System

Abstract

An object of a system according to an embodiment is to enable a user to easily take a clear photograph.SOLUTION: A system includes a position information acquisition part, an imaging plan proposal part, and a grid display part. The position information acquisition unit acquires the position information only by activating the application at a place where the user wants to capture an image. The imaging plan proposal unit proposes an imaging plan suitable for the user on the basis of the position information acquired by the position information acquisition unit. The grid display unit displays a grid on the screen on the basis of the composition proposed by the imaging plan proposal unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] With conventional technology, it is difficult to find the optimal angle and composition when taking a photo, making it particularly difficult for beginners to take eye-catching photos.

[0005] The system according to the embodiment aims to enable a user to easily take attractive photos. [Means for solving the problem]

[0006] The system according to the embodiment includes a location information acquisition unit, a photography plan proposal unit, and a grid display unit. The location information acquisition unit acquires location information simply by launching an app at a location where a user wants to take a photo. The photography plan proposal unit proposes a photography plan suited to the user based on the location information acquired by the location information acquisition unit. The grid display unit displays a grid on the screen based on the composition proposed by the photography plan proposal unit. [Effects of the Invention]

[0007] The system according to the embodiment can enable a user to easily take attractive photos. [Brief explanation of the drawings]

[0008] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. DETAILED DESCRIPTION OF THE INVENTION

[0009] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0010] First, the terms used in the following description will be explained.

[0011] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0013] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0014] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), and Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0019] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. Camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) In the photography support system according to an embodiment of the present invention, a user simply launches the app at the location where they want to take a photo, and the AI ​​generator proposes the best angles, compositions, and poses in real time, and displays a grid on the screen. This allows the user to easily take great photos.

[0029] A photography support system according to an embodiment includes a generation AI, a location information acquisition unit, a photography plan proposal unit, and a grid display unit. The generation AI acquires location information simply by launching an app at a location where a user wants to take a photo. For example, the current location is identified using GPS. It can also identify an indoor location using Wi-Fi location information. The generation AI then proposes a photography plan tailored to the user based on the location information acquired by the location information acquisition unit. For example, the generation AI considers the characteristics of a tourist spot to suggest the most effective photography spot and pose. The generation AI can also suggest optimal angles and compositions based on the user's preferences and style. The generation AI then displays a grid on the screen based on the composition proposed by the photography plan proposal unit. For example, it displays auxiliary lines for the golden ratio and the rule of thirds. The generation AI can also guide the user to follow the grid when holding the camera. This allows the photography support system to easily take eye-catching photos. The system can be used in a variety of situations, such as commemorative photos at tourist spots and photos to post on social media. Furthermore, the photography plan proposals and the display of auxiliary lines can improve photography skills and enable users to take higher-quality photos.

[0030] The photo shoot plan suggestion unit analyzes the user's past photo data and can suggest angles, compositions, and poses based on the user's preferences and style. For example, the photo shoot plan suggestion unit uses a generation AI to collect the user's past photo data and identify the user's preferences and style using image analysis technology. For example, it analyzes the scenery and poses the user often photographs and suggests optimal angles and compositions based on that. The photo shoot plan suggestion unit also stores the user's past photo data in the cloud, and the generation AI learns the user's photography habits based on that data. For example, it identifies the user's preferred color and composition patterns and makes suggestions based on those. The photo shoot plan suggestion unit also analyzes the user's past photo data and suggests angles, compositions, and poses based on a specific style or theme. For example, it suggests optimal photo spots and poses based on photos of theme parks that the user often photographs. This allows the system to provide a photo shoot plan that suits the user's preferences.

[0031] The photography plan proposal unit can detect weather and light conditions in real time and propose optimal photography conditions accordingly. For example, the generation AI in the photography plan proposal unit obtains weather data in real time and proposes angles and compositions that are optimal for the current weather. For example, on a cloudy day, it will propose a photography spot that makes use of soft light. The photography plan proposal unit also uses the generation AI to detect light conditions using the camera's sensors and proposes optimal photography conditions based on that. For example, it will propose angles that avoid backlighting and compositions that make use of reflected light. The photography plan proposal unit also uses the generation AI to propose the optimal time of day for photography based on weather forecast data. For example, it will propose photography spots and poses that are optimal for the golden hour in the evening. This makes it possible to provide optimal photography conditions in real time.

[0032] The grid display unit can have a function that allows the user to apply their preferred filters and effects in real time. For example, the grid display unit provides an interface that allows the user to apply filters in real time to angles and compositions suggested by the generation AI. For example, the user can select filters such as monochrome or sepia. The grid display unit also adds a function that allows the user to preview effects in real time when taking a photo based on the generation AI's suggestions. For example, the user can take a photo by applying a bokeh or vignette effect. The grid display unit also provides a function that allows the user to apply their preferred effects to poses suggested by the generation AI. For example, the user can select retro or pop art effects. This allows the user to apply their preferred filters and effects in real time.

[0033] The photography plan proposal unit can have a function to customize angles, compositions, and poses based on the aesthetic sensibilities of different cultures and regions. In the photography plan proposal unit, for example, the generation AI learns the aesthetic sensibilities of different cultures and regions and customizes angles and compositions based on that. For example, it proposes a composition based on traditional Japanese aesthetic sensibilities. In addition, the photography plan proposal unit has the generation AI propose optimal poses according to the region and culture selected by the user. For example, it proposes poses based on classical European aesthetic sensibilities. In addition, the photography plan proposal unit has the generation AI take into account the aesthetic sensibilities of different cultures and regions and propose a photography plan that suits the user. For example, it proposes angles and compositions based on modern Asian aesthetic sensibilities. This makes it possible to provide photography plans based on the aesthetic sensibilities of different cultures and regions.

[0034] The location information acquisition unit can analyze popular photos taken at that location in the past and propose the most eye-catching photo shoot plan. For example, the generation AI acquires location information and searches a database for popular photos taken at that location in the past. For example, it identifies famous photo spots in tourist destinations and proposes the optimal photo shoot plan. The location information acquisition unit also allows the generation AI to collect and analyze popular photos from social media and photo sharing sites based on location information. For example, it refers to photos that have received many likes at specific locations. The location information acquisition unit also allows the generation AI to analyze the shooting conditions of past popular photos based on location information and propose the optimal photo shoot plan based on that. For example, it proposes a photo shoot plan that takes into account specific time periods and weather conditions. This allows the generation AI to provide the optimal photo shoot plan based on past popular photos.

[0035] The location information acquisition unit can suggest the optimal shooting time and light angle based on the location information and time of day. For example, the generation AI in the location information acquisition unit acquires location information and suggests the optimal shooting time according to the time of day at that location. For example, it suggests a shooting plan that takes into account the time of sunrise or sunset. The location information acquisition unit also analyzes the light angle based on the location information and time of day and suggests the optimal shooting conditions. For example, it suggests angles and compositions to avoid backlighting. The location information acquisition unit also considers the location information and time of day and suggests the best shooting spot for a specific time of day. For example, it suggests the best shooting spot during bright daytime hours. This makes it possible to provide the optimal shooting time and light angle.

[0036] The location information acquisition unit can provide information on nearby tourist spots and events based on the location information and propose a photography plan that matches that. For example, the generation AI in the location information acquisition unit acquires location information and searches a database for information on nearby tourist spots and events. For example, it can propose a photography plan that matches an event being held nearby. The location information acquisition unit also identifies nearby tourist spots based on the location information and proposes the optimal photography plan that matches them. For example, it can introduce famous tourist spots and hidden gems. The location information acquisition unit also collects information on nearby events based on the location information and proposes a photography plan that matches that. For example, it can propose the best photography spots for seasonal events and festivals. This makes it possible to provide a photography plan based on information on nearby tourist spots and events.

[0037] The location information acquisition unit can analyze the user's movement history based on the location information and propose a photo shoot plan that is related to places visited in the past. For example, the generation AI in the location information acquisition unit analyzes the user's movement history and proposes an optimal photo shoot plan based on the relationship with places visited in the past. For example, it considers the similarities between tourist spots visited in the past and the current location. The location information acquisition unit also analyzes the user's movement patterns based on the location information and proposes a photo shoot plan based on that. For example, it proposes photo shoot spots that match places the user frequently visits. The location information acquisition unit also proposes a photo shoot plan that is related to places visited in the past based on the user's movement history. For example, it proposes a photo shoot plan that takes into account the common theme between past travel destinations and the current location. This makes it possible to provide a photo shoot plan based on the user's movement history.

[0038] The grid display unit can have a function that detects the user's camera shake and camera tilt in real time and automatically corrects them. For example, the grid display unit provides a function that allows the generation AI to detect camera shake in real time using a camera sensor and automatically correct it. For example, it stabilizes the image using a camera shake correction algorithm. The grid display unit also adds a function that allows the generation AI to detect the camera tilt and automatically correct it to maintain horizontality. For example, it analyzes the camera tilt in real time and automatically rotates the image. The grid display unit also allows the generation AI to detect the user's camera shake and camera tilt and display guidelines for correction. For example, it displays horizontal and vertical lines on the screen to guide the user to hold the camera correctly. This allows the generation AI to automatically correct camera shake and camera tilt.

[0039] The grid display unit recognizes the user's face and can suggest the optimal facial position and expression. For example, the generation AI uses the camera's facial recognition function to detect the user's face and suggest the optimal facial position. For example, it displays guidelines to keep the face in the center of the screen. The generation AI also analyzes the user's facial expression and suggests the optimal expression. For example, it provides advice on how to bring out a smile or a natural expression. The generation AI also uses facial recognition technology to suggest the optimal position when there are multiple people. For example, it displays guidelines to keep everyone's faces evenly visible in a group photo. This makes it possible to suggest the optimal facial position and expression.

[0040] The grid display unit has a function that allows users to customize the grid, making it possible to provide shooting assistance tailored to individual preferences. For example, the grid display unit provides a function that allows users to customize the color and design of the grid suggested by the generation AI. For example, the user can select their favorite color or pattern. The grid display unit also adds a function that allows users to adjust the display position and size of the grid based on suggestions from the generation AI. For example, the grid position can be changed by dragging and dropping. The grid display unit also provides a function that allows users to save customized settings for the grid suggested by the generation AI and reflect them in subsequent shooting. For example, the user can save their preferred settings as a preset. This allows users to customize the grid.

[0041] The grid display unit can have a function to accommodate different shooting modes. For example, the grid display unit provides a function to accommodate the grid proposed by the generation AI to panoramic shooting mode. For example, it displays auxiliary lines that are optimal for panoramic shooting. The grid display unit also adds a function to accommodate the grid proposed by the generation AI to macro shooting mode. For example, it displays auxiliary lines that are optimal when approaching a subject. The grid display unit also provides a function to automatically switch the grid proposed by the generation AI according to different shooting modes. For example, it displays auxiliary lines that are optimal for landscape shooting mode or portrait shooting mode. This makes it possible to accommodate different shooting modes.

[0042] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0043] The photo shoot plan suggestion unit analyzes the user's past photo data and can suggest angles, compositions, and poses based on the user's preferences and style. For example, the generation AI collects the user's past photo data and uses image analysis technology to identify the user's preferences and style. It analyzes the scenery and poses the user often photographs and suggests optimal angles and compositions based on that. The photo shoot plan suggestion unit also stores the user's past photo data in the cloud, and the generation AI uses that data to learn the user's photography habits. It identifies the user's preferred color and composition patterns and makes suggestions based on those. Furthermore, the generation AI analyzes the user's past photo data and suggests angles, compositions, and poses based on a specific style or theme. For example, it suggests optimal photo spots and poses based on photos of theme parks that the user often photographs. This allows the system to provide a photo shoot plan that suits the user's preferences.

[0044] The shooting plan suggestion unit can detect weather and light conditions in real time and suggest the optimal shooting conditions accordingly. For example, the generation AI obtains weather data in real time and suggests angles and compositions that are best suited to the current weather. On cloudy days, it suggests shooting spots that make the most of soft light. The generation AI also uses the camera's sensors to detect light conditions and suggests the optimal shooting conditions based on that. It can suggest angles that avoid backlighting and compositions that make use of reflected light. Furthermore, the generation AI suggests the optimal time of day for shooting based on weather forecast data. It can also suggest shooting spots and poses that are best suited to the golden hour in the evening. This makes it possible to provide optimal shooting conditions in real time.

[0045] The grid display section can be equipped with a function that allows users to apply their preferred filters and effects in real time. For example, an interface can be provided that allows users to apply filters in real time to angles and compositions suggested by the generation AI. Filters such as monochrome and sepia can be selected. A function can also be added that allows users to preview effects in real time when taking a photo based on the generation AI's suggestions. Bokeh and vignette effects can be applied when taking a photo. Furthermore, a function can be provided that allows users to apply their preferred effects to poses suggested by the generation AI. Retro and pop art effects can be selected. This allows users to apply their preferred filters and effects in real time.

[0046] The photo shoot plan suggestion unit can have a function to customize angles, compositions, and poses based on the aesthetic sensibilities of different cultures and regions. For example, the generation AI can learn the aesthetic sensibilities of different cultures and regions and customize angles and compositions based on that. It can propose compositions based on traditional Japanese aesthetic sensibilities. The generation AI can also propose optimal poses based on the region and culture selected by the user. It can propose poses based on classical European aesthetic sensibilities. Furthermore, the generation AI can take into account the aesthetic sensibilities of different cultures and regions to propose a photo shoot plan that suits the user. It can also propose angles and compositions based on modern Asian aesthetic sensibilities. This makes it possible to provide photo shoot plans based on the aesthetic sensibilities of different cultures and regions.

[0047] The location information acquisition unit can analyze popular photos taken at that location in the past and suggest the most attractive photo shoot plan. For example, the generation AI acquires location information and searches a database for popular photos taken at that location in the past. It can identify famous photo spots at tourist destinations and suggest the optimal photo shoot plan. The generation AI also collects and analyzes popular photos from social media and photo sharing sites based on location information. Photos that have received many likes at specific locations can be used as reference. Furthermore, the generation AI analyzes the shooting conditions of popular photos from the past based on location information and suggests the optimal photo shoot plan based on that. It can also suggest photo shoot plans that take into account specific time periods and weather conditions. This makes it possible to provide the optimal photo shoot plan based on popular photos from the past.

[0048] The location information acquisition unit can suggest the optimal shooting time and light angle based on the location information and time of day. For example, the generation AI acquires location information and suggests the optimal shooting time according to the time of day at that location. It can propose a shooting plan that takes into account the times of sunrise and sunset. The generation AI can also analyze the light angle based on the location information and time of day and suggest the optimal shooting conditions. It can suggest angles and compositions to avoid backlighting. Furthermore, the generation AI takes location information and time of day into consideration and suggests shooting spots that look best at specific times of day. It can also suggest the best shooting spots during bright daylight hours. This makes it possible to provide the optimal shooting time and light angle.

[0049] The location information acquisition unit can provide information on nearby tourist spots and events based on the location information and propose a photography plan that matches it. For example, the generation AI acquires location information and searches a database for information on nearby tourist spots and events. It can propose a photography plan that matches an event being held nearby. The generation AI can also identify nearby tourist spots based on the location information and propose the optimal photography plan that matches them. It can introduce famous tourist spots and hidden gems. Furthermore, the generation AI can collect information on nearby events based on the location information and propose a photography plan that matches it. It can also suggest the best photography spots for seasonal events and festivals. This makes it possible to provide a photography plan based on information on nearby tourist spots and events.

[0050] The processing flow of the first embodiment will be briefly explained below.

[0051] Step 1: The location information acquisition unit acquires location information simply by launching the app at the location where the user wants to take a photo. For example, the current location can be identified using GPS, and the indoor location can be identified using Wi-Fi location information. Step 2: The photography plan suggestion unit proposes a photography plan suited to the user based on the location information acquired by the location information acquisition unit. For example, it considers the characteristics of tourist spots and suggests the most attractive photography points and poses, and suggests optimal angles and compositions based on the user's preferences and style. Step 3: The grid display unit displays a grid on the screen based on the composition proposed by the photography plan proposal unit. For example, it displays auxiliary lines for the golden ratio or the rule of thirds, and guides the user to follow the grid when holding the camera.

[0052] (Example 2) In the photography support system according to an embodiment of the present invention, a user simply launches the app at the location where they want to take a photo, and the AI ​​generator proposes the best angles, compositions, and poses in real time, and displays a grid on the screen. This allows the user to easily take great photos.

[0053] A photography support system according to an embodiment includes a generation AI, a location information acquisition unit, a photography plan proposal unit, and a grid display unit. The generation AI acquires location information simply by launching an app at a location where a user wants to take a photo. For example, the current location is identified using GPS. It can also identify an indoor location using Wi-Fi location information. The generation AI then proposes a photography plan tailored to the user based on the location information acquired by the location information acquisition unit. For example, the generation AI considers the characteristics of a tourist spot to suggest the most effective photography spot and pose. The generation AI can also suggest optimal angles and compositions based on the user's preferences and style. The generation AI then displays a grid on the screen based on the composition proposed by the photography plan proposal unit. For example, it displays auxiliary lines for the golden ratio and the rule of thirds. The generation AI can also guide the user to follow the grid when holding the camera. This allows the photography support system to easily take eye-catching photos. The system can be used in a variety of situations, such as commemorative photos at tourist spots and photos to post on social media. Furthermore, the photography plan proposals and the display of auxiliary lines can improve photography skills and enable users to take higher-quality photos.

[0054] The photo shoot plan suggestion unit analyzes the user's past photo data and can suggest angles, compositions, and poses based on the user's preferences and style. For example, the photo shoot plan suggestion unit uses a generation AI to collect the user's past photo data and identify the user's preferences and style using image analysis technology. For example, it analyzes the scenery and poses the user often photographs and suggests optimal angles and compositions based on that. The photo shoot plan suggestion unit also stores the user's past photo data in the cloud, and the generation AI learns the user's photography habits based on that data. For example, it identifies the user's preferred color and composition patterns and makes suggestions based on those. The photo shoot plan suggestion unit also analyzes the user's past photo data and suggests angles, compositions, and poses based on a specific style or theme. For example, it suggests optimal photo spots and poses based on photos of theme parks that the user often photographs. This allows the system to provide a photo shoot plan that suits the user's preferences.

[0055] The photography plan proposal unit can detect weather and light conditions in real time and propose optimal photography conditions accordingly. For example, the generation AI in the photography plan proposal unit obtains weather data in real time and proposes angles and compositions that are optimal for the current weather. For example, on a cloudy day, it will propose a photography spot that makes use of soft light. The photography plan proposal unit also uses the generation AI to detect light conditions using the camera's sensors and proposes optimal photography conditions based on that. For example, it will propose angles that avoid backlighting and compositions that make use of reflected light. The photography plan proposal unit also uses the generation AI to propose the optimal time of day for photography based on weather forecast data. For example, it will propose photography spots and poses that are optimal for the golden hour in the evening. This makes it possible to provide optimal photography conditions in real time.

[0056] The photo shoot plan suggestion unit uses the emotion estimation function to analyze the user's current emotional state and suggest angles, compositions, and poses that match that emotion. In the photo shoot plan suggestion unit, for example, the generation AI analyzes the user's facial expression to estimate the user's current emotional state. For example, if the user is smiling, it suggests angles and compositions that create a bright and cheerful atmosphere. The photo shoot plan suggestion unit also uses the emotion estimation function to analyze the user's vocal tone to identify the user's emotional state. For example, if the user is relaxed, it suggests calm scenery and poses. The photo shoot plan suggestion unit also uses the generation AI to suggest photo shoot plans that match the user's emotions based on the user's emotional data. For example, if the user is excited, it suggests dynamic angles and compositions that include movement. This makes it possible to provide a photo shoot plan that matches the user's emotions.

[0057] The grid display unit can have a function that allows the user to apply their preferred filters and effects in real time. For example, the grid display unit provides an interface that allows the user to apply filters in real time to angles and compositions suggested by the generation AI. For example, the user can select filters such as monochrome or sepia. The grid display unit also adds a function that allows the user to preview effects in real time when taking a photo based on the generation AI's suggestions. For example, the user can take a photo by applying a bokeh or vignette effect. The grid display unit also provides a function that allows the user to apply their preferred effects to poses suggested by the generation AI. For example, the user can select retro or pop art effects. This allows the user to apply their preferred filters and effects in real time.

[0058] The photography plan proposal unit can have a function to customize angles, compositions, and poses based on the aesthetic sensibilities of different cultures and regions. In the photography plan proposal unit, for example, the generation AI learns the aesthetic sensibilities of different cultures and regions and customizes angles and compositions based on that. For example, it proposes a composition based on traditional Japanese aesthetic sensibilities. In addition, the photography plan proposal unit has the generation AI propose optimal poses according to the region and culture selected by the user. For example, it proposes poses based on classical European aesthetic sensibilities. In addition, the photography plan proposal unit has the generation AI take into account the aesthetic sensibilities of different cultures and regions and propose a photography plan that suits the user. For example, it proposes angles and compositions based on modern Asian aesthetic sensibilities. This makes it possible to provide photography plans based on the aesthetic sensibilities of different cultures and regions.

[0059] The photography plan suggestion unit can use the emotion estimation function to make suggestions that have a relaxing effect to reduce the stress and anxiety the user feels while taking photos. For example, the photography plan suggestion unit uses the emotion estimation function to detect the stress the user feels while taking photos and suggest angles and compositions that have a relaxing effect. For example, it can suggest natural scenery or gentle poses. The photography plan suggestion unit also uses the generation AI to analyze the user's emotional state and suggest photography plans that have a relaxing effect. For example, it can play messages encouraging deep breathing or relaxing music. The photography plan suggestion unit also uses the emotion estimation function to provide advice to reduce the anxiety the user feels while taking photos. For example, it can suggest simple stretches or relaxing poses. This allows the user to relax while taking photos.

[0060] The location information acquisition unit can analyze popular photos taken at that location in the past and propose the most eye-catching photo shoot plan. For example, the generation AI acquires location information and searches a database for popular photos taken at that location in the past. For example, it identifies famous photo spots in tourist destinations and proposes the optimal photo shoot plan. The location information acquisition unit also allows the generation AI to collect and analyze popular photos from social media and photo sharing sites based on location information. For example, it refers to photos that have received many likes at specific locations. The location information acquisition unit also allows the generation AI to analyze the shooting conditions of past popular photos based on location information and propose the optimal photo shoot plan based on that. For example, it proposes a photo shoot plan that takes into account specific time periods and weather conditions. This allows the generation AI to provide the optimal photo shoot plan based on past popular photos.

[0061] The location information acquisition unit can suggest the optimal shooting time and light angle based on the location information and time of day. For example, the generation AI in the location information acquisition unit acquires location information and suggests the optimal shooting time according to the time of day at that location. For example, it suggests a shooting plan that takes into account the time of sunrise or sunset. The location information acquisition unit also analyzes the light angle based on the location information and time of day and suggests the optimal shooting conditions. For example, it suggests angles and compositions to avoid backlighting. The location information acquisition unit also considers the location information and time of day and suggests the best shooting spot for a specific time of day. For example, it suggests the best shooting spot during bright daytime hours. This makes it possible to provide the optimal shooting time and light angle.

[0062] The location information acquisition unit can use the emotion estimation function to propose a photography plan based on the emotions the user feels at that location. For example, the location information acquisition unit uses the emotion estimation function to analyze the emotions the user feels at that location and propose a photography plan based on that. For example, if the user is relaxed, it proposes calm scenery and poses. The location information acquisition unit also uses the generation AI to propose the optimal photography plan for that location based on the user's emotional state. For example, if the user is excited, it proposes dynamic angles and compositions with movement. The location information acquisition unit also uses the emotion estimation function to propose a photography plan based on the emotions the user feels at that location. For example, if the user is moved, it proposes photography points and poses that will bring out the emotion. This makes it possible to provide a photography plan based on the user's emotions.

[0063] The location information acquisition unit can provide information on nearby tourist spots and events based on the location information and propose a photography plan that matches that. For example, the generation AI in the location information acquisition unit acquires location information and searches a database for information on nearby tourist spots and events. For example, it can propose a photography plan that matches an event being held nearby. The location information acquisition unit also identifies nearby tourist spots based on the location information and proposes the optimal photography plan that matches them. For example, it can introduce famous tourist spots and hidden gems. The location information acquisition unit also collects information on nearby events based on the location information and proposes a photography plan that matches that. For example, it can propose the best photography spots for seasonal events and festivals. This makes it possible to provide a photography plan based on information on nearby tourist spots and events.

[0064] The location information acquisition unit can analyze the user's movement history based on the location information and propose a photo shoot plan that is related to places visited in the past. For example, the generation AI in the location information acquisition unit analyzes the user's movement history and proposes an optimal photo shoot plan based on the relationship with places visited in the past. For example, it considers the similarities between tourist spots visited in the past and the current location. The location information acquisition unit also analyzes the user's movement patterns based on the location information and proposes a photo shoot plan based on that. For example, it proposes photo shoot spots that match places the user frequently visits. The location information acquisition unit also proposes a photo shoot plan that is related to places visited in the past based on the user's movement history. For example, it proposes a photo shoot plan that takes into account the common theme between past travel destinations and the current location. This makes it possible to provide a photo shoot plan based on the user's movement history.

[0065] The location information acquisition unit can use the emotion estimation function to suggest relaxation spots or rest areas based on the emotions the user feels at that location. For example, the location information acquisition unit uses the emotion estimation function to analyze the emotions the user feels at that location and suggest relaxation spots or rest areas. For example, if the user is tired, it suggests a quiet place. The location information acquisition unit also uses the generation AI to suggest relaxation spots or rest areas at that location based on the user's emotional state. For example, if the user is feeling stressed, it suggests a cafe or park where they can relax. The location information acquisition unit also uses the emotion estimation function to suggest relaxation spots or rest areas based on the emotions the user feels at that location. For example, if the user wants to refresh themselves, it suggests a rest area in nature. This makes it possible to provide relaxation spots and rest areas based on the user's emotions.

[0066] The grid display unit can have a function that detects the user's camera shake and camera tilt in real time and automatically corrects them. For example, the grid display unit provides a function that allows the generation AI to detect camera shake in real time using a camera sensor and automatically correct it. For example, it stabilizes the image using a camera shake correction algorithm. The grid display unit also adds a function that allows the generation AI to detect the camera tilt and automatically correct it to maintain horizontality. For example, it analyzes the camera tilt in real time and automatically rotates the image. The grid display unit also allows the generation AI to detect the user's camera shake and camera tilt and display guidelines for correction. For example, it displays horizontal and vertical lines on the screen to guide the user to hold the camera correctly. This allows the generation AI to automatically correct camera shake and camera tilt.

[0067] The grid display unit recognizes the user's face and can suggest the optimal facial position and expression. For example, the generation AI uses the camera's facial recognition function to detect the user's face and suggest the optimal facial position. For example, it displays guidelines to keep the face in the center of the screen. The generation AI also analyzes the user's facial expression and suggests the optimal expression. For example, it provides advice on how to bring out a smile or a natural expression. The generation AI also uses facial recognition technology to suggest the optimal position when there are multiple people. For example, it displays guidelines to keep everyone's faces evenly visible in a group photo. This makes it possible to suggest the optimal facial position and expression.

[0068] The grid display unit uses the emotion estimation function to change the color and design of the grid according to the user's emotions, thereby improving the enjoyment of photography. For example, the grid display unit uses the emotion estimation function to analyze the user's emotional state and change the color of the grid accordingly. For example, if the user is relaxed, it displays a grid with calm colors. The grid display unit also changes the grid design using a generation AI based on the user's emotional state. For example, if the user is excited, it displays a grid with a dynamic design. The grid display unit also uses the emotion estimation function to suggest a grid theme according to the user's emotions. For example, if the user is moved, it displays a grid with a design that enhances the emotion. This makes it possible to change the color and design of the grid according to the user's emotions.

[0069] The grid display unit has a function that allows users to customize the grid, making it possible to provide shooting assistance tailored to individual preferences. For example, the grid display unit provides a function that allows users to customize the color and design of the grid suggested by the generation AI. For example, the user can select their favorite color or pattern. The grid display unit also adds a function that allows users to adjust the display position and size of the grid based on suggestions from the generation AI. For example, the grid position can be changed by dragging and dropping. The grid display unit also provides a function that allows users to save customized settings for the grid suggested by the generation AI and reflect them in subsequent shooting. For example, the user can save their preferred settings as a preset. This allows users to customize the grid.

[0070] The grid display unit can have a function to accommodate different shooting modes. For example, the grid display unit provides a function to accommodate the grid proposed by the generation AI to panoramic shooting mode. For example, it displays auxiliary lines that are optimal for panoramic shooting. The grid display unit also adds a function to accommodate the grid proposed by the generation AI to macro shooting mode. For example, it displays auxiliary lines that are optimal when approaching a subject. The grid display unit also provides a function to automatically switch the grid proposed by the generation AI according to different shooting modes. For example, it displays auxiliary lines that are optimal for landscape shooting mode or portrait shooting mode. This makes it possible to accommodate different shooting modes.

[0071] The grid display unit uses the emotion estimation function to display audio guidance and animation based on the emotions the user feels while shooting, thereby improving the shooting experience. For example, the grid display unit uses the emotion estimation function to analyze the emotions the user feels while shooting and provide audio guidance based on the analysis. For example, if the user is nervous, audio advice to relax is provided. The grid display unit also changes the animation displayed during shooting based on the user's emotional state using the generation AI. For example, if the user is having fun, a fun animation is displayed. The grid display unit also uses the emotion estimation function to provide audio guidance and animation in real time according to the emotions the user feels while shooting. For example, if the user is moved, audio guidance and animation that enhances the emotion are displayed. This makes it possible to provide audio guidance and animation based on the user's emotions.

[0072] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0073] The photo shoot plan suggestion unit analyzes the user's past photo data and can suggest angles, compositions, and poses based on the user's preferences and style. For example, the generation AI collects the user's past photo data and uses image analysis technology to identify the user's preferences and style. It analyzes the scenery and poses the user often photographs and suggests optimal angles and compositions based on that. The photo shoot plan suggestion unit also stores the user's past photo data in the cloud, and the generation AI uses that data to learn the user's photography habits. It identifies the user's preferred color and composition patterns and makes suggestions based on those. Furthermore, the generation AI analyzes the user's past photo data and suggests angles, compositions, and poses based on a specific style or theme. For example, it suggests optimal photo spots and poses based on photos of theme parks that the user often photographs. This allows the system to provide a photo shoot plan that suits the user's preferences.

[0074] The shooting plan suggestion unit can detect weather and light conditions in real time and suggest the optimal shooting conditions accordingly. For example, the generation AI obtains weather data in real time and suggests angles and compositions that are best suited to the current weather. On cloudy days, it suggests shooting spots that make the most of soft light. The generation AI also uses the camera's sensors to detect light conditions and suggests the optimal shooting conditions based on that. It can suggest angles that avoid backlighting and compositions that make use of reflected light. Furthermore, the generation AI suggests the optimal time of day for shooting based on weather forecast data. It can also suggest shooting spots and poses that are best suited to the golden hour in the evening. This makes it possible to provide optimal shooting conditions in real time.

[0075] The photo shoot plan suggestion unit uses the emotion estimation function to analyze the user's current emotional state and suggest angles, compositions, and poses that match that emotion. For example, the generation AI analyzes the user's facial expression to estimate their current emotional state. If the user is smiling, it suggests angles and compositions that create a bright and cheerful atmosphere. The emotion estimation function can also be used to analyze the user's vocal tone to identify their emotional state. If the user is relaxed, it can suggest calm scenery and poses. Furthermore, the generation AI suggests photo shoot plans that match the user's emotions based on the user's emotional data. If the user is excited, it can also suggest dynamic angles and compositions that include movement. This makes it possible to provide a photo shoot plan that matches the user's emotions.

[0076] The grid display section can be equipped with a function that allows users to apply their preferred filters and effects in real time. For example, an interface can be provided that allows users to apply filters in real time to angles and compositions suggested by the generation AI. Filters such as monochrome and sepia can be selected. A function can also be added that allows users to preview effects in real time when taking a photo based on the generation AI's suggestions. Bokeh and vignette effects can be applied when taking a photo. Furthermore, a function can be provided that allows users to apply their preferred effects to poses suggested by the generation AI. Retro and pop art effects can be selected. This allows users to apply their preferred filters and effects in real time.

[0077] The photo shoot plan suggestion unit can have a function to customize angles, compositions, and poses based on the aesthetic sensibilities of different cultures and regions. For example, the generation AI can learn the aesthetic sensibilities of different cultures and regions and customize angles and compositions based on that. It can propose compositions based on traditional Japanese aesthetic sensibilities. The generation AI can also propose optimal poses based on the region and culture selected by the user. It can propose poses based on classical European aesthetic sensibilities. Furthermore, the generation AI can take into account the aesthetic sensibilities of different cultures and regions to propose a photo shoot plan that suits the user. It can also propose angles and compositions based on modern Asian aesthetic sensibilities. This makes it possible to provide photo shoot plans based on the aesthetic sensibilities of different cultures and regions.

[0078] The photography plan suggestion unit can use the emotion estimation function to make suggestions that have a relaxing effect to reduce the stress and anxiety the user feels while taking photos. For example, the emotion estimation function can be used to detect the stress the user feels while taking photos and suggest angles and compositions that have a relaxing effect. Natural scenery and gentle poses can be suggested. The generation AI can also analyze the user's emotional state and suggest photography plans that have a relaxing effect. Messages encouraging deep breathing and relaxing music can be played. Furthermore, the emotion estimation function can be used to provide advice to reduce the anxiety the user feels while taking photos. Simple stretches and relaxing poses can also be suggested. This allows the user to relax while taking photos.

[0079] The location information acquisition unit can analyze popular photos taken at that location in the past and suggest the most attractive photo shoot plan. For example, the generation AI acquires location information and searches a database for popular photos taken at that location in the past. It can identify famous photo spots at tourist destinations and suggest the optimal photo shoot plan. The generation AI also collects and analyzes popular photos from social media and photo sharing sites based on location information. Photos that have received many likes at specific locations can be used as reference. Furthermore, the generation AI analyzes the shooting conditions of popular photos from the past based on location information and suggests the optimal photo shoot plan based on that. It can also suggest photo shoot plans that take into account specific time periods and weather conditions. This makes it possible to provide the optimal photo shoot plan based on popular photos from the past.

[0080] The location information acquisition unit can suggest the optimal shooting time and light angle based on the location information and time of day. For example, the generation AI acquires location information and suggests the optimal shooting time according to the time of day at that location. It can propose a shooting plan that takes into account the times of sunrise and sunset. The generation AI can also analyze the light angle based on the location information and time of day and suggest the optimal shooting conditions. It can suggest angles and compositions to avoid backlighting. Furthermore, the generation AI takes location information and time of day into consideration and suggests shooting spots that look best at specific times of day. It can also suggest the best shooting spots during bright daylight hours. This makes it possible to provide the optimal shooting time and light angle.

[0081] The location information acquisition unit can use the emotion estimation function to propose a photo shoot plan based on the emotions the user feels at the location. For example, the emotion estimation function can be used to analyze the emotions the user feels at the location and propose a photo shoot plan based on that. If the user is relaxed, it can propose calm scenery and poses. In addition, the generation AI proposes the optimal photo shoot plan for the location based on the user's emotional state. If the user is excited, it can propose dynamic angles and compositions with movement. Furthermore, the emotion estimation function can be used to propose a photo shoot plan based on the emotions the user feels at the location. If the user is moved, it can also suggest photo shoot points and poses that will bring out their emotions. This makes it possible to provide a photo shoot plan based on the user's emotions.

[0082] The location information acquisition unit can provide information on nearby tourist spots and events based on the location information and propose a photography plan that matches it. For example, the generation AI acquires location information and searches a database for information on nearby tourist spots and events. It can propose a photography plan that matches an event being held nearby. The generation AI can also identify nearby tourist spots based on the location information and propose the optimal photography plan that matches them. It can introduce famous tourist spots and hidden gems. Furthermore, the generation AI can collect information on nearby events based on the location information and propose a photography plan that matches it. It can also suggest the best photography spots for seasonal events and festivals. This makes it possible to provide a photography plan based on information on nearby tourist spots and events.

[0083] The processing flow of the second embodiment will be briefly explained below.

[0084] Step 1: The location information acquisition unit acquires location information simply by launching the app at the location where the user wants to take a photo. For example, the current location can be identified using GPS, and the indoor location can be identified using Wi-Fi location information. Step 2: The photography plan suggestion unit proposes a photography plan suited to the user based on the location information acquired by the location information acquisition unit. For example, it considers the characteristics of tourist spots and suggests the most attractive photography points and poses, and suggests optimal angles and compositions based on the user's preferences and style. Step 3: The grid display unit displays a grid on the screen based on the composition proposed by the photography plan proposal unit. For example, it displays auxiliary lines for the golden ratio or the rule of thirds, and guides the user to follow the grid when holding the camera.

[0085] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0086] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0087] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0088] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0089] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0090] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0091] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0092] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0093] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0094] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0095] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0096] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0097] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0098] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0099] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0100] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0101] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0102] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0103] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0104] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0105] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0106] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0107] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0108] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0109] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0110] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0111] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0112] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0113] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0114] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0115] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0116] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0117] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0118] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0119] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0120] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN and / or a LAN.

[0121] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[0122] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0123] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0124] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0125] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[0126] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0127] The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0128] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0129] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0130] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0131] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[0132] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0133] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0134] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0135] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[0136] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[0137] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[0138] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0139] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[0140] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[0141] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0142] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0143] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0144] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0145] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A processor also includes a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0146] The hardware resource that executes the specific process may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific process may be a single processor.

[0147] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0148] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0149] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0150] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0151] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0152] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. Equipped with generative AI, A location information acquisition unit that acquires location information by simply launching the app at the location where the user wants to take a photo; a photography plan suggestion unit that suggests a photography plan suited to a user based on the location information acquired by the location information acquisition unit; a grid display unit that displays a grid on a screen based on the composition proposed by the photography plan proposal unit. A system characterized by:

2. The photography plan proposal unit Analyzes the user's past photo data and suggests angles, compositions, and poses based on the user's preferences and style 2. The system of claim 1.

3. The photography plan proposal unit Detects weather and light conditions in real time and suggests optimal shooting conditions accordingly 2. The system of claim 1.

4. The photography plan proposal unit Analyze the user's current emotional state and suggest angles, compositions, and poses that match that emotion 2. The system of claim 1.

5. The grid display unit The function allows the user to apply their preferred filters and effects in real time.

2. The system of claim 1.

6. The photography plan proposal unit Ability to customize angles, compositions, and poses based on different cultural or regional aesthetics 2. The system of claim 1.

7. The photography plan proposal unit Providing suggestions that have a relaxing effect to reduce stress and anxiety felt by the user during shooting 2. The system of claim 1.

8. The location information acquisition unit Analyze popular photos taken at the location in the past and propose the most effective photoshoot plan.

2. The system of claim 1.

Images