A1 - Système pour promouvoir la reproduction d'une image animée, procédé pour promouvoir la reproduction d'une image animée, et programme - Google Patents

Système pour promouvoir la reproduction d'une image animée, procédé pour promouvoir la reproduction d'une image animée, et programme Download PDF

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Publication number
WO2023058101A1
WO2023058101A1 PCT/JP2021/036700 JP2021036700W WO2023058101A1 WO 2023058101 A1 WO2023058101 A1 WO 2023058101A1 JP 2021036700 W JP2021036700 W JP 2021036700W WO 2023058101 A1 WO2023058101 A1 WO 2023058101A1
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WIPO (PCT)
Prior art keywords
video
moving image
uploaded
unit
thumbnail
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PCT/JP2021/036700
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English (en)
Japanese (ja)
Inventor
寿郎 佐々木
健晴 手嶋
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シエンプレ株式会社
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Priority to PCT/JP2021/036700 priority Critical patent/WO2023058101A1/fr
Publication of WO2023058101A1 publication Critical patent/WO2023058101A1/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]
    • H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
    • H04N21/27—Server based end-user applications

Definitions

  • the present invention relates to a technique effective for supporting the playback of videos uploaded to SNS (Social Networking Service).
  • SNS Social Networking Service
  • SNSs for uploading moving images as described above are popular, and if the number of views of the uploaded moving images can be earned, profits from the moving images can be expected.
  • simply uploading a video to an SNS does not necessarily mean that the number of views of the video can be earned.
  • Patent Literatures 1 and 2 do not lead to techniques for displaying a video uploaded to an SNS in a related video column of other videos viewed by a third party or in a recommended video column for a third party. I didn't. Therefore, the present inventors focused on a mechanism for displaying a video uploaded to an SNS in a related video column of other videos viewed by a third party or in a recommended video column for a third party.
  • the present invention supports displaying a video uploaded to a SNS in a related video column of another video viewed by a third party or in a recommended video column for a third party. It is an object of the present invention to provide a moving image reproduction support system, a moving image reproduction support method, and a program capable of efficiently increasing the number of reproductions.
  • the present invention is a video playback support system that supports playback of videos uploaded to SNS, an acquisition unit that acquires materials for creating the moving image; a creation unit that creates the video and thumbnail using the acquired material; an input reception unit that receives input of video information of the created video; an upload unit that uploads the created video and thumbnail and the received video information to the SNS; Supporting the number of views, comments, and likes of the uploaded video, and displaying the uploaded video in the related video column of other videos watched by a third party, or in the recommended video column for the third party.
  • a display support unit for supporting the To provide a video playback support system comprising
  • a video playback support system that supports playback of a video uploaded to an SNS acquires materials for creating the video, and uses the acquired materials to create the video and the thumbnail. , receiving input of video information of the created video, uploading the created video and thumbnail, and the received video information to the SNS, and calculating the number of plays, the number of comments, and the number of high ratings of the uploaded video It supports displaying the uploaded moving image in a related moving image column of other moving images viewed by a third party or in a recommended moving image column for the third party.
  • FIG. 1 is a diagram illustrating an overview of a video reproduction support system 1;
  • FIG. 1 is a diagram showing a functional configuration of a video reproduction support system 1;
  • FIG. 4 is a diagram showing a flowchart of a moving image creation process executed by the moving image reproduction support system 1;
  • FIG. 4 is a diagram showing a flowchart of upload processing executed by the video reproduction support system 1.
  • FIG. FIG. 4 is a diagram schematically showing an example of a moving image information input acceptance screen 20; 4 is a diagram showing a flowchart of display support processing executed by the video reproduction support system 1;
  • FIG. 3 is a diagram schematically showing an example of a moving image viewing screen 30 on which a third person views moving images.
  • FIG. 4 is a diagram schematically showing an example of a home screen 40 of an SNS viewed by a third party; 4 is a diagram showing a flowchart of first learning processing executed by the video reproduction support system 1; FIG. 6 is a diagram showing a flowchart of second learning processing executed by the video reproduction support system 1. FIG. FIG. 9 is a diagram showing a flowchart of third learning processing executed by the video reproduction support system 1; FIG. 10 is a diagram showing a flowchart of a modified example of moving image creation processing executed by the moving image reproduction support system 1; FIG. 11 is a diagram showing a flowchart of a modified example of upload processing executed by the video reproduction support system 1;
  • FIG. 1 is a diagram for explaining an overview of a video reproduction support system 1.
  • the video playback support system 1 is a system that supports the number of playbacks of videos uploaded to an SNS having at least a computer 10 .
  • the video playback support system 1 includes a computer 10, an SNS computer having a server function managed by an SNS operator, and a third party terminal possessed by a third party who views videos uploaded to the SNS. , are connected for data communication.
  • the computer 10 acquires materials for creating a moving image (step S1).
  • the materials are, for example, unedited video data, BGM (background music), sounds such as sound effects, and other materials (stock materials (videos, images, sounds, etc.), effects, icons, avatars, etc.) that are used to create videos. be.
  • the computer 10 acquires unedited moving image data, audio, and other materials photographed by the photographer. Also, the computer 10 acquires voice and other materials from an external database or the like.
  • the computer 10 uses the acquired material to create a moving image and a thumbnail (step S2).
  • the computer 10 edits the acquired material and creates a moving image.
  • the method of creating a moving image it suffices to execute processing necessary for creating a general moving image.
  • the computer 10 edits the obtained material and the created moving image to create a thumbnail.
  • the method of creating thumbnails it is sufficient to execute the processing necessary for creating thumbnails of general moving images.
  • the computer 10 receives input of moving image information of the created moving image (step S3).
  • the video information includes, for example, the title, summary, hashtags, table of contents, video links on the timeline, language, subtitle setting, category, display content of comments, and order of comments.
  • the computer 10 receives input of moving image information on the moving image information input receiving screen.
  • the computer 10 uploads the created moving image and thumbnail, and the received moving image information to the SNS (step S4).
  • the computer 10 transmits the created moving image and thumbnail and the received moving image information to the SNS computer.
  • the SNS computer receives and stores them. As a result, the computer 10 uploads the created moving image and thumbnail and the received moving image information to the SNS.
  • the computer 10 supports the number of views, comments, and high ratings of the uploaded video, and puts the uploaded video in the related video column of other videos watched by third parties or the recommended video column for third parties.
  • the display is assisted (step S5).
  • the related video column is a column in which one or more videos related to the video that the third party is viewing on the third party terminal is displayed, and the recommended video column is the column that the third party is displaying on the third party terminal.
  • a column in which one or more videos recommended for the account are displayed on the home screen of the SNS.
  • the computer 10 supports complete viewing, comment support, and high evaluation until the number of plays, the number of comments, and the number of high evaluations reaches a predetermined number, thereby increasing the relevance of the video displayed by the third-party terminal.
  • the third party terminal displays the video supported by the number of plays, the number of comments, and the number of high evaluations in the related video column of the video viewed by the third party or in the recommended video column on the home screen.
  • the video playback support system 1 includes at least a computer 10, the computer 10 being an SNS computer managed by an operator of the SNS, a third party terminal owned by a third party viewing videos uploaded to the SNS, and a public line. It is a system that is connected for data communication via a network 9 such as a network.
  • the video reproduction support system 1 may include an SNS computer, a third party terminal, other terminals and devices, and the like. In this case, the moving picture reproduction support system 1 executes each process described later by any one or a combination of the computers, terminals, devices, etc. included therein.
  • the computer 10 is a computer, a personal computer, or the like that has a server function that supports the number of playbacks of moving images uploaded to the SNS.
  • the computer 10 may be realized by, for example, one computer, or may be realized by a plurality of computers like a cloud computer.
  • a cloud computer in this specification is a computer that uses any computer in a scalable manner to perform a specific function, or includes multiple functional modules to realize a certain system, and uses the functions in a free combination. It can be anything.
  • the computer 10 includes a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a RAM (Random Access Memory), a ROM (Read Only Memory), etc. as a control unit, and a communication unit to communicate with other terminals, devices, etc.
  • a device for enabling communication an acquisition unit 11 that acquires materials for creating videos, an upload unit 12 that uploads videos to SNS, and a display support unit 13 that supports displaying videos uploaded to SNS to a third party. etc.
  • the computer 10 also includes a data storage unit such as a hard disk, a semiconductor memory, a storage medium, or a memory card as a storage unit.
  • the computer 10 also includes, as processing units, various devices that execute various processes, a creating unit 14 that creates moving images and thumbnails, an input receiving unit 15 that receives input of moving image information of moving images, and the like.
  • a material acquisition module by reading a predetermined program by the control unit, in cooperation with the communication unit, a material acquisition module, an upload module, a first support module, a second support module, a third support module, a fourth support module, A display support module, a first collection module, a second collection module, and a third collection module are implemented.
  • the control unit reads a predetermined program, and cooperates with the storage unit to realize a moving image storage module and a learning result storage module.
  • the control unit reads a predetermined program to cooperate with the processing unit to create a creation module, an input reception module, a first learning module, a second learning module, a third learning module, and a material determination module. , a material extraction module, a thumbnail determination module, a keyword determination module, and an additional module.
  • the SNS computer is a computer having a server function managed by the SNS operator. Similar to the computer 10 described above, the SNS computer includes a CPU, GPU, RAM, ROM, etc. as a control unit, and a computer 10 and a third computer as a communication unit.
  • a data storage unit is provided as a storage unit, and various devices for executing various processes are provided as a processing unit.
  • the third party terminal is a terminal device such as a mobile terminal such as a mobile phone, a smart phone, a tablet terminal, or a personal computer possessed by a third party who views videos uploaded to the SNS. , RAM, ROM, etc., a device for enabling data communication with the SNS computer as a communication unit, and various devices for displaying a video viewing screen and inputting and outputting data as an input/output unit.
  • Moving image creation processing executed by computer 10 will be described with reference to FIG. This figure is a diagram showing a flowchart of the moving image creation processing executed by the computer 10 .
  • This moving image creation processing is the details of the material acquisition processing (step S1) and the moving image and thumbnail creation processing (step S2) described above.
  • the material acquisition module acquires materials for creating a moving image (step S10).
  • the materials are unedited moving image data, sounds such as BGM and sound effects, and others (stock materials (moving images, images, sounds, etc.), effects, icons, avatars, etc.) used to create moving images.
  • the material acquisition module acquires unedited video data, audio, and other materials shot by the photographer. Also, the material acquisition module acquires voice and other materials from an external database or the like.
  • the materials acquired by the material acquisition module are not limited to the examples described above, and materials other than these may be acquired as materials, or some of these may be acquired as materials. Also, the material acquisition module may acquire materials pre-stored in the computer 10 itself.
  • the creating module uses the acquired material to create a moving image and a thumbnail (step S11).
  • the creation module edits the obtained material and creates a moving image.
  • the creating module executes processing necessary for creating moving images, such as cutting, trimming, transitions, materials and others, adding and processing telops, characters, symbols, effects, etc., encoding, etc., on unedited moving image data.
  • the creation module uses unedited video data, other materials, created videos, etc. to create thumbnails of videos.
  • the creating module executes processing necessary for creating a thumbnail of a moving image, such as trimming the created moving image, adding and processing materials, other materials, telops, characters, symbols, and images other than materials. Note that the processing related to movie and thumbnail creation executed by the creation module is not limited to the example described above, and can be changed or added as appropriate as long as it is processing required for creating general movies and thumbnails of movies.
  • the moving picture storage module stores the created moving picture and thumbnail (step S12).
  • the moving image storage module associates and stores created moving images, thumbnails, and meta information (eg, file name, creator, date of creation, file size, file type, description, comment, language).
  • meta information eg, file name, creator, date of creation, file size, file type, description, comment, language. Note that the meta information is not limited to the above example, and may be only a part of it, or may include other information.
  • the above is the moving image creation processing.
  • the moving picture reproduction support system 1 uses the moving picture created by this moving picture creating process to execute the process described later.
  • FIG. 10 is a diagram showing a flowchart of upload processing executed by the computer 10 .
  • This upload process is the details of the above-described moving image information input acceptance process (step S3) and upload process (step S4), and is a process performed after the above-described moving image creation process.
  • the input acceptance module accepts input of a moving image to be uploaded (step S20).
  • the input reception module receives input of the moving image created by the above-described moving image creating process on an upload screen (not shown).
  • the input reception module receives a drag-and-drop of a video to be uploaded onto an upload screen, or receives a selection input of a video to be uploaded.
  • the input reception module receives input of moving image information of the created moving image (step S21).
  • the video information includes the title, summary, hashtags, table of contents, video links on the timeline, language, subtitle settings, categories, display contents of comments, order of comments, and the like.
  • the input reception module receives input of video information on the video information input reception screen (see FIG. 5).
  • the moving image information input reception screen will be described with reference to FIG. The same figure is a figure which shows typically an example of a moving image information input reception screen.
  • the moving image information input reception screen 20 has a display field for displaying a moving image whose input to be uploaded has been received and input fields for inputting moving image information.
  • the input reception module displays, in the video display field 21, the video for which the input to be uploaded has been received, the link destination URL (Uniform Resource Locator) of this video, and the file name of the video.
  • the input reception module receives the input of the title of the moving picture in the title column 22.
  • the input reception module receives an input regarding the description of the animation such as an outline of the animation, a table of contents, a animation link on the timeline, and the contents of the animation in the detail column 23 .
  • the input reception module receives input of thumbnails in the thumbnail column 24 .
  • the input acceptance module accepts input such as drag-and-drop or thumbnail selection input to the thumbnail column 24 in which the thumbnail created by the above-described moving image creating process is input.
  • the input reception module receives input of hashtags in the tag field 25 .
  • the input reception module receives a selection input from the language of the moving image displayed by the pull-down menu in the language/caption column 26, and receives the selection input from the subtitle setting displayed by the pull-down menu.
  • the input reception module receives the input of the shooting date and shooting location of the unedited moving image data, which is the raw material for creating this moving image, in the shooting date/location column 27 .
  • the input reception module receives a selection input from among the categories of moving images displayed in the category column 28 by a pull-down menu. Categories are classifications of videos, such as movies, anime, cars, vehicles, music, pets, animals, sports, travel, events, games, blogs, comedy, entertainment, news, politics, how-to, styles, education, science. , technology, non-profit organizations, and social activism.
  • the input reception module receives a selection input from the comment display method displayed by the pull-down menu in the comment column 29, and receives the selection input from the comment arrangement order displayed by the pull-down menu.
  • the input fields included in the video information input reception screen are not limited to the examples described above. For example, if the video is for kids, if it requires age restriction, if it's a paid promotion, playlists, chapter settings, license settings, add subtitles, add end screens, add cards , public settings, and schedule settings. Also, the input fields included in the moving image information input reception screen may be part of the input fields described above.
  • the upload module uploads the created moving image and thumbnail and the received moving image information to the SNS (step S22).
  • the upload module uploads the video, the thumbnail, and the video information to the SNS when the input reception module receives input for uploading the video, the thumbnail, and the video information to the SNS.
  • the upload module sends the video, thumbnail, and video information in association to the SNS computer.
  • the SNS computer receives and stores videos, thumbnails and video information. As a result, the upload module uploads the created moving image and thumbnail and the received moving image information to the SNS.
  • the video playback support system 1 supports the number of playbacks of videos uploaded by this upload process by display support processing, which will be described later.
  • FIG. 10 is a diagram showing a flow chart of the display support processing executed by the computer 10 .
  • This display support process is the details of the above-described display support process (step S5), and is a process performed after the above-described upload process.
  • the first support module supports collection of unique SNS accounts up to a predetermined number (step S30).
  • the first support module supports the collection of unique SNS accounts up to a predetermined number by executing support such as support for creation of a new SNS account and support for collection of existing accounts.
  • the new account creation support executed by the first support module for example, supports input necessary for issuing a new account and supports collection of a plurality of issued unique accounts.
  • the existing account creation support executed by the first support module receives registration inputs for existing accounts from a predetermined site or the like, and supports collection of a plurality of received unique accounts.
  • the method of collecting unique SNS accounts executed by the first support module is not limited to the example described above.
  • the second support module supports the number of complete views until the number of playbacks of the uploaded video reaches a predetermined number by using the unique account that supported the collection (step S31).
  • Complete viewing means watching the video from the beginning to the end in full length without closing the video in the middle.
  • the predetermined number is 300, for example.
  • the second support module supports the input of viewing this video for the unique account that has supported the collection.
  • the second support module supports setting the input operation in the SNS of this unique account to automatically complete viewing of this video, and until the number of playbacks by this unique account reaches a predetermined number, this unique account Help set up for your account.
  • the third support module supports the number of comments until the number of comments on the uploaded video reaches a predetermined number by using the unique account that has supported the collection (step S32).
  • the predetermined number is 100, for example.
  • a third support module supports the input of comments on this video for the unique accounts that have supported the collection.
  • the third support module supports setting the input operation on the SNS of this unique account to automatically comment on this video, and until the number of comments by this unique account reaches a predetermined number, to help set up.
  • the third support module prepares one or more comment contents in advance, appropriately selects from the prepared comments, and supports setting the selected comment to comment on the moving image.
  • the fourth support module uses the unique account that assisted the collection to support the number of high ratings of the uploaded video until the number of high ratings reaches a predetermined number (step S33).
  • the predetermined number is fifty, for example.
  • a fourth support module supports the unique account that has supported the collection to input a high rating for this video.
  • the fourth support module supports setting the input operation in the SNS of this unique account to automatically set this video to be highly rated, and until the number of highly rated by this unique account reaches a predetermined number, this Assist with configuration for unique accounts.
  • the display support module supports displaying the uploaded moving image in the related moving image column of other moving images viewed by a third party or the recommended moving image column for a third party (step S34).
  • the display support module supports displaying the uploaded video in the related video column or the recommended video column of the video displayed by the third party terminal.
  • the related video column is a column in which one or more videos related to the video that the third party is viewing on the third party terminal is displayed, and the recommended video column is the column that the third party is displaying on the third party terminal.
  • a column in which one or more videos recommended for the account are displayed on the home screen of the SNS.
  • the display support module supports the number of plays, the number of comments, and the number of high ratings of the above-mentioned videos, so that the related videos column of other videos viewed by third parties (see FIG. 7), or recommendations to third parties Support display in the video column (see Figure 8)
  • FIG. 7 is a diagram schematically showing an example of a moving image viewing screen on which a third party views a moving image.
  • the video viewing screen 30 is a screen displayed on a third party terminal when a third party views a video.
  • On the video viewing screen 30, an other video 31 and a related video column 32 are displayed.
  • the other moving image 31 is a moving image currently being viewed by a third party.
  • a related video column 32 is displayed near the other video 31 on the video viewing screen 30 .
  • the related moving image column 32 displays the thumbnail, title, playback time, number of playbacks, etc. of the moving image related to the other moving image 31 .
  • the display support module supports the display of the uploaded video in the related video column 32 by supporting the number of plays, the number of comments, and the number of high ratings.
  • the home screen 40 is a screen displayed on a third party terminal when a third party browses the SNS home screen.
  • a recommended movie column 41 is displayed on the home screen 40 .
  • the recommended moving image column 41 displays the thumbnail, title, playback time, number of playbacks, etc. of the moving image recommended by the SNS to a third party.
  • the display support module supports the display of the uploaded video in the recommended video column 41 by supporting the number of plays, the number of comments, and the number of high ratings.
  • the above is the display support processing.
  • the video reproduction support system 1 assists the display of the uploaded video in the related video column 30 and the recommended video column 40, thereby allowing a third party to become interested in the video and actually play the video. provide an opportunity to try to watch As a result, compared to the case where the video is simply uploaded to the SNS, it leads to an increase in opportunities for third parties to view the video, and it is possible to earn the number of views of the video.
  • Learning methods include supervised learning, unsupervised learning, machine learning such as reinforcement learning, convolutional neural networks, recurrent neural networks, and deep learning using long/short-term memory.
  • machine learning based on supervised learning will be described as an example.
  • FIG. 10 is a diagram showing a flowchart of the first learning process executed by the computer 10 .
  • the first collection module collects keywords included in the moving image information of moving images that have been reproduced more than a predetermined number (step S40).
  • the first collection module extracts videos that have been played more than a predetermined number (eg, 300, 1,000, 10,000 times) on the SNS.
  • the first collection module may collect all the videos that satisfy the conditions, or select some of the videos that meet the conditions (within the top few percent of the number of plays, the number of plays is a predetermined number).
  • a moving image or the like that has achieved a predetermined number of playbacks in a predetermined period) may be attached and extracted.
  • a first collection module collects video information of the extracted video.
  • the first collection module collects the title, summary, and hashtags as the moving image information of the extracted moving images.
  • the first collection module may collect moving image information other than these, or may collect a part of the moving image information.
  • the first collection module identifies keywords included in the collected video information.
  • the first collection module identifies symbols, character strings, etc. common to the collected video information as keywords.
  • the first collection module identifies symbols, character strings, etc., common to the collected titles as keywords. Identify each as a keyword.
  • a first collection module collects the identified keywords.
  • the first collection module collects keywords included in the moving image information of moving images that have been reproduced more than a predetermined number.
  • the first learning module learns by associating the collected keywords with the number of reproductions of videos containing the keywords (step S41).
  • the first learning module performs learning using the collected keywords and the number of reproductions of videos containing the keywords in the video information as teacher data.
  • the first learning module learns by associating the keyword in the title with the number of playbacks of the video containing this keyword, and similarly learns the keyword in the other video information. Learn by associating with the number of plays.
  • a first learning module generates a first learning model based on the respective learning results. That is, the first learning module generates a learning model based on the learning results of each of the title, summary, and hashtag as the first learning model.
  • the learning result storage module stores the learning result (step S42).
  • the learning result storage module stores the learning result by storing the generated first learning model.
  • the above is the first learning process.
  • FIG. 10 is a diagram showing a flowchart of the second learning process executed by the computer 10 .
  • the second collection module collects materials included in the moving image information of moving images that have been reproduced more than a predetermined number (step S50).
  • the second collection module like the first learning process described above, extracts videos that have been played more than a predetermined number on the SNS.
  • the second collection module may collect all the moving images that satisfy the conditions, or extract a portion of the moving images with further conditions, as in the first learning process described above. can be
  • the second collection module collects the extracted moving image material.
  • the second collection module collects BGM, sound effects, stock materials, effects, and icons as extracted moving image materials.
  • the second collection module may collect materials other than these, or may collect some of these materials. As a result, the second collection module collects the materials included in the moving images that have been played more than the predetermined number.
  • the second learning module learns by associating the collected material with the number of reproductions of the moving image containing the material (step S51).
  • the second learning module performs learning using the collected materials and the number of reproductions of videos containing the materials as teacher data.
  • the second learning module learns BGM and the number of reproductions of moving images including this BGM, and likewise learns each material and the number of reproductions of moving images including each material for other materials.
  • a second learning module generates a second learning model based on the respective learning results. That is, the second learning module generates learning models based on learning results of BGM, sound effects, stock materials, effects, and icons as second learning models.
  • the learning result storage module stores the learning result (step S52).
  • the learning result storage module stores the learning result by storing the generated second learning model.
  • FIG. 11 is a diagram showing a flowchart of the third learning process executed by the computer 10 .
  • the third collection module collects thumbnails of videos that have been played more than a predetermined number (step S60).
  • the third collection module like the first learning process and the second learning process described above, extracts videos that have been reproduced more than a predetermined number on the SNS. At this time, the third collection module may collect all the moving images that satisfy the conditions, or may further collect some of the moving images that meet the conditions, as in the first learning process and the second learning process described above. You can also extract with .
  • a third collection module collects thumbnails of the extracted videos.
  • a third collection module identifies the content of the collected thumbnails.
  • the third collection module specifies the color usage, character size, wording, the presence or absence of people, the arrangement of characters and images, etc. of the collected thumbnails.
  • a third collection module collects the content of the identified thumbnails. As a result, the third collecting module collects the thumbnails of the moving pictures that have been played more than the predetermined number.
  • the third learning module learns by associating the collected thumbnails with the number of playbacks of moving images of the thumbnails (step S61).
  • the third learning module performs learning using the collected thumbnails and the number of reproductions of moving images of the thumbnails as teacher data.
  • the third learning module learns by associating the content of the identified thumbnail with the number of reproductions of this thumbnail.
  • a third learning module generates a third learning model based on the learning results.
  • the learning result storage module stores the learning result (step S62).
  • the learning result storage module stores the learning result by storing the generated third learning model.
  • FIG. 12 is a diagram showing a flowchart of a modified example of the moving image creation process executed by the computer 10 . Note that detailed descriptions of the same processes as those described above will be omitted.
  • the material acquisition module acquires materials for creating a moving image (step S70).
  • the processing of step S70 is the same as the processing of step S10 described above.
  • the material determination module determines materials that tend to increase the number of reproductions of videos to be uploaded (step S71).
  • the material determination module uses the second learning model generated by the second learning process described above to perform this material determination.
  • the material judgment module judges the speech and others in the second learning model among the materials acquired this time.
  • the material extraction module extracts materials based on the acquired materials and the determined materials (step S72).
  • the material extraction module extracts materials to be used for moving image creation from the currently acquired materials based on the acquired materials and the determined materials.
  • the material extraction module cannot extract a sufficient amount of material for video creation, such as when the acquired material is less than the predetermined number or type, etc., For materials that do not exist, extract them from the collected materials.
  • the thumbnail determination module determines thumbnails that tend to increase the number of times the video to be uploaded is reproduced (step S73).
  • the thumbnail determination module uses the third learning model generated by the above-described third learning process to perform thumbnail determination.
  • the thumbnail judgment module judges the use of color, character size, wording, the presence or absence of a person, the arrangement and balance of images and characters, etc. of thumbnails based on the learning results.
  • the creation module uses the determined material and thumbnail to create a moving image and thumbnail (step S74).
  • the creating module edits the unedited data of the moving image and the extracted material to create the moving image.
  • the creating module executes processing necessary for creating a moving image, such as cutting, trimming, transitioning, adding and processing extracted materials, and encoding, on unedited moving image data.
  • the creation module combines unedited video data, materials extracted from the determined materials, created videos, etc. with the determined thumbnail color usage, character size, phrases, presence or absence of people, image and character placement and balance, etc. Use it to create thumbnails for your videos.
  • the processing related to video creation and thumbnail creation executed by the creation module is not limited to the above example, and general processing required for video creation except for the configuration of using the determined material and using the determined thumbnail If so, changes or additions can be made as appropriate.
  • the moving picture storage module stores the created moving picture and thumbnail (step S75).
  • the processing of step S75 is the same as the processing of step S12 described above.
  • the above is a modified example of the moving image creation process.
  • the moving picture reproduction support system 1 uses the moving picture created by the modified example of this moving picture creating process to execute the process described later.
  • FIG. 10 is a diagram showing a flowchart of a modification of the upload process executed by the computer 10 .
  • a modification of this upload process is a process performed after the modification of the above-described moving image creation process. Note that detailed descriptions of the same processes as those described above will be omitted.
  • the input reception module receives input of a moving image to be uploaded (step S80), and receives input of moving image information of the created moving image (step S81).
  • the process of step S80 is the same as the process of step S20 described above, and the process of step S81 is the same as the process of step S21 described above.
  • the keyword determination module determines a keyword that tends to increase the number of playbacks of the uploaded moving image (step S82).
  • the keyword determination module executes this keyword determination using the first learning model generated by the first learning process described above.
  • the keyword determination module determines keywords in titles, summaries, hashtags, etc. based on the learning results.
  • the addition module adds the determined keyword to the moving image information (step S83).
  • the additional module identifies keywords that are not included in the title, summary, and hashtags based on the determined keywords and the title, summary, and hashtags in the received video information.
  • the additional module recognizes the content of the received title, summary, and hash tag by performing character recognition or the like, and identifies keywords that are not included in these content.
  • the additional module adds a keyword not included in the title to the title, adds a keyword not included in the synopsis to the synopsis, and adds a keyword not included in the hashtag to the hashtag.
  • the add module adds a keyword to the video information input acceptance screen that has accepted the input of video information.
  • the additional module can also be configured to exclude keywords that are unrelated to the content of the video information.
  • the additional module refers to a database or the like in which the correlation between keywords and the correlation between keywords and predetermined character strings is set in advance, and correlates with the keywords that have been input as video information this time.
  • a related keyword or a keyword correlated with a character string received as input as moving image information is added to the moving image information, and a keyword having no correlation is not added to the moving image information.
  • the addition module adds the determined keyword to the moving image information so that the determined keyword is included in the moving image information.
  • the upload module uploads the created moving image and thumbnail and the received moving image information to the SNS (step S84).
  • the processing of step S84 is the same as the processing of step S22 described above.
  • the video playback support system 1 supports the number of playbacks of the video uploaded by the modified example of this upload process by the display support process described above.
  • each process executed by the video reproduction support system 1 has been described above.
  • Each of the processes described above is described as separate processes, but the computer 10 can also be configured to execute a combination of some or all of the processes described above. Further, the computer 10 can be configured to execute the processing even at timings other than the timings described in each processing.
  • the means and functions described above are realized by a computer (including CPU, information processing device, and various terminals) reading and executing a predetermined program.
  • the program may be provided, for example, from a computer via a network (SaaS: software as a service) or provided as a cloud service.
  • the program may be provided in a form recorded on a computer-readable recording medium.
  • the computer reads the program from the recording medium, transfers it to an internal recording device or an external recording device, records it, and executes it.
  • the program may be recorded in advance in a recording device (recording medium) and provided from the recording device to the computer via a communication line.
  • a video playback support system that supports playback of videos uploaded to SNS (for example, video sharing platform, short movie platform, photo/video sharing SNS), Acquisition of materials (e.g., unedited video data, sounds such as BGM and sound effects, and others (stock materials (videos, images, sounds, etc.), effects, icons, avatars, etc.) for creating the aforementioned video a unit (for example, an acquisition unit 11, a material acquisition module); a creation unit (for example, creation unit 14, creation module) that creates the video and thumbnail using the acquired material; Input reception for receiving input of video information of the created video (for example, title, summary, hashtag, table of contents, video link on timeline, language, subtitle setting, category, display content of comment, order of comment) a unit (for example, an input reception unit 15, an input reception module); an upload unit (e.g., upload unit 12, upload module) that uploads the created video and thumbnail and the received video information to the SNS; Supporting the number of views, comments, and likes of the uploaded video, and displaying the
  • a first support unit for example, a first support module that supports collecting unique accounts of the SNS up to a predetermined number;
  • a second support unit (for example, a second support module) that supports the number of completed views until the number of views of the uploaded video reaches a predetermined number, using the unique account that supported the collection;
  • a third support unit for example, a third support module that supports the number of comments until the number of comments on the uploaded video reaches a predetermined number using the unique account that supported the collection;
  • a fourth support unit for example, a fourth support module )and, The moving image reproduction support system according to (2), further comprising:
  • a first collection unit for example, a first collection module
  • a first determination unit for example, a keyword determination module
  • the upload unit includes the determined keyword in the video information and uploads the video information.
  • a first learning unit for example, a first learning module that learns by associating the collected keywords with the number of plays of the video containing the keywords; further comprising The first determination unit determines the keyword based on the learning result.
  • a second collection unit for example, a second collection module
  • a second determination unit e.g., a material determination module
  • the creating unit uses the determined material to create the video and the thumbnail; (1) The moving image reproduction support system described in (1).
  • a second learning unit for example, a second learning module that learns by associating the collected material with the number of times the video containing the material has been played; further comprising The second judgment unit judges the material based on the learning result.
  • a third collection unit for example, a third collection module
  • a third determination unit e.g., thumbnail determination module
  • the creation unit creates the moving image and the thumbnail using the acquired material and the determined thumbnail; (1) The moving image reproduction support system described in (1).
  • a third learning unit for example, a third learning module that learns by associating the collected thumbnails with the number of times the videos of the thumbnails have been played; further comprising the third determination unit determines the thumbnail based on a learning result;
  • the moving image reproduction support system according to (10).
  • a video playback support method comprising:
  • a step of acquiring materials for creating the moving image for example, step S10); a step of creating the video and thumbnail using the acquired material (for example, step S11); a step of receiving input of moving image information of the created moving image (for example, step S21); a step of uploading the created video and thumbnail and the received video information to the SNS (for example, step S22); Supporting the number of views, comments, and likes of the uploaded video, and displaying the uploaded video in the related video column of other videos watched by a third party, or in the recommended video column for the third party.
  • a step (for example, step S34) of assisting in causing A computer readable program for executing
  • Video Playback Support System 9 Network 10 Computer 20 Video Information Entry Screen 21 Video Display Field 22 Title Field 23 Details Field 24 Thumbnail Field 25 Tag Field 26 Language/Caption Field 27 Shooting Date/Location Field 28 Category Field 29 Comment Field 30 Video Viewing screen 31 Other videos 32 Related videos column 40 Home screen 41 Recommended videos column

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  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Television Signal Processing For Recording (AREA)

Abstract

Le problème décrit par la présente invention est de permettre d'augmenter efficacement le nombre de reproductions d'une image animée mise à jour auprès d'un SNS. La solution de l'invention porte sur un système pour promouvoir la reproduction d'une image animée, destiné à promouvoir la reproduction d'une image animée mise à jour auprès d'un SNS, qui acquiert du matériel avec lequel l'image animée doit être créée, crée l'image animée et une vignette à l'aide du matériel acquis, accepte la saisie d'informations d'image animée de l'image animée créée, téléverse l'image animée et la vignette créées ainsi que les informations d'image animée acceptées vers le SNS, promeut le nombre de reproductions de l'image animée téléversée, le nombre de commentaires, et le nombre d'évaluations élevées, et aide à amener l'image animée mise à jour à être affichée dans une colonne d'images animées associées d'une autre image animée visualisée par une tierce personne ou à être affichée dans une colonne d'images animées recommandées pour la tierce personne.
PCT/JP2021/036700 2021-10-04 2021-10-04 Système pour promouvoir la reproduction d'une image animée, procédé pour promouvoir la reproduction d'une image animée, et programme WO2023058101A1 (fr)

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JP6812586B1 (ja) * 2020-03-27 2021-01-13 株式会社ドワンゴ 動画編集装置、動画編集方法、およびプログラム
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