JP7189779B2 - Decision device, decision method, decision program - Google Patents

Description

The present invention relates to a determination device, determination method, and determination program.

Conventionally, techniques for displaying advertising content related to video content have been provided.

JP 2010-526494 A

However, with the conventional technology described above, it is not always possible to determine an appropriate scene in which content to be superimposed on a moving image is displayed. For example, with the above-described conventional technology, the creative simply appears overlaid on the video content, and it is not always possible to determine an appropriate scene in which the content superimposed on the moving image is displayed.

The present application has been made in view of the above, and an object thereof is to provide a determination device, a determination method, and a determination program capable of determining an appropriate scene in which content to be superimposed on a moving image is displayed.

A determination device according to the present application includes an analysis unit that analyzes each scene that constitutes information about a moving image, and a determination that determines a scene in which content to be superimposed on the moving image is displayed based on the analysis result analyzed by the analysis unit. and a part.

According to one aspect of the embodiment, it is possible to determine an appropriate scene in which content superimposed on a moving image is displayed.

FIG. 1 is a diagram illustrating an example of determination processing executed by a determination device according to an embodiment. FIG. 2 is a diagram illustrating a configuration example of a determination device according to the embodiment; 3 is a diagram illustrating an example of a moving image information storage unit according to the embodiment; FIG. 4 is a diagram illustrating an example of a condition information storage unit according to the embodiment; FIG. FIG. 5 is a flowchart showing an example of the flow of determination processing executed by the determination device according to the embodiment. FIG. 6 is a diagram illustrating an example of content distributed by a determining device according to a modification; FIG. 7 is a diagram illustrating an example of content distributed by a determining device according to a modification; FIG. 8 is a hardware configuration diagram showing an example of a computer that implements the functions of the determination device.

Embodiments (hereinafter referred to as "embodiments") for implementing the determination device, determination method, and determination program according to the present application will be described in detail below with reference to the drawings. Note that the determination device, determination method, and determination program according to the present application are not limited to this embodiment. Further, each embodiment can be appropriately combined within a range that does not contradict the processing contents. Also, in each of the following embodiments, the same parts are denoted by the same reference numerals, and overlapping descriptions are omitted.

[1. Example of provision processing indicated by decision device]
An example of provision processing executed by the determination device according to the embodiment will be described with reference to FIG. FIG. 1 is a diagram illustrating an example of determination processing executed by a determination device according to an embodiment. Specifically, the determining device 100 determines the scene in which the content to be superimposed on the moving image is displayed based on the analysis results obtained by analyzing each scene that constitutes the information about the moving image. Note that an example in which advertising content is superimposed as content to be superimposed on a moving image will be described below. Also, a case in which one piece of advertising content is superimposed on a moving image will be described as an example.

As shown in FIG. 1 , the decision system 1 includes a terminal device 10 , an advertising device 20 and a decision device 100 . The terminal device 10, the advertising device 20, and the determination device 100 are communicably connected by wire or wirelessly via a predetermined communication network (not shown). Note that the decision system 1 shown in FIG. 1 may include a plurality of terminal devices 10, a plurality of advertising devices 20, and a plurality of decision devices 100. FIG.

The terminal device 10 according to the embodiment is a determination device used by a user who accesses content such as web pages displayed on a browser and content for applications. For example, the terminal device 10 is a desktop PC (Personal Computer), a notebook PC, a tablet terminal, a mobile phone, a PDA (Personal Digital Assistant), or the like. The example of FIG. 1 shows a case where the terminal device 10 is a smartphone used by a user. In addition, below, the terminal device 10 may be described as a user. That is, hereinafter, the user can also be read as the terminal device 10 .

The advertising device 20 according to the embodiment is a server device that receives a distribution request for advertising content from the terminal device 10 and performs distribution processing for distributing advertising content submitted by an advertiser to the terminal device 10 . In the following example, it is assumed that advertising content has been previously submitted to the advertising device 20 by the advertiser.

The determination device 100 according to the embodiment is realized by, for example, a server device. Specifically, the determining device 100 analyzes each scene that constitutes the information about the moving image. Then, the determining device 100 determines the scene in which the advertising content to be superimposed on the moving image is displayed based on the analysis result.

Also, the determining device 100 is a server or the like that distributes content to the terminal device 10 . For example, the decision device 100 can access news sites, auction sites, weather forecast sites, shopping sites, finance (stock prices) sites, route search sites, map providing sites, travel sites, restaurant introduction sites, web blogs, etc. on the terminal device 10. To deliver.

Here, the content delivered by the decision device 100 includes a content acquisition command. For example, in an HTML file or the like written in HTML (HyperText Markup Language) forming content, the URL (Uniform Resource Locator) of the advertising device 20 or the like is written as an advertisement content acquisition command. In this case, the terminal device 10 acquires the advertising content from the advertising device 20 by accessing the URL described in the HTML file or the like.

An example of determination processing by the determination device 100 will be described below along the flow with reference to FIG. 1 .

First, as shown in FIG. 1, the determination device 100 receives a content distribution request from a user (step S1). Subsequently, the determining device 100 analyzes each scene that constitutes the information about the moving image (step S2). Specifically, the determination device 100 analyzes the audio included in the information about the moving image for each scene by conventional techniques such as image analysis techniques and conventional techniques such as pattern matching and machine learning. Further, specifically, the determination device 100 analyzes the motion of the object included in the information about the moving image for each scene using conventional techniques such as image analysis techniques and conventional techniques such as pattern matching and machine learning.

For example, assume that the video is a person dancing in a room. In this case, the determination device 100 analyzes the volume of the audio or BGM (Background Music) included in the information about the moving image by conventional techniques such as image analysis techniques and conventional techniques such as pattern matching and machine learning. Then, the determining device 100 outputs the volume level of each scene as an analysis result.

Also, for example, it is assumed that the video is a video of a person dancing in a room. In this case, the determination device 100 analyzes the motion of the person included in the information about the moving image by conventional techniques such as image analysis techniques and conventional techniques such as pattern matching and machine learning. For example, when it is determined that the difference between the motion of the person displayed in the first scene and the motion of the person displayed in the second scene is large, the determining device 100 determines that the motion between the scenes is large. To analyze. Then, the determining device 100 outputs the magnitude of the action for each scene as an analysis result.

Also, for example, it is assumed that the video is a video of a person dancing in a room. In this case, the determination device 100 analyzes the user's comments on the moving image included in the information on the moving image by conventional techniques such as image analysis technology and conventional techniques such as pattern matching and machine learning. Then, the determining device 100 outputs the number of comments for each scene as an analysis result.

Then, the determining device 100 determines a scene for superimposing the advertisement content based on the analysis result (step S3). Specifically, the determining device 100 determines a scene SE1 including a predetermined area SP1 for superimposing the advertising content based on the analysis result.

For example, assume that the video is a person dancing in a room. In this case, the determining device 100 selects a scene with a low volume based on the analysis result indicating the level of volume for each scene. Then, the determining device 100 generates an area in which the advertisement content is superimposed on the predetermined area SP1 of the scene with low volume. Then, the determining device 100 determines this scene as the scene SE1 on which the advertising content is superimposed.

Also, for example, it is assumed that the video is a video of a person dancing in a room. In this case, the determining device 100 selects a scene with a small action based on the analysis result indicating the magnitude of the action for each scene. Then, the determining device 100 generates an area in which the advertisement content is superimposed on the predetermined area SP1 of the scene in which the action is small. Then, the determining device 100 determines this scene as the scene SE1 on which the advertising content is superimposed.

Also, for example, it is assumed that the video is a video of a person dancing in a room. In this case, the determining device 100 selects a scene with a small number of comments based on the analysis result indicating the number of comments for each scene. Then, the determining device 100 generates an area in which the advertising content is superimposed on the predetermined area SP1 of the scene in which the number of comments is small. Then, the determining device 100 determines this scene as the scene SE1 on which the advertising content is superimposed.

Subsequently, the determining device 100 distributes content including moving images (step S4). Specifically, the determining device 100 distributes content including advertising content to be superimposed on the scene. More specifically, the determining device 100 distributes content in which a moving image including a scene SE1 on which advertising content is superimposed is displayed. For example, suppose the advertising content is about rentals. In this case, the determining device 100 distributes content showing information on sales of furniture, which is content in which a moving image including a scene SE1 in which advertising content regarding rental is superimposed is displayed.

Then, the advertising device 20 distributes the advertising content when receiving the advertising content acquisition command from the terminal device 10 (step S5). For example, the advertising device 20 distributes the advertising content to the terminal device 10 according to the advertising content acquisition command included in the predetermined area SP1 included in the scene SE1 on which the advertising content is superimposed.

In this way, the determining device 100 according to the embodiment analyzes each scene that constitutes a moving image. Then, the determining device 100 determines the scene in which the content to be superimposed on the moving image is displayed based on the analysis result. As a result, the determination device 100 according to the embodiment can search for a scene suitable for the content by analyzing each scene that constitutes the moving image. can do.

This point will be explained. To explain using the example of FIG. 1, the determining device 100 analyzes the volume of audio or BGM included in the moving image. Then, the determining device 100 selects a scene with a low volume based on the analysis result indicating the level of volume for each scene. Then, the determining device 100 generates an area in which the advertising content is superimposed on a predetermined area of the scene with low volume. Then, the determining device 100 determines this scene as the scene on which the advertising content is superimposed. From this, the determining device 100 can determine a scene in which the user is likely to pay attention to the advertising content among the scenes of the moving image. As a result, the determining device 100 can determine an appropriate scene in which the content to be superimposed on the moving image is displayed, thereby enhancing the appealing effect of the content.

[2. Configuration of Decision Device]
Next, the configuration of the determination device 100 according to the embodiment will be described using FIG. FIG. 2 is a diagram showing a configuration example of the determination device 100 according to the embodiment. As shown in FIG. 2 , the determination device 100 has a communication section 110 , a storage section 120 and a control section 130 .

(Regarding communication unit 110)
The communication unit 110 is realized by, for example, a NIC (Network Interface Card) or the like. The communication unit 110 is connected to a network by wire or wirelessly, and transmits and receives information between the terminal device 10 and the advertising device 20 .

(Regarding storage unit 120)
The storage unit 120 is realized by, for example, a semiconductor memory device such as a RAM (Random Access Memory) or flash memory, or a storage device such as a hard disk or an optical disk. Storage unit 120 has moving image information storage unit 121 and condition information storage unit 122 .

(Regarding the moving image information storage unit 121)
The moving image information storage unit 121 according to the embodiment stores information related to moving images. Here, FIG. 3 shows an example of the moving image information storage unit 121 according to the embodiment. In the example shown in FIG. 3, the moving picture information storage unit 121 has items such as "moving picture ID" and "moving picture".

“Movie ID” is an identifier for identifying a movie. "Movie" is information about a movie. For example, in FIG. 3, "M1" identified by the movie ID has a movie "MO1". In the example shown in FIG. 3, moving images are represented by abstract codes such as "MO1", but the moving images may be information or the like indicating specific file formats of moving images.

(Regarding the condition information storage unit 122)
The condition information storage unit 122 according to the embodiment stores information related to conditions related to scenes of advertising content to be superimposed on moving images. Here, FIG. 4 shows an example of the condition information storage unit 122 according to the embodiment. In the example shown in FIG. 4, the condition information storage unit 122 has items such as "condition ID", "video ID", "timing", "location", "size", and "advertisement content".

"Condition ID" is an identifier that identifies a condition. “Movie ID” is an identifier for identifying a movie. “Timing” is information about the timing of superimposing the advertising content on the scene associated with the “condition ID” and the “video ID”. The “place” is information about the place in the scene where the advertising content is superimposed on the scene associated with the “condition ID” and the “video ID”. "Size" is information about the size of the advertisement content to be superimposed on the scene associated with the "condition ID" and the "video ID". "Advertisement content" is information about advertisement content to be superimposed on the scene.

For example, in FIG. 4, "CO1" identified by condition ID for "M1" identified by movie ID has timing "T3", location "LC1", and magnitude "SI1". Yes, and the advertising content is "AD1".

In the example shown in FIG. 4, the timing is represented by an abstract code such as "T3", but the timing may be information indicating a specific number. In addition, in the example shown in FIG. 4, the location is represented by an abstract code such as "LC3", but the location may be information indicating coordinates specified by a specific pixel number.

Also, in the example shown in FIG. 4, the size is represented by an abstract code such as "SI1", but the size may be information indicating a specific pixel size. Also, in the example shown in FIG. 4, the advertising content is represented by an abstract code such as "AD1", but the advertising content may be information or the like indicating a specific file format.

(Regarding the control unit 130)
The control unit 130 is a controller, and for example, various programs (an example of a determination program) stored in a storage device inside the determination device 100 are controlled by a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like. equivalent) is implemented by executing the RAM as a work area. Also, the control unit 130 is a controller, and is implemented by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

As shown in FIG. 2, the control unit 130 includes a reception unit 131, an analysis unit 132, a determination unit 133, and a distribution unit 134, and implements or executes information processing functions and actions described below. . Note that the internal configuration of the control unit 130 is not limited to the configuration shown in FIG. 2, and may be another configuration as long as it performs the information processing described later. Moreover, the connection relationship between the processing units of the control unit 130 is not limited to the connection relationship shown in FIG. 2, and may be another connection relationship.

(Regarding the reception unit 131)
The reception unit 131 receives a content distribution request from a user. Note that the receiving unit 131 may receive information about the user as well as receiving a content distribution request from the user. Here, the information about the user includes attribute information that is information about the user's attribute, user's location information, user's content viewing history, user's advertising content viewing history, information about user's interests, and the like.

(Regarding the analysis unit 132)
The analysis unit 132 analyzes each scene that constitutes the moving image. Specifically, the analysis unit 132 analyzes the volume, the motion of the object, and the number of comments corresponding to each scene. More specifically, the analysis unit 132 refers to the moving image information storage unit 121 and analyzes the audio included in the moving image using conventional techniques such as image analysis technology and conventional techniques such as pattern matching and machine learning. More specifically, the analysis unit 132 refers to the moving image information storage unit 121 and uses conventional techniques such as image analysis technology and conventional techniques such as pattern matching and machine learning to analyze the movement of objects included in the moving image. to parse More specifically, the analysis unit 132 refers to the moving image information storage unit 121 and applies conventional techniques such as image analysis technology and conventional techniques such as pattern matching and machine learning. Parse user comments for scenes.

For example, assume that the video is a person dancing in a room. In this case, the analysis unit 132 analyzes the volume of the audio or BGM included in the moving image by conventional techniques such as image analysis techniques and conventional techniques such as pattern matching and machine learning. Then, the analysis unit 132 outputs the volume level of each scene as an analysis result.

Also, for example, it is assumed that the video is a video of a person dancing in a room. In this case, the analysis unit 132 analyzes the motion of the person included in the moving image by conventional techniques such as image analysis technology, pattern matching, machine learning, and the like. For example, when the analysis unit 132 determines that the difference between the human motion displayed in the first scene and the human motion displayed in the second scene is large, the analysis unit 132 determines that the motion between scenes is large. To analyze. Then, the analysis unit 132 outputs the magnitude of the motion for each scene as an analysis result.

Also, for example, it is assumed that the video is a video of a person dancing in a room. In this case, the analysis unit 132 analyzes the user's comments on each scene included in the information about the moving image by conventional techniques such as image analysis technology and conventional techniques such as pattern matching and machine learning. Then, the analysis unit 132 outputs the number of comments for each scene as an analysis result.

Also, for example, it is assumed that the video is a video of a person dancing in a room. In this case, the analysis unit 132 detects the flatness, which is the degree of flatness in the moving image, by conventional techniques such as image analysis techniques and conventional techniques such as pattern matching and machine learning. Then, the analysis unit 132 outputs the flatness suitable for the area in which the advertising content is displayed for each scene as an analysis result.

(About decision unit 133)
The determination unit 133 determines a scene in which content to be superimposed on the moving image is displayed based on the analysis result analyzed by the analysis unit 132 . Specifically, the determining unit 133 determines a scene including a predetermined area for superimposing the advertising content based on the analysis result.

For example, in the example of FIG. 1, it is assumed that the video is a person dancing in a room. In this case, the determination unit 133 selects a scene with a low volume based on the analysis result indicating the level of volume for each scene. Then, the determining unit 133 generates an area in which the advertisement content is superimposed on the predetermined area SP1 of the low volume scene. Then, the determination unit 133 determines this scene as the scene SE1 on which the advertisement content is superimposed. The determination unit 133 then stores the result in the condition information storage unit 122 .

Also, in the example of FIG. 1, for example, it is assumed that the video is a person dancing in a room. In this case, the determining unit 133 selects a scene with a small motion based on the analysis result indicating the magnitude of the motion for each scene. Then, the determining unit 133 generates an area in which the advertising content is superimposed on the predetermined area SP1 of the scene in which the action is small. Then, the determination unit 133 determines this scene as the scene SE1 on which the advertisement content is superimposed. The determination unit 133 then stores the result in the condition information storage unit 122 .

Also, in the example of FIG. 1, for example, it is assumed that the video is a person dancing in a room. In this case, the determination unit 133 selects a scene with a small number of comments based on the analysis result indicating the number of comments for each scene. Then, the determination unit 133 generates an area in which the advertisement content is superimposed on the predetermined area SP1 of the scene with a small number of such comments. Then, the determination unit 133 determines this scene as the scene SE1 on which the advertisement content is superimposed. The determination unit 133 then stores the result in the condition information storage unit 122 .

(About distribution unit 134)
The distribution unit 134 distributes various contents. Specifically, the distribution unit 134 distributes content including advertising content to be superimposed on the scene determined by the determination unit 133 . More specifically, the distribution unit 134 distributes content in which a moving image including a scene based on the condition stored in the condition information storage unit 122 and including a scene in which the advertisement content is superimposed is displayed. Also, more specifically, the distribution unit 134 distributes content corresponding to the advertisement content superimposed on the moving image.

For example, suppose the advertising content is about rentals. In this case, the distribution unit 134 distributes content showing information about sales of furniture, which is content in which a moving image including a scene in which advertising content regarding rental is superimposed is displayed.

[3. Processing procedure]
Next, with reference to FIG. 5, a procedure of determination processing executed by the determination device 100 according to the embodiment will be described. FIG. 5 is a flowchart showing an example of the flow of determination processing executed by the determination device according to the embodiment.

As shown in FIG. 5, the reception unit 131 receives a content distribution request from a user (step S101). If the receiving unit 131 has not received a content distribution request from the user (step S101; No), the analyzing unit 132 waits until receiving a content distribution request from the user.

On the other hand, when the accepting unit 131 accepts a content distribution request from the user (step S101; Yes), the analyzing unit 132 analyzes each scene constituting the information about the moving image (step S102).

For example, assume that the video is a person dancing in a room. In this case, the analysis unit 132 analyzes the volume of the audio or BGM included in the information about the moving image by conventional techniques such as image analysis techniques and conventional techniques such as pattern matching and machine learning. Then, the analysis unit 132 outputs the volume level of each scene as an analysis result.

Also, for example, it is assumed that the video is a video of a person dancing in a room. In this case, the analysis unit 132 analyzes the motion of the person included in the information about the moving image by conventional techniques such as image analysis technology and conventional techniques such as pattern matching and machine learning. For example, when the analysis unit 132 determines that the difference between the human motion displayed in the first scene and the human motion displayed in the second scene is large, the analysis unit 132 determines that the motion between scenes is large. To analyze. Then, the analysis unit 132 outputs the magnitude of the motion for each scene as an analysis result.

Also, for example, it is assumed that the video is a video of a person dancing in a room. In this case, the analysis unit 132 analyzes the user's comments on each scene included in the information about the moving image by conventional techniques such as image analysis technology and conventional techniques such as pattern matching and machine learning. Then, the analysis unit 132 outputs the number of comments for each scene as an analysis result.

Then, the determination unit 133 determines a scene for superimposing the advertisement content based on the analysis result analyzed by the analysis unit 132 (step S103). For example, in the example of FIG. 1, it is assumed that the video is a person dancing in a room. In this case, the determination unit 133 selects a scene with a low volume based on the analysis result indicating the level of volume for each scene. Then, the determining unit 133 generates an area in which the advertisement content is superimposed on the predetermined area SP1 of the low volume scene. Then, the determination unit 133 determines this scene as the scene SE1 on which the advertisement content is superimposed.

Also, for example, in the example of FIG. 1, it is assumed that the video is a person dancing in a room. In this case, the determining unit 133 selects a scene with a small motion based on the analysis result indicating the magnitude of the motion for each scene. Then, the determining unit 133 generates an area in which the advertising content is superimposed on the predetermined area SP1 of the scene in which the action is small. Then, the determination unit 133 determines this scene as the scene SE1 on which the advertisement content is superimposed.

Also, for example, in the example of FIG. 1, it is assumed that the video is a person dancing in a room. In this case, the determination unit 133 selects a scene with a small number of comments based on the analysis result indicating the number of comments for each scene. Then, the determination unit 133 generates an area in which the advertisement content is superimposed on the predetermined area SP1 of the scene with a small number of such comments. Then, the determination unit 133 determines this scene as the scene SE1 on which the advertisement content is superimposed.

Then, the distribution unit 134 distributes the content in which the moving image including the scene determined by the determination unit 133 is displayed (step S104). For example, suppose the advertising content is about rentals. In this case, the distribution unit 134 distributes content showing information about sales of furniture, which is content in which a moving image including a scene in which advertising content regarding rental is superimposed is displayed.

[4. Modification]
The determination device 100 described above may be implemented in various different forms other than the above embodiment. Therefore, other embodiments of the determination device 100 will be described below.

[4-1. Aspect of Advertisement Content]
In the above embodiment, an example was given in which the determining device 100 executes the distribution process of distributing content including a video in which advertising content is superimposed on the predetermined area SP1. There may be. For example, the determining device 100 may distribute content including a video on which advertisement content is superimposed in the form of a banner or the like.

Further, for example, as shown in FIG. 6, the advertisement content AD1 displayed around the moving image MO1 and different from the advertising content superimposed on the moving image MO1 is distributed. good too.

Further, for example, as shown in FIG. 7, the advertisement content AD2 displayed around the moving image MO2 of the moving image MO1 and the advertising content AD3 superimposed on the moving image MO2 are connected to each other to display the advertisement content. good too.

[4-2. Multiple Ad Content]
In the above embodiment, an example was given in which the determining device 100 executes the distribution process of distributing content including a video on which one piece of advertising content is superimposed, but a plurality of pieces of advertising content may be displayed. For example, the determining device 100 may distribute content including a moving image in which multiple pieces of advertising content are superimposed on one scene. Further, for example, the determining device 100 may distribute content including a moving image in which one or more pieces of advertising content are superimposed on a plurality of scenes.

[4-3. Decision processing (1) specific shape]
In the above-described embodiment, an example of the determination process in which the determination unit 133 of the determination device 100 determines the scene including the predetermined area SP1 as the scene SE1 on which the advertising content is superimposed based on the analysis result has been described. is not limited to Specifically, the determination unit 133 may determine a scene including a specific shape as the predetermined area based on the analysis result analyzed by the analysis unit 132 . For example, suppose a video is about renting. In this case, the determination unit 133 may determine a scene for superimposing advertising content regarding the sale of a sofa-shaped sofa on the moving image.

Accordingly, the determination unit 133 of the determination device 100 according to the embodiment can determine an appropriate scene in which the advertising content to be superimposed on the moving image is displayed, thereby enhancing the advertising effect of the advertising content.

[4-4. Decision processing (2) specific mark]
In the above-described embodiment, an example of the determination process in which the determination unit 133 of the determination device 100 determines the scene including the predetermined area SP1 as the scene SE1 on which the advertising content is superimposed based on the analysis result has been described. is not limited to Specifically, the determination unit 133 may determine a scene including a specific mark as the predetermined area based on the analysis result analyzed by the analysis unit 132 . Note that the specific mark referred to here includes, for example, product tags and the like.

For example, assume that the video is about clothes. In this case, the determination unit 133 may determine a scene in which a product tag indicating the identification information of the clothes linked to the clothes displayed in the moving image is superimposed. At this time, the determining unit 133 can browse the advertising content of the clothes by the user clicking the product tag.

Accordingly, the determination unit 133 of the determination device 100 according to the embodiment can determine an appropriate scene in which the advertising content to be superimposed on the moving image is displayed, thereby enhancing the advertising effect of the advertising content.

[4-5. Decision processing (3) information specified by the content provider]
In the above-described embodiment, an example of the determination process in which the determination unit 133 of the determination device 100 determines the scene including the predetermined area SP1 as the scene SE1 on which the advertising content is superimposed based on the analysis result has been described. is not limited to Specifically, the determination unit 133 may determine the scene based on information specified by the advertiser. The information designated by the advertiser here includes conditions for superimposing the advertising content, scenes for superimposing the advertising content, and the like.

For example, the timing for superimposing the advertising content on the scene, the location in the scene for superimposing the advertising content on the scene, and the size of the advertising content to be superimposed on the scene are specified as the conditions for superimposing the advertising content by the advertiser. shall be In this case, the determination unit 133 generates a predetermined area SP1 on which the advertising content is superimposed based on such conditions. At this time, the determination unit 133 generates a predetermined area SP1 positioned away from the object. Then, the determination unit 133 determines a scene including the predetermined area SP1 as a scene on which the advertising content is superimposed.

For example, assume that an advertiser is in the business of furniture. Also assume that the video is about renting. In this case, the determining unit 133 may specify a scene in which the furniture is displayed by the advertiser, and determine this scene as the scene on which the advertisement content regarding the sales of the furniture is to be superimposed.

Accordingly, the determination unit 133 of the determination device 100 according to the embodiment can determine an appropriate scene in which the advertising content to be superimposed on the moving image is displayed, thereby enhancing the advertising effect of the advertising content.

[4-6. Decision processing (4) Auction]
In the above-described embodiment, an example of the determination process in which the determination unit 133 of the determination device 100 determines the scene including the predetermined area SP1 as the scene SE1 on which the advertising content is superimposed based on the analysis result has been described. is not limited to Specifically, the determination unit 133 may determine the scene in which the advertising content determined by the auction is displayed based on the analysis result analyzed by the analysis unit 132 . For example, suppose a video is about renting. Also, it is assumed that the advertising content related to the sale of the table is determined by the auction. In this case, the determining unit 133 may determine a scene to be superimposed with the advertising content related to the sale of the table determined by the auction, which is the advertising content displayed in the moving image.

Accordingly, the determination unit 133 of the determination device 100 according to the embodiment can determine an appropriate scene in which the advertising content to be superimposed on the moving image is displayed, thereby enhancing the advertising effect of the advertising content.

Note that the auction may be a real-time auction. For example, suppose a video is about renting. In this case, the determining unit 133 may determine a scene in which the advertising content displayed in the moving image, which sequentially changes in real time, is superimposed.

[4-7. Decision processing (5) Billing]
In the above-described embodiment, an example of the determination process in which the determination unit 133 of the determination device 100 determines the scene including the predetermined area SP1 as the scene SE1 on which the advertising content is superimposed based on the analysis result has been described. is not limited to Specifically, the determination unit 133 may determine the scene in which the advertising content determined according to the billing amount of the user is displayed based on the analysis result analyzed by the analysis unit 132 . For example, suppose a video is about renting. In addition, when the billing amount of the user is equal to or greater than a predetermined amount, it is assumed that the advertisement content regarding the sale of the table, which is the target product of the time bargain sale, can be viewed. In this case, the determination unit 133 may determine a scene to superimpose the advertisement content displayed on the moving image, which relates to the sale of the table, which is the target product of the time bargain sale, according to the billing amount of the user.

Accordingly, the determination unit 133 of the determination device 100 according to the embodiment can determine an appropriate scene in which the advertising content to be superimposed on the moving image is displayed, thereby enhancing the advertising effect of the advertising content.

[4-8. Decision processing (6) content according to user]
In the above-described embodiment, an example of the determination process in which the determination unit 133 of the determination device 100 determines the scene including the predetermined area SP1 as the scene SE1 on which the advertising content is superimposed based on the analysis result has been described. is not limited to Specifically, the determination unit 133 may determine the scene in which the advertising content determined according to the user is displayed in the moving image based on the analysis result analyzed by the analysis unit 132 .

For example, assume that the user is a male in his thirties. It is also assumed that the motion picture relates to scenery. In this case, the determination unit 133 may determine a scene for superimposing advertising content regarding automobile sales. Also, for example, assume that the video is about rental. In this case, the determination unit 133 may determine a scene for superimposing advertising content regarding nearby rental properties based on the user's location information. Also, for example, it is assumed that the user has viewed advertising content related to a hair restorer in the past. Also assume that the video is about selling shampoo. In this case, the determination unit 133 may determine a scene for superimposing the advertising content regarding the hair restorer based on the browsing history of the user.

Accordingly, the determination unit 133 of the determination device 100 according to the embodiment can determine an appropriate scene in which the advertising content to be superimposed on the moving image is displayed according to the user. can.

[4-9. Decision processing (7) content according to the scene]
In the above-described embodiment, an example of the determination process in which the determination unit 133 of the determination device 100 determines the scene including the predetermined area SP1 as the scene SE1 on which the advertising content is superimposed based on the analysis result has been described. is not limited to Specifically, the determination unit 133 may determine the scene in which the advertising content is displayed, which is determined according to the scene included in the moving image, based on the analysis result analyzed by the analysis unit 132 . For example, suppose a video is about renting. In this case, the determination unit 133 may determine a scene for superimposing advertising content regarding furniture sales.

Accordingly, the determination unit 133 of the determination device 100 according to the embodiment can determine an appropriate scene in which the advertising content to be superimposed on the moving image is displayed, thereby enhancing the advertising effect of the advertising content.

[4-10. Decision processing (8) content selected by user]
In the above-described embodiment, an example of the determination process in which the determination unit 133 of the determination device 100 determines the scene including the predetermined area SP1 as the scene SE1 on which the advertising content is superimposed based on the analysis result has been described. is not limited to Specifically, the determination unit 133 may determine a scene in which the advertisement content selected by the user is displayed based on the analysis result analyzed by the analysis unit 132 . For example, suppose a video is about renting. In this case, the determining unit 133 may determine a scene to be superimposed with the advertising content selected by the user and relating to the sale of furniture. Note that the user may decide the size of the advertisement content, the place where it is displayed in the scene, and the like.

Accordingly, the determination unit 133 of the determination device 100 according to the embodiment can determine an appropriate scene in which the advertising content to be superimposed on the moving image is displayed, thereby enhancing the advertising effect of the advertising content.

[4-11. Decision processing (9) Determine scene according to video content]
In the above embodiment, the determination unit 133 of the determination device 100 determines the scene including the predetermined area SP1 as the scene SE1 on which the advertisement content is superimposed, based on the volume of the moving image, the movement of the object, and the analysis result of the external information. Although an example of the processing has been described, the processing is not limited to the determination processing described above. Specifically, the determining unit 133 determines a scene corresponding to the content of the moving image based on the analysis result obtained by analyzing the content of each scene by the analyzing unit 132 . More specifically, the determination device 100 determines a scene according to the degree of gaze of the user. For example, assume that the user is a male in his thirties. It is also assumed that the user has an interest in automobiles. In addition, it is assumed that the moving image includes a scene in which an automobile runs. It is also assumed that the advertising content is advertising content related to automobiles. In this case, the determination unit 133 may determine the scene in which the advertising content related to the automobile is superimposed on the scene in which the automobile that the user is presumed to be watching is running.

In the above modified example, an example is given in which the scene in which the vehicle that the user is watching is estimated from the information about the user's interest is running is determined as the scene in which the advertising content related to the vehicle is superimposed. The scene may be determined according to the degree of gaze of the user based on the analysis results of the volume, the motion of the object, and the number of comments.

For example, assume that the moving image includes a scene in which an automobile runs. It is also assumed that the advertising content is advertising content related to automobiles. In this case, the analysis unit 132 analyzes the volume of the engine sound of the automobile by conventional techniques such as image analysis techniques and conventional techniques such as pattern matching and machine learning. Then, the analysis unit 132 outputs the volume level of each scene as an analysis result. Then, the determining unit 133 selects a scene with a high volume based on the analysis result indicating the level of volume for each scene. Then, the determining unit 133 may determine such a scene with a high volume as the scene on which the advertising content is superimposed.

For example, assume that the moving image includes a scene in which an automobile runs. It is also assumed that the advertising content is advertising content related to automobiles. In this case, the analysis unit 132 analyzes the motion of the automobile by conventional techniques such as image analysis techniques and conventional techniques such as pattern matching and machine learning. For example, when it is determined that the difference between the motion of the car displayed in the first scene and the motion of the car displayed in the second scene is large, the analysis unit 132 determines that the motion between the scenes is large. To analyze. Then, the analysis unit 132 outputs the magnitude of the motion for each scene as an analysis result. Then, the determination unit 133 selects a scene in which the car moves significantly based on the analysis result indicating the magnitude of the motion for each scene. Then, the determination unit 133 may determine a scene in which such an action is large as a scene on which the advertising content is superimposed.

For example, assume that the moving image includes a scene in which an automobile runs. It is also assumed that the advertising content is advertising content related to automobiles. In this case, the analysis unit 132 analyzes the user's comment on the moving image included in the information on the moving image by conventional techniques such as image analysis technology and conventional techniques such as pattern matching and machine learning. Then, the analysis unit 132 outputs the number of comments for each scene as an analysis result. Then, the determining unit 133 selects a scene with a large number of comments based on the analysis result indicating the number of comments for each scene. Then, the determination unit 133 determines a scene with a large number of such comments as a scene on which advertising content is superimposed.

Accordingly, the determination unit 133 of the determination device 100 according to the embodiment can determine an appropriate scene in which the advertising content to be superimposed on the moving image is displayed, thereby enhancing the advertising effect of the advertising content.

[4-12. Decision processing (10) Determine scene based on past broadcast]
In the above-described embodiment, an example of the determination process in which the determination unit 133 of the determination device 100 determines the scene including the predetermined area SP1 as the scene SE1 on which the advertising content is superimposed based on the analysis result has been described. is not limited to Specifically, the analysis unit 132 analyzes the characteristics of the scene in which the advertising content is superimposed, which is the information about the video that was broadcast in the past and includes the advertising content. A scene is determined based on the scene characteristics analyzed by 132 . The information about moving pictures broadcasted in the past is, for example, information about moving pictures broadcasted by terrestrial broadcasting, satellite broadcasting, or the Internet.

More specifically, the analysis unit 132 analyzes the characteristics of the scene in which the advertising content of the video that was broadcast in the past and contains the advertising content is superimposed. For example, the analysis unit 132 determines that the scene on which the advertisement content is superimposed has features such as being zoomed out, objects being displayed small, objects moving little, human voices being absent, and only background music being played. , and points where the background image occupies most of the scene. Then, the determination unit 133 may determine a scene corresponding to the characteristics of the scene analyzed by the analysis unit 132 as the scene on which the advertisement content is superimposed.

For example, it is assumed that a moving image broadcasted in the past is a terrestrial broadcast. Moreover, it is assumed that the advertising content included in the terrestrial broadcasting is displayed as a telop. It is also assumed that the terrestrial broadcasting includes many zoomed-out scenes. In this case, the analysis unit 132 extracts a feature of scenes in which advertising content of moving images broadcasted by terrestrial broadcasting is displayed as telops, that there are many zoomed-out scenes. Then, the determination unit 133 may determine the zoomed-out scene as the scene on which the advertisement content is superimposed, based on the analysis result analyzed by the analysis unit 132 . Note that the analysis unit 132 may analyze the feature of the location of the telop of the video broadcasted by terrestrial broadcasting. For example, the analysis unit 132 extracts a point that does not overlap with other objects or the like as a feature of the location of the telop. Then, the determination unit 133 may determine a location where the advertisement content is superimposed, based on the analysis result obtained by the analysis unit 132, where the advertisement content is not overlapped with other objects or the like.

Accordingly, the determination unit 133 of the determination device 100 according to the embodiment can determine an appropriate scene in which the advertising content to be superimposed on the moving image is displayed, thereby enhancing the advertising effect of the advertising content.

[4-13. content〕
In the above embodiment, an example was given in which the determining device 100 executes the distribution process of distributing content including a video in which advertising content is superimposed on the predetermined area SP1. It does not have to be content for advertising purposes. For example, the information superimposed on the moving image may be content related to weather forecasts, content related to news, or the like. Also, for example, the information superimposed on the video may be subtitles. The subtitles referred to here are, for example, content related to supplementary description of the content of the moving image, content in which the audio of the moving image is written in characters, content related to translation of the audio of the moving image, and the like.

[5. Hardware configuration]
Also, the terminal device 10, the advertising device 20, and the determining device 100 according to the above-described embodiments are implemented by a computer 1000 configured as shown in FIG. 8, for example. The determination device 100 will be described below as an example. FIG. 8 is a hardware configuration diagram showing an example of a computer 1000 that implements the functions of the determination device 100. As shown in FIG. The computer 1000 includes a CPU 1100, a RAM 1200, a ROM (Read Only Memory) 1300, a HDD (Hard Disk Drive) 1400, a communication interface (I/F) 1500, an input/output interface (I/F) 1600, and a media interface (I/F). ) 1700.

The CPU 1100 operates based on programs stored in the ROM 1300 or HDD 1400 and controls each section. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 is started up, a program depending on the hardware of the computer 1000, and the like.

The HDD 1400 stores programs executed by the CPU 1100, data used by the programs, and the like. Communication interface 1500 receives data from other devices via network N, sends the data to CPU 1100, and transmits data generated by CPU 1100 via network N to other devices.

The CPU 1100 controls output devices such as displays and printers, and input devices such as keyboards and mice, through an input/output interface 1600 . CPU 1100 acquires data from an input device via input/output interface 1600 . Also, CPU 1100 outputs the generated data to an output device via input/output interface 1600 .

Media interface 1700 reads programs or data stored in recording medium 1800 and provides them to CPU 1100 via RAM 1200 . CPU 1100 loads such a program from recording medium 1800 onto RAM 1200 via media interface 1700, and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or a PD (Phase change rewritable disc), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory. etc.

For example, when the computer 1000 functions as the determination device 100 according to the embodiment, the CPU 1100 of the computer 1000 implements the functions of the control unit 130 by executing programs loaded on the RAM 1200 . In addition, data in storage unit 120 is stored in HDD 1400 . The CPU 1100 of the computer 1000 reads these programs from the recording medium 1800 and executes them, but as another example, these programs may be acquired via the network N from another device.

[6. others〕
Further, among the processes described in the above embodiments and modifications, all or part of the processes described as being performed automatically can be performed manually, or described as being performed manually. All or part of the processing can also be performed automatically by known methods. In addition, information including processing procedures, specific names, various data and parameters shown in the above documents and drawings can be arbitrarily changed unless otherwise specified. For example, the various information shown in each drawing is not limited to the illustrated information.

Also, each component of each device illustrated is functionally conceptual, and does not necessarily need to be physically configured as illustrated. In other words, the specific form of distribution and integration of each device is not limited to the one shown in the figure, and all or part of them can be functionally or physically distributed and integrated in arbitrary units according to various loads and usage conditions. Can be integrated and configured.

Also, the above-described embodiments and modifications can be appropriately combined within a range that does not contradict the processing content.

Also, the above-mentioned "section, module, unit" can be read as "means" or "circuit". For example, the determination unit can be read as determination means or a determination circuit.

[7. effect〕
As described above, the determination device 100 according to the embodiment has the analysis section 132 and the determination section 133 . The analysis unit 132 analyzes each scene that constitutes information about a moving image. The determination unit 133 determines a scene in which content to be superimposed on the moving image is displayed based on the analysis result analyzed by the analysis unit 132 .

As a result, the determination device 100 according to the embodiment can search for a scene suitable for the content by analyzing each scene that constitutes the moving image. can do.

In addition, in the determination device 100 according to the embodiment, the analysis unit 132 analyzes the volume corresponding to each scene, the motion of the object, and the number of comments, and the determination unit 133 performs the analysis analyzed by the analysis unit 132. Based on the result, determine the scene containing the predetermined area for the content to be superimposed.

As a result, the determination device 100 according to the embodiment can search for a scene suitable for the content by analyzing each scene that constitutes the moving image. can do.

Also, in the determination device 100 according to the embodiment, the determination unit 133 determines a scene including a specific shape as the predetermined area based on the analysis result analyzed by the analysis unit 132 .

As a result, the determination device 100 according to the embodiment can search for a scene suitable for the content by analyzing each scene that constitutes the moving image. can do.

Also, in the determination device 100 according to the embodiment, the determination unit 133 determines a scene including a specific mark as the predetermined area based on the analysis result of the analysis unit 132 .

As a result, the determination device 100 according to the embodiment can search for a scene suitable for the content by analyzing each scene that constitutes the moving image. can do.

In addition, in the determination device 100 according to the embodiment, the analysis unit 132 analyzes the content of each scene, and the determination unit 133 determines the scene based on the analysis result analyzed by the analysis unit 132 .

As a result, the determination device 100 according to the embodiment can search for a scene suitable for the content by analyzing each scene that constitutes the moving image. can do.

In addition, in the determination device 100 according to the embodiment, the analysis unit 132 calculates the user's gaze level estimated from the sound volume corresponding to each scene, the motion of the object, the number of comments, and the information regarding the user's interests. The analysis determination unit 133 determines a scene based on the analysis result analyzed by the analysis unit 132 .

As a result, the determination device 100 according to the embodiment can search for a scene suitable for the content by analyzing each scene that constitutes the moving image. can do.

In addition, in the determination device 100 according to the embodiment, the determination unit 133 determines the scene in which the content determined by the auction is displayed based on the analysis result analyzed by the analysis unit 132 .

As a result, the determination device 100 according to the embodiment can search for a scene suitable for the content by analyzing each scene that constitutes the moving image. can do.

Also, in the determination device 100 according to the embodiment, the determination unit 133 determines the scene in which the content determined according to the user's billing amount is displayed based on the analysis result analyzed by the analysis unit 132 .

As a result, the determination device 100 according to the embodiment can search for a scene suitable for the content by analyzing each scene that constitutes the moving image. can do.

Also, in the determination device 100 according to the embodiment, the determination unit 133 determines the scene based on information specified by the content provider.

As a result, the determination device 100 according to the embodiment can search for a scene suitable for the content by analyzing each scene that constitutes the moving image. can do.

Also, in the determination device 100 according to the embodiment, the determination unit 133 determines a scene in which content determined according to the user is displayed based on the analysis result analyzed by the analysis unit 132 .

As a result, the determination device 100 according to the embodiment can search for a scene suitable for the content by analyzing each scene that constitutes the moving image. can do.

Also, in the determination device 100 according to the embodiment, the determination unit 133 determines a scene in which content determined according to the scene included in the moving image is displayed based on the analysis result analyzed by the analysis unit 132 .

As a result, the determination device 100 according to the embodiment can search for a scene suitable for the content by analyzing each scene that constitutes the moving image. can do.

Also, in the determination device 100 according to the embodiment, the determination unit 133 determines the scene in which the content selected by the user is displayed based on the analysis result analyzed by the analysis unit 132 .

As a result, the determination device 100 according to the embodiment can search for a scene suitable for the content by analyzing each scene that constitutes the moving image. can do.

Further, in the determination device 100 according to the embodiment, the analysis unit 132 analyzes the characteristics of the scene in which the content of the information related to the moving image including the content, which is the information related to the moving image broadcast in the past, is superimposed, and the determining unit 133 determines the scene based on the scene features analyzed by the analysis unit 132 .

As a result, the determination unit 133 of the determination device 100 according to the embodiment can determine an appropriate scene in which the content to be superimposed on the moving image is displayed, thereby enhancing the appealing effect of the content.

The determining device 100 according to the embodiment further includes a distribution unit that distributes content including content to be superimposed on the scene determined by the determination unit 133 .

As a result, the determining device 100 according to the embodiment can determine an appropriate scene in which the content to be superimposed on the moving image is displayed, thereby enhancing the appealing effect of the content.

In addition, in the determination device 100 according to the embodiment, the distribution unit 134 distributes content that is displayed around the moving image and that includes other content that is different from the content.

As a result, the determining device 100 according to the embodiment can distribute the content superimposed on the moving image in various modes, thereby enhancing the appealing effect of the content.

In addition, in the determination device 100 according to the embodiment, the distribution unit 134 distributes content including content in which the content displayed around the moving image and the content are connected.

As a result, the determining device 100 according to the embodiment can distribute the content to be superimposed on the moving image in various modes, thereby enhancing the appealing effect of the content.

As described above, some of the embodiments of the present application have been described in detail based on the drawings. It is possible to carry out the invention in other forms with modifications.

1 determination system 10 terminal device 20 advertising device 100 determination device 110 communication unit 120 storage unit 121 moving image information storage unit 122 condition information storage unit 130 control unit 131 reception unit 132 analysis unit 133 determination unit 134 distribution unit

Claims (17)

an analysis unit that analyzes each scene that constitutes information about a video;
a determination unit that determines a scene in which content to be superimposed on the moving image is displayed based on the analysis result analyzed by the analysis unit;
with
The decision unit
A product tag indicating identification information of a product linked to the product displayed in the moving image based on the analysis result analyzed by the analysis unit, wherein when the product tag is clicked by a user, the product is identified. Determining the scene for superimposing the product tag for displaying the content ;
A decision device characterized by: The analysis unit is
Analyzing the sound volume, the movement of the object, and the number of comments corresponding to each scene;
The decision device according to claim 1 , characterized in that: The decision unit
Determining the scene on which a specific shape is superimposed based on the analysis result analyzed by the analysis unit;
3. The decision device according to claim 2 , characterized in that: The analysis unit is
analyzing the content of each scene;
The decision unit
determining the scene based on the analysis result analyzed by the analysis unit;
The decision device according to claim 1, characterized in that: The analysis unit is
Analyzing the degree of attention of the user estimated from the sound volume corresponding to each scene, the movement of the object, the number of comments, and information on the user's interest,
The decision unit
determining the scene based on the analysis result analyzed by the analysis unit;
5. The decision device according to claim 4 , characterized in that: The decision unit
Determining a scene in which the content determined by the auction is displayed based on the analysis result analyzed by the analysis unit;
The decision device according to any one of claims 1 to 5 , characterized in that: The decision unit
Determining a scene in which the content determined according to the user's billing amount is displayed based on the analysis result analyzed by the analysis unit;
The decision device according to any one of claims 1 to 6 , characterized in that: The decision unit
determining the scene based on information specified by a content provider;
The decision device according to any one of claims 1 to 7 , characterized in that: The decision unit
Determining a scene in which content determined according to the user is displayed based on the analysis result analyzed by the analysis unit;
The decision device according to any one of claims 1 to 8 , characterized in that: The decision unit
Determining a scene in which content determined according to the scene included in the moving image is displayed based on the analysis result analyzed by the analysis unit;
The decision device according to any one of claims 1 to 9 , characterized in that: The decision unit
Determining a scene in which the content selected by the user is displayed based on the analysis result analyzed by the analysis unit;
The decision device according to any one of claims 1 to 10 , characterized in that: The analysis unit is
Analyze the characteristics of the scene in which the content of the information related to the moving image including the content is superimposed, which is information related to the moving image broadcast in the past,
The decision unit
determining the scene based on features of the scene analyzed by the analysis unit;
The decision device according to any one of claims 1 to 11 , characterized in that: Further comprising a distribution unit that distributes content including content to be superimposed on the scene determined by the determination unit,
The decision device according to any one of claims 1 to 12 , characterized in that: The distribution unit
Distributing content that is displayed around the moving image and that includes other content that is different from the content.
14. A decision device according to claim 13 , characterized in that: The distribution unit
Distributing content including content displayed around the moving image and content linked to the content;
15. A decision device according to claim 13 or 14 , characterized in that: A computer implemented method of determination comprising:
an analysis step of analyzing each scene that constitutes information about a video;
a determining step of determining a scene in which content to be superimposed on the moving image is displayed based on the analysis result analyzed by the analyzing step;
including
The determining step includes:
A product tag indicating the identification information of the product linked to the product displayed in the video based on the analysis result analyzed by the analysis step, wherein when the product tag is clicked by the user, the product is identified. Determining the scene for superimposing the product tag for displaying the content ;
A determination method characterized by: an analysis procedure for analyzing each scene that constitutes information about a video;
a determination procedure for determining a scene in which content to be superimposed on the moving image is displayed based on the analysis result analyzed by the analysis procedure;
on the computer, and
The determination procedure includes:
A product tag indicating identification information of a product linked to the product displayed in the video based on the analysis result analyzed by the analysis procedure, wherein when the product tag is clicked by the user, the product is identified. Determining the scene for superimposing the product tag for displaying the content ;
A decision program characterized by:

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