JP2005235027A - Information processing system, information processing method and computer program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To suitably support business requiring ideas when producing content or the like. <P>SOLUTION: An information processing system has a relational database having an algorithm for generating a new image. Since the database has an expected value as a parameter, the expected value is varied with respect to a user's selection behavior, and presentation content of data from the database is varied. In addition, the user newly defines an operation procedure or the like which is carried out for linking images, and registers it with the database. As the result, this system supports ideas and a production behavior for finalizing linked images developed along a certain time axis. <P>COPYRIGHT: (C)2005,JPO&NCIPI

Description

  The present invention relates to an information processing system and information processing method for supporting a user's application work, and a computer program, and more particularly to an information processing system and information processing method for supporting work requiring an idea at the time of content production. And a computer program.

  More specifically, the present invention relates to an information processing system, an information processing method, and a computer program for supporting a work of completing one work by sequentially connecting contents created and edited along a time axis. In particular, the present invention relates to an information processing system and information processing method and a computer program for supporting a work of sequentially thinking and connecting contents along a time axis in story telling such as creation of a scenario or a picture book.

  With the recent development of computing technology, computers have penetrated deeply into offices and general households. Coupled with this, various applications in industrial activities and daily sliding have received computer support.

  In the old days, routine tasks such as document creation / editing, document management, spreadsheets, and communication were supported by computer processing. More recently, it has become possible to receive the benefits of computer processing even in highly intelligent activities such as ideas when creating content.

  In storytelling such as scenario and picture book creation, if it is possible to support intellectual work such as sequentially thinking and connecting content along the time axis using computer resources, shortening the production time Reduction of production cost can be realized.

  For example, there has been proposed an animation creation device that enables creation of motion animation by selecting keywords such as motion meaning, motion part and motion, and speech associated with motion (for example, Patent Document 1). checking).

  In this case, the animation creating apparatus has a database of keywords, presents and previews an operation pattern in response to a user input, and the user can select a desired one. Therefore, even a user unfamiliar with animation creation can produce a loop animation relatively easily.

  However, in this animation creation device, the operation pattern corresponding to the keyword is simply selected, and the selection method is fixed, and how it is developed when the selected operation pattern is connected. It does not deal with such matters as. In other words, it cannot be applied to the idea / production support in storytelling that develops along the time axis.

JP-A-10-134202

  An object of the present invention is to provide an excellent information processing system, information processing method, and computer program capable of favorably supporting a work requiring an idea at the time of content production.

  A further object of the present invention is to provide an excellent information processing system and information processing capable of suitably supporting the work of completing one work by sequentially connecting contents created and edited along the time axis. It is to provide a method and a computer program.

  A further object of the present invention is to provide an excellent information processing system and information processing capable of suitably supporting the work of sequentially thinking and connecting contents along a time axis in story telling such as creation of scenarios and picture books. It is to provide a method and a computer program.

The present invention has been made in consideration of the above problems, and the first aspect of the present invention is an information processing system that supports the conception or production of content that connects a plurality of media data,
A relational database storing relational data describing the relation between the original media data and the media data linked to the original media data;
For each media data, a media database that stores the media data that links the media data together with data related to the media data that is linked to the media data;
A connection direction input means for a user to input a direction for connecting new media data to original media data;
In accordance with the direction input by the connection direction input means, candidate relational data relating the original media data and new media data are extracted from the relational database and presented as recommended relational data. Recommended relationship selection means,
Media data processing means for generating new media data using the user-selected one of the presented relational data;
Means for concatenating new media data in the input direction of the original media data and storing it in a media database;
It is an information processing system characterized by comprising.

  However, “system” here refers to a logical collection of a plurality of devices (or functional modules that realize specific functions), and each device or functional module is in a single housing. It does not matter whether or not.

  The information processing system according to the present invention can handle an image as media data. In this case, the relational data includes an image processing algorithm applied to the original image in order to generate a new image to be connected.

  The relational database manages expected values that use each relational data, and the recommended relation selecting means selects relational data that should be recommended based on the expected values.

  The information processing system according to the present invention may further include media editing means for further editing new media data generated from the original media data using the related data.

  Further, an action storage unit that stores an action added to the media data by the media editing unit may be further provided. Then, the action saved in the action saving means can be registered in the relational database as new relational data so that it can be reused in the next and subsequent media editing.

  In such a case, the relation data registration means may register relation data defined only by actions added to the media data. Alternatively, relationship data that is defined by combining the relationship data used for the original media data and the action added to the newly generated media data may be registered.

  Here, in the relational database, the expected value may be changed according to the number of times the relational data is selected.

  Alternatively, in the relational database, in the process of concatenating new media data from the reference media data that is currently focused on, similar media that are similar to the reference media data among the past media data generated in the past are stored. Data may be searched, and the expected value of the related data used when the new media data is linked to the similar media data may be changed.

  Alternatively, past media data generated using the same relationship data as that used when concatenating the reference media data to the original media data is searched, and a new media You may make it change the expected value of the related data used when connecting data.

  Or, search for similar media data similar to the reference media data among the past media data generated in the past, and the same relationship as the relationship data used when linking the reference media data to the original media data Used to determine whether data has been used in the past, and to link new media data with similar media data that has a similarity greater than or equal to a predetermined value among similar media data generated using the same relationship data The expected value of the related data may be changed.

  Or you may make it change the expected value of the related data used in the past in order to connect media data in the same connection direction as the connection direction input with respect to the reference media data.

The second aspect of the present invention provides a computer program described in a computer-readable format so as to execute processing on a computer system to support the conception or production of content that connects a plurality of media data. A program,
A relational data management step for managing relational data describing the relation between the original media data and the media data linked thereto;
A media management step for storing each media data together with the media data concatenating the media data and the relationship data with the media data linked to the media data;
A connection direction input step in which a user inputs a direction in which new media data is connected to original media data;
A recommended relationship selection step of searching for candidate relationship data relating the original media data and the new media data in accordance with the direction input in the connection direction input step, and presenting it as relationship data to be recommended ,
A media data processing step for generating new media data using a user-selected one of the presented relational data;
A media editing step that further edits the new media data generated from the original media data using the relationship data;
An action storage means step for storing an action added to the media data in the media editing step;
A relation data registration step of registering the action stored in the action storage step in the relation database as new relation data;
A computer program characterized by comprising:

  The computer program according to the second aspect of the present invention defines a computer program described in a computer-readable format so as to realize predetermined processing on a computer system. In other words, by installing the computer program according to the second aspect of the present invention in the computer system, a cooperative action is exhibited on the computer system, and the information processing according to the first aspect of the present invention is performed. The same effect as the system can be obtained.

  According to the present invention, it is possible to provide an excellent information processing system, information processing method, and computer program that can favorably support a work requiring an idea at the time of content production.

  In addition, according to the present invention, an excellent information processing system and information that can suitably support the work of completing one work by sequentially connecting content that has been created and edited along the time axis. A processing method and a computer program can be provided.

  In addition, according to the present invention, an excellent information processing system and information capable of suitably supporting the work of sequentially thinking and connecting contents along a time axis in story telling such as creation of a scenario or a picture book A processing method and a computer program can be provided.

  According to the present invention, a relational database having an algorithm for generating a new image is provided, and this database has an expected value as a parameter. The presentation contents of data from can be changed. In addition, the user can newly define a work procedure or the like to be performed when images are connected, and can be registered in the database. As a result, it is possible to favorably support an idea / production act of finishing a connected image developed along a certain time axis.

  In short, according to the present invention, it is possible to obtain a support effect such as presenting a hint for idea generation or creating a draft for production based on an image (media data). In addition, each media data and editing contents under production can be stored and registered. In addition, by arranging the image geometrically and spatially, it is possible to obtain the effect of grasping the image and efficient browsing. Further, it becomes easy to visually and intuitively grasp the connection direction and the number of connections from the shape of the image. In addition, by presenting recommended editing content based on past history, it is possible to obtain an effect of expanding and summarizing ideas.

  Other objects, features, and advantages of the present invention will become apparent from more detailed description based on embodiments of the present invention described later and the accompanying drawings.

  Hereinafter, embodiments of the present invention will be described in detail with reference to the drawings.

A. Hardware Configuration of System FIG. 1 schematically shows the configuration of an information processing apparatus that realizes the idea / production support system according to the present invention.

  A CPU (Central Processing Unit) 101 that is a main controller executes various applications under the control of an operating system (OS). In the present embodiment, the CPU 101 can execute, for example, an idea / production application program that supports an idea at the time of producing content such as an image or production.

  As illustrated, the CPU 101 is interconnected with other devices (described later) by a bus 108.

  The main memory 102 is a storage device used for loading a program code to be executed by the CPU 101 and temporarily storing work data of the execution program. For example, a semiconductor memory such as a DRAM (Dynamic RAM) Is used. For example, an idea / production support application is loaded into the main memory 102 as an execution program. In addition, image content being produced, parameter data used in the production process, and the like are temporarily stored in the main memory 102 as work data.

  A ROM (Read Only Memory) 103 is a semiconductor memory that permanently stores data. For example, a self-diagnostic test (POST: Power On Self Test) at startup and a program code for hardware input / output (BIOS: Basic Input / Output System) is written.

  The display controller 104 is a dedicated controller for actually processing drawing commands issued by the CPU 101. The drawing data processed in the display controller 103 is temporarily written in, for example, a frame buffer (not shown) and then output on the screen by the display 111.

  The display screen of the display 111 generally has a role of visually feeding back to the user the contents input from the user, the processing result thereof, or an error or other system message. Further, in the present embodiment, the display screen of the display 111 is used for creating / editing image content being produced, image content related to the image content being created, and new image content from the related image content. It is used to display and output tools, list screens of image contents created so far.

  The input device interface 105 is a device for connecting user input devices such as a keyboard 112 and a mouse 113 to the interactive device 100.

  The keyboard 112 and the mouse 113 have a role of capturing user inputs such as data and commands into the system. In this embodiment, in order to input an instruction command for producing / editing media data such as an image, or to input an instruction for connecting to the latest media data at the time of new content production used.

  The network interface 106 can connect the system 100 to a local network such as a LAN (Local Area Network) or even a wide area network such as the Internet according to a predetermined communication protocol such as Ethernet (registered trademark).

  On the network, a plurality of host terminals (not shown) are connected in a transparent state to construct a distributed computing environment. On the network, distribution services such as software programs and data contents can be provided. For example, it is possible to download ideas, production applications, programs, etc. that support ideas and production support during content production via the network. In addition, content created using an idea / production support application can be distributed and distributed to other host devices via a network.

  The external device interface 107 is a device for connecting an external device such as a hard disk drive (HDD) 114 or a media drive 115 to the operation information processing apparatus 100.

  The HDD 114 is an external storage device in which a magnetic disk as a storage carrier is fixedly mounted (well-known), and is superior to other external storage devices in terms of storage capacity and data transfer speed. Placing the software program on the HDD 114 in an executable state is called “installation” of the program in the system. Normally, the HDD 114 stores program codes of an operating system to be executed by the CPU 101, application programs, device drivers, and the like in a nonvolatile manner. For example, an idea / production application program for supporting the idea of media data and production at the time of content production can be installed on the HDD 114. Further, content created using an idea / production support application may be stored on the HDD 114.

  The media drive 115 is a device for loading portable media such as CD (Compact Disc), MO (Magneto-Optical Disc), DVD (Digital Versatile Disc), and accessing the data recording surface.

  The portable media is mainly used for the purpose of backing up software programs, data files, and the like as data in a computer-readable format, and for moving them between systems (that is, including sales, distribution, and distribution). For example, it is possible to physically distribute and distribute an idea / production application program that supports the idea and production of media data at the time of content production among a plurality of devices using these portable media. In addition, portable media can be used for exchanging media data produced using an idea / production support application and content composed of media data with other devices.

  As shown in FIG. 1, an example of the information processing apparatus 100 is a compatible computer or a successor of an IBM personal computer “PC / AT (Personal Computer / Advanced Technology)”. Needless to say, a computer having another architecture can be applied as the program processing apparatus 100 according to the present embodiment.

B. Functional Configuration of System The idea / production support system according to the present invention contemplates / creates a new image (media data) from a starting image (media data), and connects these images along a time axis. By doing so, it supports the work of storytelling, such as creating scenarios and picture books.

  The idea / production support system according to the present invention includes a relational database that stores relational data describing a relation between an original image as a starting point and an image connected to the original image. The relationship data has an algorithm for generating a new image from the original image and an expected value using the relationship data. And with respect to a user's selection action, an expected value is changed sequentially and the presentation content of the data from a database is changed. The algorithm here refers to the processing procedure applied to the starting image in order to generate a new image. However, there is also an aspect of describing the relationship connecting the starting image and the new image. Have.

  In the work procedure to be performed when images are linked, when starting a new image (media data) from the image (media data) as a starting point, the starting image (media data) ), A means for inputting the direction in which the user connects, a means for selecting a relationship recommended by the system from the relational database for the input connection direction, and a starting point using the corresponding algorithm for the user input. A means for processing the image (media data), a means for presenting the new image (media data) created as a result to the user, and a history of ideas started by such connection direction input Provide a means to

  Here, the direction in which the user connects to the starting image (media data) is determined by the notation shape of the media data, the connection angle and distance, and the number of connections (see FIG. 2). ). However, the notation shape of the media data mentioned here does not necessarily mean only a physical shape, but may mean a logical shape.

  Further, when selecting a relationship recommended by the system (that is, an algorithm for generating a new image) from the relationship database, a relationship to be recommended is determined according to an expected value managed in the relationship database. Here, the expected value is determined by the following procedure, for example.

(1) Number of selected relational data (2) Matching of past relations (images, media data) (3) Matching of relational data used in the past

  Further, the user is allowed to further edit the screen on which the new image (media data) created as a result is presented. In this case, the relationship between the starting image and the new image, that is, the algorithm for generating the image is newly defined, and this can be additionally registered in the relationship database.

  FIG. 3 schematically shows a functional configuration of the idea / production support system 10. As shown in the figure, the idea / production support system 10 includes a connection direction input unit 11, a recommended relationship selection unit 12, a recommended relationship display unit 13, a use relationship selection unit 14, an image processing unit 15, and an image. The display unit 16, the image editing unit 17, the action storage unit 18, the relational data registration unit 19, the relational database 20, and the media database 21 are configured. The illustrated configuration is actually realized by the cooperative operation of the idea / production support application executed by the CPU 101 and each hardware component.

  The idea / production support system 10 according to the present invention connects a new image (media data) to a starting image (media data) in a connecting direction designated by the user. By connecting these images sequentially along the time axis, the work of storytelling such as creation of scenarios and picture books is supported. The connecting direction differs depending on the notation shape of the media data. However, for the sake of simplicity, the image as the media data is a rectangle, and four connecting directions, top and bottom and left and right, are defined. It shall be.

  Here, the new image is generated by applying a predetermined algorithm such as image processing to the starting image. In the present idea / production support system 10, the relationship between the starting image and a new image connected thereto is defined by a processing algorithm applied at the time of connection. The relationship database 20 manages the relationship used when sequentially generating and connecting new images from the starting image, that is, the processing algorithm, together with the expected value that activates the relationship when connected.

  FIG. 4 shows a data structure for managing the relationship between the original image (media data) and the new image (media data) to be connected in the relationship database 20. As shown in the figure, an entry is provided in the relational database 20 for each relation used at the time of connecting images, and each entry uses the relation name, the content of the processing algorithm applied to the origin image, and the relation. It has a field to write expected value. In the illustrated example, a processing algorithm named “Zoom In”, which is related to “Zoom In”, is stored in the relational database 20 together with its expected value 35.

  Note that when a new image is generated from the starting image, the user can define a new relationship between images using an existing processing algorithm or the like. It is additionally registered. Each time the relation data is used, the expected value of each entry is updated.

  In addition, the media database 21 manages images (media data) that are sequentially generated by applying a predetermined algorithm such as image processing to the starting image.

  FIG. 5 shows a data structure for managing each image (media data) in the media database 21. In the media database 21, an entry is provided for each image (media data) handled in the system 10. In each entry, the storage destination (reference destination) address of the entity of the media data, the position from the starting point, the connection direction and the image ID of the next image to be linked to itself, the relationship of the original image to be linked to itself A field for storing the connection direction, the image ID, and the relationship used is provided. In the example of the media database entry shown in the figure, the image (media data) stored in \\ aaa \ bbb \ cc is located at the position (x, y) from the starting point, and upward from itself. Describes that the image generated with the relationship “Zoom In”, the image generated with the relationship “Zoom Out” in the downward direction, and the image generated with the relationship “Right Pan” in the right direction are connected. ing.

  In the media database 21, scenarios and picture books, etc., are managed in units of story telling units, that is, groups of images (media data) that continue to be connected, and images are referenced only within the same image group. Allow. Of course, the system 10 can also be constructed to allow cross-reference of media data between different image groups.

  Returning to FIG. 3 again, the configuration of the idea / production support system will be described. The connection direction input unit 11 determines the direction in which an image (media data) to be generated next is connected to the image (media data) as a starting point based on an instruction from the user via a mouse or cursor keys. input.

  The recommended relationship selection unit 12 has relationship data (that is, processing algorithm) to be used when connecting a new image in the connection direction input in the connection direction input unit 11 in each entry from the relationship database 20. Select based on expected value. The recommended relationship display unit 13 displays and outputs the contents of the entry retrieved from the relationship database 20 by the recommended relationship selection unit 12 on a display screen or the like.

  Here, when the recommended relationship selection unit 12 picks up two or more entries as candidates, the recommended relationship display unit 13 displays and outputs them, and then the usage relationship selection unit 14 automatically applies them automatically or based on a user instruction. Identify the relationship data that should be done.

  The image processing unit 15 applies image processing to the original image by applying a processing algorithm corresponding to the selected relationship. The image display unit 16 displays and outputs the image processed by the image processing unit 15 on a display screen or the like.

  The image editing unit 17 further performs image editing processing on the new image displayed and output by the image display unit 16 after the related data is applied based on an instruction from the user.

  The action storage unit 18 holds the editing action used in the image editing unit 17 for editing the image after application of the relation data. The relationship data registration unit 19 integrates the relationship data applied to the lower image and the edit action used at the time of image editing, defines new relationship data, and registers this in the relationship database 20. Do.

C. Processing Procedure for Idea / Production Support Next, the processing procedure in the idea / production support system 10 according to the present invention will be described in detail.

  FIG. 6 shows a processing procedure at the time of image creation in the form of a flowchart.

  First, as an initial setting, the user prepares an image as a starting point and sets its notation shape (step S1).

  Next, a direction in which an image (media data) to be generated next is connected to an image (media data) serving as a starting point is selected (step S2). Which direction of which image is selected is input to the connection direction input unit 11.

  Next, the display probability is calculated from the expected value in the relationship database 20, and the recommended relationship (that is, processing algorithm) is selected (step S3). That is, the recommended relationship selection unit 12 calculates an expected value from the direction input by the connection direction input unit 11, the media database 21, and the relationship database 20. Details of the expected value calculation method will be described later.

  Next, the recommended relationship display failure 13 displays and outputs the relationship data selected in the preceding step S3 on the display screen or the like as the relationship data recommended by the system 10 (step S4).

  The user selects one suitable for obtaining a desired linked image from one or more related data displayed on the screen (step S5). Then, the selected relationship data is input to the use relationship selection unit 14.

  Based on the input, the usage relationship selection unit 14 searches the relationship database 20 and retrieves the corresponding processing algorithm. Then, a new image is generated from the original image using the selected processing algorithm (step S6). Then, the image display unit 16 outputs the newly generated image on the screen.

  The user can further perform image editing processing on the new image displayed on the screen (step S7). The image editing processing procedure will be described later.

  In this way, when the user generates a new image, the user can define new relationship data between the images using an existing processing algorithm or the like. By additionally registering these newly defined relational data in the relational database 20 (step S8), these can be reused at the time of next image generation or editing. The procedure of the related data registration process will be described later.

  As described above, a new image (media data) can be generated using the algorithm of the recommended relation data selected by the user. Add, that is, edit the image. FIG. 7 is a flowchart showing the image editing processing procedure performed in step S7 of the flowchart shown in FIG.

  The image editing unit 17 performs editing processing on the image generated from the original image in step S6 (step S11). The editing process itself is performed according to a user operation via a predetermined GUI, for example. The result of image editing is output to the screen by the image display unit 16.

Here, the action (edit contents) performed by the user in the image editing process is stored in the action storage unit 18 (step S12). Examples of actions include enlarging around the point (x, y) and moving (x ₁ , y ₁ ) to (x ₂ , y ₂ ) (parallel movement).

  Then, upon input from the user to end the editing process (step S13), the entire processing routine is ended.

  As described above, the user can further edit the image of the linked image generated from the original image using the relationship data. Then, the contents that the user has made by editing work can be registered as new relation data. In this case, it is also possible to define the new relation data by combining the relation data used and the contents that the user has made by editing.

  FIG. 8 shows a processing procedure for registering the newly defined relationship in the relational database 20 at the time of image editing performed in step S8 of the flowchart shown in FIG. 6 in the form of a flowchart.

  The relation data registration unit 19 confirms with the user via the GUI or the like whether or not the newly defined action (edit contents) should be registered in the relation database 20 (step S21).

  If the user wishes to register, the user is further inquired whether or not the relational data selected by the user in step S5 and the action stored in the action storage unit 18 should be registered. (Step S22).

  If the answer from the user is affirmative, a processing algorithm that integrates the relationship data selected by the user in step S5 and the action stored in the action storage unit 18 is defined as new relationship data. It is additionally registered in the database 20 (step S23).

  If the answer from the user is negative in step S22, the user further inquires whether or not he / she wants to register the edit difference (step S24). If the answer to this inquiry is affirmative, all actions stored in the action storage unit 18 or any of them are additionally registered in the relational database 20 as new relational data. (Step S25).

D. The data structure in the relational data relational database 20 has already been described with reference to FIG. Here, the structure of the relation data will be described in more detail.

  The relation data includes a relation name, an algorithm, and an expected value (or usage frequency), and is preset in the relation database 20.

  The algorithm for defining the relational data is based on viewpoint movement (up / down / left / right), passage of time, change in size (enlargement / reduction), change in thickness (touch, trace), copy and paste, etc. , Other actions, and combinations with other actions.

  When a new image is generated for the original image, recommended relationship data is presented to the user based on the expected value. When the relation data is selected, an algorithm associated with the relation data is applied to the original image, and a result is automatically generated. Of course, the application of the relational data can be tried any number of times until the user likes (consents) the newly generated image.

  In this way, by selecting relational data and applying a corresponding algorithm to the original image, an image to be connected to the original image is automatically generated. Here, the user can further perform image editing on the generated image. Contents edited by the user can be added to the used relational data, or only the edited contents added can be additionally registered in the relational database 20 as a new algorithm.

  Every time you use related data in the idea / production support, it is reflected in the expected value parameter. Then, the recommended relationship selection unit 12 presents relationship data having a high expected value (or a high use frequency) or a low value from the next time.

  In the idea / production support according to the present invention, the relationship between images that have been repeatedly connected in the past is scanned and matched to present relevant data that seems appropriate. When there are multiple connections between images, the presented relationship data is presented not only from the back of the currently referenced image but also depending on the other connection.

  FIG. 9 illustrates a processing procedure for scanning a relationship between connected images and specifying appropriate relationship data by matching.

  Assume a scene in which a reference image is currently focused and an image to be linked to the reference image is to be created. In the illustrated example, related data is applied to the reference image A, and a new image to be connected to the reference image A is generated.

  In this case, a search is made in the media database 21 and an image A ′ similar to the current reference image A is found in the same image group constituted by repeated connection so far.

  Then, in the past, relation data used when connecting the images in the similar reference image A ′ is extracted from the media database 21. When the similar reference image A ′ has a plurality of connection directions, for example, relation data corresponding to the connection direction input to the current reference image A may be extracted. In the illustrated example, it is assumed that relation1 is extracted as the relationship data, the recommended relationship selection unit 12 extracts the information, and the recommended relationship presentation unit 13 presents the contents to the user.

  Here, taking into account the image from which the reference image A is generated, that is, the image B connecting the reference image A, those similar to the connection flow of image B → image A are included in the same image group. Scanning and matching processing may be performed to narrow down related data to be applied to the reference image A.

  FIG. 10 illustrates another example of a processing procedure for scanning a relationship between images to be connected and specifying appropriate relationship data by matching.

  In the idea / production support according to the present invention, as described above, the history and order of the relationship data used in the past are scanned and the relationship data deemed appropriate are presented.

  Here, when there are a plurality of connections between images in the same image group, the relationship data to be presented is narrowed down not only from the back of the current reference image but also depending on the other relationship. Is done.

  In the example shown in FIG. 10, when the relation data is applied to the reference image A and an image to be connected to the reference image A is newly generated, the reference image A is applied to the original image to connect the reference image A. Relevant data is retrieved from the media database 21. In the example shown in the figure, it is assumed that the reference image is generated by applying the relation data relative1 to the original image.

  For example, the past relation data is scanned in the same image group, and the relation data relation1 is used to search the original image generated using relation1. Then, in the illustrated example, the similar reference images A ′ connected using relation1 are found. Then, the similar reference image A ′ is searched in the media database 21, and it is confirmed that the relation data used for connecting a new image to the similar reference image A ′ is relation2.

  In such a case, the recommended relationship presentation unit 13 can present the relationship data relation2 used after relation1 as a recommendation to be recommended.

  Furthermore, paying attention to the fact that the relational data relation3 is used before the relational data relation1 is used to connect the reference image A, an object similar to the connection flow of relation3 → relation1 is included in the same image group. The related data to be applied to the reference image A may be narrowed down by performing scanning and matching processing.

  Below, the example which applied the relational data with respect to the original image and produced | generated the connection image is demonstrated.

  FIG. 11 shows an example in which a connected image is generated by applying relation data having “right pan” as a processing algorithm to a landscape image as an original image. In such a case, the right edge image data (RGB, coordinates) of the original image and the horizontal line element of the entire original image are scanned, and the horizontal line element of the entire original image is retained and extended. The connected image is generated by dragging the image data value at the right end of the original image.

  FIG. 12 shows an example in which a concatenated image is generated by applying a processing algorithm called the passage of time to a landscape image as an original image. By analyzing the original image, the metaphor (color, silhouette) of the tree is discriminated, and metadata such as “use tree as part” is added. For example, when “night” is applied as the passage of time, the background tone is changed. In addition, when “seasonal change” is applied as the passage of time, the color of the leaf portion is changed to make the autumn leaves. In addition, when “weather change” is applied as the passage of time, rain (or snow, fog, etc.) is combined with the background. Such a background may be prepared as a template.

  FIG. 13 shows an example in which a connected image is generated by applying a processing algorithm called “change in size” to the original image. In such a case, the user selects an area to be enlarged from the door image. In general, when an image is enlarged by copying a region, the image becomes dull and blurry. However, by performing processing such as prediction and interpolation together with enlargement, the sharpness is maintained (the number of pixels to be blurred is matched with the original image). Such). Depending on the LOD (switching the object to be displayed according to the distance), any number of different images may be provided.

  FIG. 14 shows an example in which a connected image is generated by applying a processing algorithm that gives a change in thickness to the original image. In this case, a line segment included in the original image is extracted, and processing such as tracing is performed by the vector analysis to thicken the image.

  FIG. 15 shows another example in which a connected image is generated by applying a processing algorithm that gives a change in thickness to the original image. In the example shown in the figure, a palm is shown in the original image. In such a case, processing such as detecting the outline of the palm from the original image and changing the thickness or touch of the line is performed.

  FIG. 16 shows an example in which a connected image is generated by applying a processing algorithm that increases the number of objects included in the original image. In this case, the shape of the object included in the original image is sampled, the size with respect to the screen is determined, and a new image is generated by repeating copy and paste of the same object in the image frame a plurality of times.

E. Calculation of Expected Value In the idea / production support system 10 according to the present invention, when a new image is generated from an original image, the recommended relationship selection unit 12 uses the relationship data to be applied to the original image as a relationship. Retrieve from database 20. Since the relational database 20 has the expected value as a parameter, the expected value can be changed in response to the user's selection action, and the data presented from the database can be changed (as described above). Below, the calculation process for changing an expected value based on a user's selection act is demonstrated.

(1) Control according to the selected number of times As a basic expected value calculation method, the expected value of the selected relational data is added by a predetermined value α or subtracted by α according to the number of times selected by the user. Give direct changes to the database. By such an expected value operation, it is possible to present related data that is frequently used or low in the next operation.

(2) Temporary changes due to image matching For example, an image for which a connected image is to be generated is used as a reference object, an image similar to this reference image is searched in an image group, and the relationship data held by the similar image is expected. Values can be manipulated.

  FIG. 17 shows an example of expected value operation in this case. Assume that image A is a reference image, and this reference image A is a connected image generated using images B and C as original images. Assume that an image A ′ is found as an image similar to the reference image A in the same image group. The similar image A ′ is a connected image generated using the image B ′ and the image C ′ as original images. In this case, an operation for changing the expected value is added to each relational data B ′ → A ′ and C ′ → A ′ of the similar image A ′.

  FIG. 18 shows an operation example for changing the expected value for the relational data. In the illustrated example, expectation values of 50, 40, and 30 are given to relational data used in each of the upper (UP), right (RIGHT), and lower (DOWN) connection directions for a certain image. And Here, when this image is detected as a similar image having a similarity of 30 with respect to the reference image, it is used in the connection direction of up (UP), right (RIGHT), down (DOWN), and left (LEFT). 30 points corresponding to the degree of similarity are added to the relationship data.

  FIG. 19 shows a processing procedure for temporarily changing the expected value of the relational data by image matching in the form of a flowchart.

  First, the similarity with the reference image is calculated for all images in the same image group (step S31). The image similarity is calculated based on, for example, pixel parameters such as hue, brightness, and drawn contents (image recognition and keywords).

  Then, an image whose similarity is equal to or greater than a certain threshold is selected as a similar image to the reference image (step S32).

  Then, the expected values of all the relational data possessed by each selected similar image are changed according to the procedure described with reference to FIG. 18 (step S33).

(3) Matching of used relational database Expected values can be manipulated based on the matching result of relational data used in the same image group.

  FIG. 20 shows an example of the expected value operation in this case. Assume that the image A is a reference image, the reference image A is a connected image generated using the image B as an original image, and the image B is a connected image generated from the image C. Then, it is determined whether or not the same relation data used for generating the reference image A from the original image B is used in the same image group. In the illustrated example, it is assumed that it is detected that the same relation data is used to generate the image A ′ from the image B ′. In such a case, an operation for changing the expected value of the relational data used for generating the connected image from the image A ′ is added.

  FIG. 21 shows an operation example for changing the expected value for the relational data. In the illustrated example, it is assumed that the relation data (relation data name) used to generate the reference image is “ZoomIn”, and the relation database 20 is searched and generated using this relation data within the image group. Find out the image that was created. Then, all related data that this image has (that is, used for image connection) is selected. In the illustrated example, the extracted image has relationship data in each of the upper (UP), right (RIGHT), and lower (DOWN) connection directions, and given expected values of 50, 40, and 30, respectively. To do. Then, an operation is performed in which the expected value of each relational data is uniformly given by 10 points.

  FIG. 22 shows a processing procedure for temporarily changing the expected value of the relationship data by matching the used relationship database in the form of a flowchart.

  First, it is determined whether or not the same relation data is used in the same image group for all the relation data used for generating the reference image (step S41).

  If it is detected that the same relationship data is used, the relationship data held in the image generated by the relationship data is selected (step S42).

  Then, points are given uniformly to the expected value of each relational data selected in this way (step S43).

(4) Matching including image and related data The expected value can be manipulated by matching including the image and related data in the same image group.

  FIG. 23 shows an example of expected value manipulation in this case. Whether the same relational data used to search for images similar to the reference image in the same image group and to generate the reference image (ie, concatenate to the original image) is used in the same image group Determine. Then, images having similarities that are equal to or higher than a threshold among images generated by the same relation data are selected. An operation is added to the expected values of all the relational data from the similar images selected in this way.

  In the example shown in FIG. 23, the images having the similarity 30 with the reference image are connected by the same relation data “ZoomIn”, so that they are selected as similar images. This similar image is given expected values of 50, 40, and 30 for relation data A, B, and C used in the upper (UP), right (RIGHT), and lower (DOWN) connection directions, respectively. Suppose that In this case, an operation is performed in which the expected value is uniformly given to each of the relationship data A, B, and C by 10 points.

  FIG. 24 shows a processing procedure for temporarily changing the expected value of the Kankei data by matching including the image and the related data in the form of a flowchart.

  First, the similarity to the reference image is calculated for all images in the same image group, and it is determined whether the same relational data referring to the reference image is used in the image group. (Step S51).

  Then, images having similarities that are equal to or higher than a threshold value are selected from images generated based on the same relation data (step S52).

  An operation is added to the expected values of all the relational data possessed from the similar images thus selected (step S53).

(5) Media / Data Linkage Direction When a user designates a link direction for a reference image, an operation of an expected value may be added to all related data used in the same link direction.

  In the example shown in FIG. 25, an upward direction is designated as a connection direction with respect to the reference image. In this case, the relational data A, B,... Used for the upward connection in the same image group are extracted from the relational database 20, and a uniform point is added to the expected value for each relational data. The operation to do is added.

  The present invention has been described in detail above with reference to specific embodiments. However, it is obvious that those skilled in the art can make modifications and substitutions of the embodiment without departing from the gist of the present invention.

  In this specification, the idea / production support according to the present invention has been described by taking as an example the case of sequentially producing related image contents, but the paper of the present invention is not limited to this. For example, the present invention can be applied in the same manner to obtain the operational effects when producing content other than images, or when performing ideas and production work other than content production.

In short, the present invention has been disclosed in the form of exemplification, and the description of the present specification should not be interpreted in a limited manner. In order to determine the gist of the present invention, the claims section described at the beginning should be considered.

FIG. 1 is a diagram schematically showing the configuration of an information processing apparatus that realizes the idea and production according to the present invention. FIG. 2 is a diagram showing the connection direction of media data determined by the notation shape of the media data. FIG. 3 is a diagram schematically illustrating a functional configuration of the idea / production support system 10. FIG. 4 is a diagram schematically showing the data structure in the relational database 20. FIG. 5 is a diagram showing a data structure for managing each image (media data) in the media database 21. FIG. 6 is a flowchart showing a processing procedure at the time of image creation. FIG. 7 is a flowchart showing a processing procedure of image editing. FIG. 8 is a flowchart showing a processing procedure for registering a newly defined relationship in the relational database 20 during image editing. FIG. 9 is a diagram for explaining a processing procedure for scanning a relationship between connected images and specifying appropriate relationship data by matching. FIG. 10 is a diagram for explaining a processing procedure for scanning a relationship between images to be connected and specifying appropriate relationship data by matching. FIG. 11 is a diagram illustrating an example in which a connection image is generated by applying relational data to an original image. FIG. 12 is a diagram illustrating an example in which a connection image is generated by applying relational data to an original image. FIG. 13 is a diagram illustrating an example in which a connection image is generated by applying relational data to an original image. FIG. 14 is a diagram illustrating an example in which a connection image is generated by applying relation data to an original image. FIG. 15 is a diagram illustrating an example in which a connection image is generated by applying relation data to an original image. FIG. 16 is a diagram showing an example in which a connection image is generated by applying relational data to an original image. FIG. 17 is a diagram for explaining processing for temporarily changing the expected value of the relational data by image matching. FIG. 18 is a diagram for explaining processing for temporarily changing the expected value of the relational data by image matching. FIG. 19 is a flowchart showing a processing procedure for temporarily changing the expected value of the relational data by image matching. FIG. 20 is a diagram for explaining a process of temporarily changing the expected value of the relational data by matching the relational database used. FIG. 21 is a diagram for explaining processing for temporarily changing the expected value of the relational data by matching the relational database used. FIG. 22 is a flowchart showing a processing procedure for temporarily changing the expected value of the relational data by matching the used relational database. FIG. 23 is a diagram for explaining a process of performing an expected value operation by matching including an image and related data in the same image group. FIG. 24 is a flowchart showing a processing procedure for performing an operation of an expected value by matching including an image and related data in the same image group. FIG. 25 is a diagram for explaining a process for performing an operation of an expected value according to the connection direction of media data.

Explanation of symbols

DESCRIPTION OF SYMBOLS 10 ... Idea and production support system 11 ... Connection direction input part 12 ... Recommended relation selection part 13 ... Recommended relation display part 14 ... Usage relation selection part 15 ... Image processing part 16 ... Image display part 17 ... Image edit part 18 ... Action preservation | save Unit 19: Relational data registration unit 20 ... Relational database 21 ... Media database 100 ... Information processing apparatus 101 ... CPU,
102: Main memory, 103: ROM
104 ... Display controller 105 ... Input device interface 106 ... Network interface 107 ... External device interface 108 ... Bus 111 ... Display 112 ... Keyboard, 113 ... Mouse 114 ... Hard disk device 115 ... Media drive

Claims (25)

An information processing system that supports the idea or production of content that connects multiple media data,
A relational database storing relational data describing the relation between the original media data and the media data linked to the original media data;
For each media data, a media database that stores the media data that links the media data together with data related to the media data that is linked to the media data;
A connection direction input means for a user to input a direction for connecting new media data to original media data;
In accordance with the direction input by the connection direction input means, candidate relational data relating the original media data and new media data are extracted from the relational database and presented as recommended relational data. Recommended relationship selection means,
Media data processing means for generating new media data using the user-selected one of the presented relational data;
Means for concatenating new media data in the input direction of the original media data and storing it in a media database;
An information processing system comprising: Treat images as media data,
The relational data includes an image processing algorithm applied to the original image to generate a new image to be connected.
The information processing system according to claim 1. The relational database manages expected values using each relational data,
The recommended relationship selection means selects relationship data to be recommended based on an expected value.
The information processing system according to claim 1. A media editing means for further editing the new media data generated from the original media data using the relationship data;
The information processing system according to claim 1. Action storage means for storing an action added to the media data by the media editing means;
The information processing system according to claim 4. A relation data registration means for registering the action stored in the action storage means as new relation data in the relation database;
The information processing system according to claim 5. The relation data registration means defines the relation data defined only by the action added to the media data, or the relation data used for the original media data and the action added to the newly generated media data. Register the relationship data to be stored in the relationship database;
The information processing system according to claim 6. The relational database changes its expected value according to the number of times the relational data is selected.
The information processing system according to claim 3. The relational database stores similar media data similar to the reference media data among the past media data generated in the past in the process of concatenating new media data from the reference media data currently focused on. Search and change the expected value of the relational data used when concatenating new media data to the similar media data;
The information processing system according to claim 3. The relationship database is the same relationship as the relationship data used when linking the reference media data to the original media data in the process of linking new media data from the reference media data that is currently focused on. Search past media data generated using the data, and change the expected value of the related data used when connecting the new media data to the past media data.
The information processing system according to claim 3. The relational database stores similar media data similar to the reference media data among the past media data generated in the past in the process of concatenating new media data from the reference media data currently focused on. Similar media generated using the same relationship data by searching and determining whether the same relationship data as the relationship data used when linking the reference media data to the original media data has been used in the past -Change the expected value of the relational data used when linking new media data to media data whose similarity is equal to or greater than a predetermined value.
The information processing system according to claim 3. The relational database connects the media data in the same connection direction as the connection direction input to the reference media data in the process of connecting new media data from the reference media data currently focused on. In order to change the expected value of the relationship data used in the past,
The information processing system according to claim 3. An information processing method that supports the idea or production of content that connects multiple media data,
A relational data management step for managing relational data describing the relation between the original media data and the media data linked thereto;
A media management step for storing each media data together with the media data concatenating the media data and the relationship data with the media data linked to the media data;
A connection direction input step in which a user inputs a direction in which new media data is connected to original media data;
A recommended relationship selection step of searching for candidate relationship data relating the original media data and the new media data in accordance with the direction input in the connection direction input step, and presenting it as relationship data to be recommended ,
A media data processing step for generating new media data using a user-selected one of the presented relational data;
Concatenating new media data in the input direction of the original media data;
An information processing method comprising: Treat images as media data,
The relational data includes an image processing algorithm applied to the original image to generate a new image to be connected.
The information processing method according to claim 13. The relational database manages expected values using each relational data,
In the recommended relationship selection step, relationship data to be recommended is selected based on an expected value.
The information processing method according to claim 13. A media editing step of further editing the new media data generated from the original media data using the relationship data;
The information processing method according to claim 13. An action storing means step for storing an action added to the media data in the media editing step;
The information processing method according to claim 16. A relationship data registration step of registering the action stored in the action storage step in the relationship database as new relationship data;
The information processing method according to claim 17. In the relation data registration step, the relation data defined only by the action added to the media data, or the relation data used for the original media data and the action added to the newly generated media data are defined together. Register the relationship data to be stored in the relationship database;
The information processing method according to claim 18. In the relational data management step, the expected value is changed according to the number of times the relational data is selected.
The information processing method according to claim 15. In the related data management step, in the process of concatenating new media data from the reference media data currently focused on, similar media similar to the reference media data among the past media data generated in the past Search for data and change the expected value of the relational data used when concatenating new media data to the similar media data.
The information processing method according to claim 15. In the relational data management step, in the process of concatenating new media data from the reference media data currently focused on, the relational data used when linking the reference media data to the original media data and Search past media data generated using the same relationship data, and change the expected value of the relationship data used when connecting the new media data to the past media data.
The information processing method according to claim 15. In the related data management step, in the process of concatenating new media data from the reference media data currently focused on, similar media similar to the reference media data among the past media data generated in the past Generated using the same relational data, searching for data and determining if the same relational data used in the past was used to link the reference media data to the original media data Change the expected value of the relational data used when linking new media data to media data that has a similarity greater than or equal to a predetermined value among similar media data.
The information processing method according to claim 15. In the relational data management step, in the process of connecting new media data from the reference media data currently focused on, the media data is transferred in the same connection direction as the connection direction input for the reference media data. Changing the expected value of the relationship data used in the past to concatenate,
The information processing method according to claim 15. A computer program written in a computer-readable format so as to execute on a computer system a process for supporting the idea or production of content that connects a plurality of media data,
A relational data management step for managing relational data describing the relation between the original media data and the media data linked thereto;
A media management step for storing each media data together with the media data concatenating the media data and the relationship data with the media data linked to the media data;
A connection direction input step in which a user inputs a direction in which new media data is connected to original media data;
A recommended relationship selection step of searching for candidate relationship data relating the original media data and the new media data in accordance with the direction input in the connection direction input step, and presenting it as relationship data to be recommended ,
A media data processing step for generating new media data using a user-selected one of the presented relational data;
A media editing step that further edits the new media data generated from the original media data using the relationship data;
An action storage means step for storing an action added to the media data in the media editing step;
A relation data registration step of registering the action stored in the action storage step in the relation database as new relation data;
A computer program comprising:

Images