system

Abstract

The system according to this embodiment aims to reduce the effort required for taking photographs and to allow for easy selection of the best photograph. [Solution] The system according to the embodiment comprises a continuous shooting mode switching unit, a selection unit, an environment recognition unit, and a user interface unit. The continuous shooting mode switching unit automatically applies various shooting modes to take pictures. The selection unit analyzes the photos taken by the continuous shooting mode switching unit and suggests the best shot. The environment recognition unit determines the shooting environment and optimizes the settings. The user interface unit allows users to intuitively check and select the suggested photos.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a persona chatbot control method performed by at least one processor, including steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In the conventional technology, there are the trouble of selecting the best shot from many photos and the annoyance of manually adjusting various shooting modes, and there is room for improvement.

[0005] The system according to the embodiment aims to reduce the trouble of shooting and enable easy selection of the optimal photo.

Means for Solving the Problems

[0006] The system according to this embodiment comprises a continuous shooting mode switching unit, a selection unit, an environment recognition unit, and a user interface unit. The continuous shooting mode switching unit automatically applies various shooting modes to perform shooting. The selection unit analyzes the photos taken by the continuous shooting mode switching unit and suggests the best shot. The environment recognition unit determines the shooting environment and optimizes the settings. The user interface unit allows users to intuitively check and select the suggested photos. [Effects of the Invention]

[0007] The system according to this embodiment can reduce the effort required for taking photos and make it easy to select the best photo. [Brief explanation of the drawing]

[0008] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Modes for carrying out the invention]

[0009] Hereinafter, an example of an embodiment of the system relating to the technology of this disclosure will be described with reference to the attached drawings.

[0010] First, let's explain the terminology used in the following explanation.

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

[0012] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

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

[0014] In the following embodiments, the labeled communication I / F (Interface) is an interface including a communication processor, an antenna, and the like. The communication I / F controls communication between a plurality of 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), or Bluetooth (registered trademark).

[0015] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B". That is, "A and / or B" means that it may be only A, only B, or a combination of A and B. Also, in this specification, when expressing three or more matters connected by "and / or", the same concept as "A and / or B" is applied.

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

[0017] As shown in FIG. 1, the 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, the RAM 30, and the storage 32 are connected to a bus 34. Also, the database 24 and the communication I / F 26 are 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 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0020] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, and accepts user input. The touch panel 38A accepts user input via touch by detecting contact with an object (e.g., a pen or finger). The microphone 38B accepts user input via voice by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 (see Figure 2) acquires the data indicating the user input.

[0021] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user by outputting the data in a form perceptible to the user (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

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

[0024] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0025] Storage 32 stores the data generation model 58 and the 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 the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0026] In the smart device 14, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used in conjunction 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 a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart device 14 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0027] Furthermore, other devices besides the data processing device 12 may also 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 processing results (such as prediction results) using the data generation model 58 by communicating with the server device having the data generation model 58. The data processing device 12 may also be a server device or a terminal device owned by a user (e.g., a mobile phone, robot, home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example of form 1) The photographic system according to an embodiment of the present invention is a system that reduces the effort required for taking photographs by utilizing generation AI and automatically selects the optimal photograph. This photographic system is equipped with a continuous shooting mode switching function that automatically applies various shooting modes for shooting. For example, when photographing fast-moving subjects, sports mode is automatically applied, and when photographing still landscapes, landscape mode is applied. Next, the photographic system is equipped with an AI-based optimal photograph selection function. The AI ​​analyzes the photographs taken and suggests the best shot. For example, from among multiple photographs, it selects the one in which the subject's smile is most natural and the background is well-balanced. Furthermore, the photographic system is equipped with environmental recognition technology. The AI ​​determines the shooting environment and optimizes the settings. For example, it automatically uses the flash in dark places and applies HDR mode in backlit situations. In this way, the optimal settings according to the shooting environment are automatically made. Finally, the photographic system is equipped with a user interface. It provides an interface that allows users to intuitively check and select the suggested photographs. For example, by simply tapping the photograph displayed as a thumbnail on the smartphone screen, users can check the details. This system reduces the time spent choosing photographs and allows users to capture the best moments effortlessly. It also improves the enjoyment and convenience of photography, allowing users to enjoy photography more comfortably. This allows the photo-taking system to reduce the effort involved in taking photos and automatically select the best photo.

[0029] The photographic system according to this embodiment comprises a continuous shooting mode switching unit, a selection unit, an environment recognition unit, and a user interface unit. The continuous shooting mode switching unit automatically applies various shooting modes to take photographs. For example, the continuous shooting mode switching unit applies sports mode when photographing fast-moving subjects and landscape mode when photographing still landscapes. For example, by applying sports mode, the continuous shooting mode switching unit can take clear photographs of fast-moving subjects. For example, by applying landscape mode, the continuous shooting mode switching unit can take beautiful photographs of still landscapes. For example, by applying portrait mode, the continuous shooting mode switching unit can take beautiful photographs of people. The selection unit analyzes the photographs taken by the continuous shooting mode switching unit and suggests the best shot. For example, the selection unit selects the best photograph by considering factors such as face recognition, expression analysis, and compositional balance. For example, the selection unit uses face recognition technology to detect the subject's face and selects the photograph with the most natural expression. The selection unit, for example, uses facial expression analysis technology to analyze the subject's smile and emotions and selects the photo with the best expression. The selection unit, for example, considers compositional balance and selects a photo with a good balance between the subject and background. The environment recognition unit determines the shooting environment and optimizes the settings. For example, the environment recognition unit automatically uses the flash in dark places and applies HDR mode in backlit situations. For example, the environment recognition unit can brighten the subject by using the flash when shooting in dark places. For example, the environment recognition unit can take well-balanced photos even in scenes with large differences in brightness by applying HDR mode in backlit situations. For example, the environment recognition unit can take clear photos even at night by applying night shooting mode. The user interface unit provides an interface that allows users to intuitively check and select the suggested photos. For example, the user interface unit allows users to check details by simply tapping the photo displayed as a thumbnail on the smartphone screen. For example, the user interface unit can display detailed information about a photo by tapping the thumbnail displayed. The user interface allows users to switch between photos using a swipe gesture, for example.The user interface allows, for example, the selection of a photograph using voice commands. This reduces the effort required for taking photographs and enables the system to automatically select the optimal photograph.

[0030] The continuous shooting mode switch automatically applies various shooting modes during shooting. For example, it applies sports mode when shooting fast-moving subjects and landscape mode when shooting still landscapes. Specifically, in sports mode, the shutter speed is set to a high speed, and the continuous shooting function is used to capture moving subjects clearly. This makes it possible to capture moments without missing a beat, such as sporting events or the movements of animals. On the other hand, in landscape mode, the aperture is stopped down to increase the depth of field, allowing for clear shooting of wide landscapes. Furthermore, in portrait mode, the aperture is opened to blur the background and make the subject stand out, beautifully expressing the texture of the subject's skin and facial expressions. By automatically switching between these modes, the continuous shooting mode switch eliminates the need for the user to manually set the optimal settings for each shooting scene, ensuring that the best photos are always taken. In addition, the continuous shooting mode switch utilizes AI to analyze the subject's movement and environmental changes in real time and select the optimal mode. For example, the AI ​​detects the subject's movement and automatically switches between sports mode and normal mode depending on its speed and direction. This allows the user to concentrate on shooting, and the system automatically makes the optimal settings, improving the success rate of the shot.

[0031] The selection unit analyzes photos taken by the continuous shooting mode switching unit and suggests the best shot. The selection unit selects the best photo by considering factors such as face recognition, expression analysis, and compositional balance. Specifically, it uses face recognition technology to detect the subject's face and evaluates elements such as whether the eyes are open and whether the subject is smiling. Furthermore, it uses expression analysis technology to analyze the subject's emotions and selects the photo with the most natural and appealing expression. For example, it can prioritize selecting photos with smiles or emotional expressions. It also considers compositional balance, evaluating the positional relationship between the subject and background and the harmony of colors to select a visually beautiful photo. The selection unit comprehensively evaluates these elements and suggests the optimal photo for the user. In addition, the selection unit can use AI to learn past shooting data and user preferences and suggest the best shot tailored to each individual user. For example, it can analyze the trends of photos the user has previously selected and evaluate new photos based on those trends. This allows the selection unit to suggest photos that match the user's preferences and increase satisfaction.

[0032] The environmental recognition unit assesses the shooting environment and optimizes settings. For example, it automatically uses the flash in dark places and applies HDR mode in backlit situations. Specifically, by using the flash when shooting in dark places, the subject can be photographed brightly. The flash intensity and timing are also automatically adjusted to achieve natural brightness. Furthermore, by applying HDR mode in backlit situations, it is possible to take well-balanced photos even in scenes with large differences in brightness. In HDR mode, images taken with multiple exposures are combined to achieve a balance between the details of bright and dark areas. In addition, the environmental recognition unit can take clear photos even at night by applying night shooting mode. In night shooting mode, long exposure and high sensitivity settings are used to take clear photos with reduced noise even in dark environments. By automatically switching these functions, the environmental recognition unit eliminates the need for the user to manually adjust the optimal settings according to the shooting environment, allowing for consistently high-quality photos. The environmental recognition unit also utilizes AI to analyze the shooting environment in real time and select the optimal settings. For example, the AI ​​detects the intensity and color temperature of the surrounding light and automatically adjusts the white balance and exposure accordingly. This allows the user to concentrate on shooting, and the system automatically makes the optimal settings, improving the success rate of the shot.

[0033] The user interface provides an intuitive interface for viewing and selecting suggested photos. For example, users can view details simply by tapping a thumbnail displayed on their smartphone screen. Specifically, tapping a thumbnail displays detailed information about the photo. This information includes the date and time of shooting, shooting mode, exposure settings, etc., allowing users to select photos based on this information. Furthermore, users can easily compare multiple photos by swiping to switch between them. Additionally, photos can be selected using voice commands, making it easy to operate even when hands are full or visual operation is difficult. Through these functions, the user interface provides an intuitive interface, reducing the effort required for photo selection. The user interface also utilizes AI to learn the user's operation history and preferences, providing a personalized interface. For example, it learns frequently used functions and operations and customizes the interface accordingly. This improves user usability and provides a more comfortable photo selection experience.

[0034] The continuous shooting mode switch allows you to apply sports mode when shooting fast-moving subjects and landscape mode when shooting still landscapes. For example, the continuous shooting mode switch applies sports mode when shooting fast-moving subjects. For example, when shooting fast-moving subjects such as athletes or animals, sports mode can be applied. For example, when shooting still landscapes, landscape mode can be applied. For example, when shooting still landscapes such as mountains, lakes, or parks, landscape mode can be applied. For example, by applying portrait mode, you can take beautiful photos of people. This allows the camera to automatically apply the optimal shooting mode according to the subject's movement.

[0035] The selection unit can select the best photograph by considering factors such as face recognition, expression analysis, and compositional balance. For example, the selection unit can use face recognition technology to detect the subject's face and select the photograph with the most natural expression. For example, the selection unit can use a face detection algorithm to detect the subject's face with high accuracy. For example, the selection unit can use expression analysis technology to analyze the subject's smile and emotions and select the photograph with the best expression. For example, the selection unit can use methods for estimating the type of expression and emotion to analyze the subject's expression in detail. For example, the selection unit can consider compositional balance to select a photograph with a good balance between the subject and the background. For example, the selection unit can use the rule of thirds or the golden ratio to evaluate compositional balance. In this way, the best photograph can be selected by considering face recognition, expression analysis, and compositional balance.

[0036] The environmental recognition unit can automatically use the flash in dark places and apply HDR mode in backlit situations. For example, by using the flash when shooting in dark places, the environmental recognition unit can brighten the subject. For example, the environmental recognition unit can use the flash in dark places such as at night, indoors, or in places with many shadows. For example, by applying HDR mode in backlit situations, the environmental recognition unit can take well-balanced photos even in scenes with large differences in brightness. For example, the environmental recognition unit can apply HDR mode in backlit situations such as shooting with the sun behind you or when there is a strong light source behind you. For example, by applying night shooting mode, the environmental recognition unit can take clear photos even at night. This allows the camera to automatically make optimal settings according to the shooting environment.

[0037] The user interface allows users to view details of photos simply by tapping the thumbnails displayed on the smartphone screen. For example, tapping a thumbnail displays detailed information about a photo. The user interface allows users to adjust the size and order of the thumbnails. For example, increasing the display size makes it easier to view photo details. For example, changing the display order prioritizes important photos. For example, users can switch between photos using swipe gestures. For example, users can select photos using voice commands. This allows for intuitive viewing and selection of suggested photos.

[0038] The continuous shooting mode switching unit can analyze the subject's movement pattern in real time and select the optimal shooting mode. For example, if the subject suddenly starts moving, the continuous shooting mode switching unit will switch to sports mode and take the picture. For example, if the subject is stationary, the continuous shooting mode switching unit will switch to landscape mode and take the picture. For example, if the subject is moving slowly, the continuous shooting mode switching unit will switch to portrait mode and take the picture. This allows the optimal shooting mode to be selected according to the subject's movement pattern. Some or all of the above processing in the continuous shooting mode switching unit may be performed using AI, for example, or without AI. For example, the continuous shooting mode switching unit can input the subject's movement pattern into a generating AI and have the generating AI select the optimal shooting mode.

[0039] The continuous shooting mode switching unit can detect changes in the shooting scene and automatically apply the appropriate shooting mode. For example, if the camera moves from indoors to outdoors, the continuous shooting mode switching unit will switch to landscape mode and start shooting. For example, if the camera moves from a bright place to a dark place, the continuous shooting mode switching unit will switch to night mode and start shooting. For example, if the camera enters a backlit scene, the continuous shooting mode switching unit will switch to HDR mode and start shooting. This allows the camera to automatically apply the optimal shooting mode according to changes in the shooting scene. Some or all of the above processing in the continuous shooting mode switching unit may be performed using AI, for example, or without AI. For example, the continuous shooting mode switching unit can input changes in the shooting scene to a generating AI and cause the generating AI to apply the appropriate shooting mode according to the scene.

[0040] The continuous shooting mode switching unit can recognize the attributes of the subject and apply the appropriate shooting mode. For example, if the continuous shooting mode switching unit recognizes a person, it will apply portrait mode. For example, if the continuous shooting mode switching unit recognizes an animal, it will apply animal mode. For example, if the continuous shooting mode switching unit recognizes a landscape, it will apply landscape mode. This allows the optimal shooting mode to be applied according to the attributes of the subject. Some or all of the above processing in the continuous shooting mode switching unit may be performed using AI, for example, or without AI. For example, the continuous shooting mode switching unit can input the attributes of the subject into a generating AI and cause the generating AI to apply the optimal shooting mode.

[0041] The continuous shooting mode switching unit can acquire weather information during shooting and apply a shooting mode appropriate to the weather. For example, the continuous shooting mode switching unit can apply landscape mode in sunny weather. For example, the continuous shooting mode switching unit can apply night mode in rainy weather. For example, the continuous shooting mode switching unit can apply snow mode on snowy days. This allows the optimal shooting mode to be applied according to the weather information. Some or all of the above processing in the continuous shooting mode switching unit may be performed using AI, for example, or without AI. For example, the continuous shooting mode switching unit can input weather information into a generating AI and cause the generating AI to execute the application of the optimal shooting mode.

[0042] The selection unit can analyze the subject's movements and facial expressions from the captured photographs and select the most natural moment. For example, the selection unit can select the moment when the subject is smiling. For example, the selection unit can select the moment when the subject is in the most natural pose during movement. For example, the selection unit can select the moment when the subject's expression is most relaxed. In this way, the selection unit can analyze the subject's movements and facial expressions and select the most natural moment. Some or all of the above processing in the selection unit may be performed using AI, for example, or without AI. For example, the selection unit can input the subject's movements and facial expressions into a generating AI and have the generating AI perform the selection of the most natural moment.

[0043] The selection unit can select photos from the captured images, taking into consideration the beauty of the background and the balance of colors. For example, the selection unit may select photos with vibrant background colors. For example, the selection unit may select photos with a beautiful background composition. For example, the selection unit may select photos with a good balance between the background and the subject. This allows the selection of the best photo to be made, taking into consideration the beauty of the background and the balance of colors. Some or all of the above processing in the selection unit may be performed using AI, for example, or without AI. For example, the selection unit can input the beauty of the background and the balance of colors into a generating AI and have the generating AI select the best photo.

[0044] The selection unit can select photos from the captured images, taking into account the colors of the subject's clothing and accessories. For example, the selection unit may select a photo where the colors of the subject's clothing harmonize with the background. For example, the selection unit may select a photo where the subject's accessories stand out. For example, the selection unit may select a photo where the design of the subject's clothing is most prominent. In this way, the best photo can be selected, taking into account the colors of the subject's clothing and accessories. Some or all of the above processing in the selection unit may be performed using AI, for example, or without AI. For example, the selection unit can input the colors of the subject's clothing and accessories into a generating AI and have the generating AI select the best photo.

[0045] The selection unit can select the best photograph from the captured images, taking into account variations in the subject's position and pose. For example, the selection unit might select a photograph where the subject is centered. For example, the selection unit might select a photograph where the subject is in a natural pose. For example, the selection unit might select a photograph where the subject's position harmonizes with the background. This allows the unit to select the best photograph by considering variations in the subject's position and pose. Some or all of the above processing in the selection unit may be performed using AI, for example, or without AI. For example, the selection unit can input variations in the subject's position and pose into a generating AI and have the generating AI select the best photograph.

[0046] The environmental recognition unit can analyze the intensity and direction of light in the shooting environment in real time and apply the optimal settings. For example, if the light intensity is strong, the environmental recognition unit adjusts the exposure. For example, if the light direction is backlighting, the environmental recognition unit applies HDR mode. For example, if the light intensity is weak, the environmental recognition unit uses the flash. This allows the optimal settings to be applied according to the intensity and direction of light in the shooting environment. Some or all of the above processing in the environmental recognition unit may be performed using AI, for example, or without AI. For example, the environmental recognition unit can input the light intensity and direction to a generating AI and cause the generating AI to execute the application of the optimal settings.

[0047] The environmental recognition unit can detect the effects of sound and wind in the shooting environment and apply settings accordingly. For example, if the wind is strong, the environmental recognition unit can apply settings to reduce wind noise. For example, if the ambient noise is loud, the environmental recognition unit can apply noise reduction. For example, in a quiet environment, the environmental recognition unit can apply settings to record audio clearly. This allows the system to apply optimal settings according to the effects of sound and wind in the shooting environment. Some or all of the above processing in the environmental recognition unit may be performed using AI, for example, or without AI. For example, the environmental recognition unit can input the effects of sound and wind to a generating AI and have the generating AI apply the optimal settings.

[0048] The environmental recognition unit can detect the temperature and humidity of the shooting environment and apply settings accordingly. For example, in a high-temperature environment, the environmental recognition unit can apply the camera's temperature control settings. In a low-temperature environment, the environmental recognition unit can apply settings to reduce battery consumption. In a high-humidity environment, the environmental recognition unit can apply settings to prevent lens fogging. This allows the optimal settings to be applied according to the temperature and humidity of the shooting environment. Some or all of the above processing in the environmental recognition unit may be performed using AI, for example, or without AI. For example, the environmental recognition unit can input temperature and humidity to a generating AI and have the generating AI execute the application of the optimal settings.

[0049] The environmental recognition unit can recognize the background color and pattern of the shooting environment and apply settings accordingly. For example, if the background is bright, the environmental recognition unit adjusts the exposure. For example, if the background is dark, the environmental recognition unit uses the flash. For example, if the background pattern is complex, the environmental recognition unit adjusts the focus. This allows the optimal settings to be applied according to the background color and pattern of the shooting environment. Some or all of the above processing in the environmental recognition unit may be performed using AI, for example, or without AI. For example, the environmental recognition unit can input the background color and pattern to a generating AI and cause the generating AI to apply the optimal settings.

[0050] The user interface unit can select the optimal display method by referring to the user's past operation history when displaying the interface. For example, the user interface unit prioritizes providing display methods that the user has used in the past. For example, the user interface unit suggests the most frequently used display method from the user's past operation history. For example, the user interface unit analyzes the user's past operation history and automatically selects the optimal display method. This allows the optimal display method to be selected based on the user's past operation history. Some or all of the above processing in the user interface unit may be performed using AI, for example, or without AI. For example, the user interface unit can input past operation history into a generating AI and have the generating AI perform the selection of the optimal display method.

[0051] The user interface unit can track the user's eye movements when displaying the interface and enable operations that correspond to the user's gaze. For example, if the user interface unit directs its gaze to a specific photograph, it will enlarge that photograph. For example, if the user interface unit moves its gaze, it will switch to the next photograph. For example, if the user interface unit fixates its gaze on a photograph, it will display detailed information about that photograph. This makes it possible to operate the interface according to the user's eye movements. Some or all of the above-described processes in the user interface unit may be performed using AI, for example, or without AI. For example, the user interface unit can input eye movements into a generating AI and have the generating AI execute operations that correspond to the gaze.

[0052] The user interface unit can select the optimal display method when displaying the interface, taking into account the user's device information. For example, if the user is using a smartphone, the user interface unit provides a display method that matches the screen size. For example, if the user is using a tablet, the user interface unit provides a display method optimized for a large screen. For example, if the user is using a smartwatch, the user interface unit provides a concise and highly visible display method. This allows the optimal display method to be selected based on the user's device information. Some or all of the above processing in the user interface unit may be performed using AI, for example, or without AI. For example, the user interface unit can input device information into a generating AI and have the generating AI select the optimal display method.

[0053] The user interface unit can recognize user voice commands when displaying the interface and enable voice operation. For example, if the user gives a voice command to select a photo, the user interface unit will display that photo. For example, if the user gives a voice command to switch to the next photo, the user interface unit will display the next photo. For example, if the user gives a voice command to display detailed information about a photo, the user interface unit will display that information. This makes it possible to operate the interface in response to user voice commands. Some or all of the above processing in the user interface unit may be performed using AI, for example, or without AI. For example, the user interface unit can input voice commands into a generating AI and have the generating AI execute voice operations.

[0054] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0055] The photography system can also be equipped with a function to predict the movement of the subject. It predicts the subject's movement and automatically determines the optimal shutter opportunity. For example, by predicting the moment an athlete jumps at a sporting event and pressing the shutter at that moment, a more dynamic photograph can be taken. It can also predict the movement of animals and capture the moment when the animal assumes the most beautiful posture. Furthermore, it can predict the moment a child smiles while playing and capture that moment without missing it. In this way, it can predict the movement of the subject and capture the optimal shutter opportunity.

[0056] The photo-taking system can also be equipped with voice recognition capabilities. It can switch shooting modes in response to user voice commands. For example, if the user says "sports mode," the system will automatically switch to sports mode. Similarly, if they say "landscape mode," it will switch to landscape mode. Furthermore, if they say "portrait mode," it will switch to portrait mode. This allows users to easily switch shooting modes using voice commands.

[0057] The photo-taking system further enhances its facial recognition capabilities, enabling it to estimate the subject's age and gender. For example, if it recognizes a child's face, it applies a bright color filter suitable for children. If it recognizes an adult's face, it applies a natural color filter. Furthermore, if it recognizes an elderly person's face, it applies a soft color filter. This allows the system to apply the optimal filter according to the subject's age and gender.

[0058] The photo-taking system can also acquire weather information and automatically apply the appropriate shooting mode based on the weather. For example, it can apply landscape mode on sunny days and night mode on rainy days. It can also apply snow mode on snowy days and HDR mode on cloudy days. This allows the system to automatically apply the optimal shooting mode based on the weather information.

[0059] The photo shooting system can further analyze the user's past shooting history and suggest shooting modes tailored to the user's preferences. For example, if the user has taken many sports photos in the past, the system will prioritize suggesting the sports mode. Similarly, if the user has taken many landscape photos, the system will prioritize suggesting the landscape mode. Furthermore, if the user has taken many portrait photos, the system will prioritize suggesting the portrait mode. This allows the system to suggest the optimal shooting mode based on the user's past shooting history.

[0060] The following briefly describes the processing flow for example form 1.

[0061] Step 1: The continuous shooting mode switching section automatically applies various shooting modes when taking pictures. For example, when shooting fast-moving subjects, the sports mode is applied, and when shooting still landscapes, the landscape mode is applied. This allows for optimal shooting according to the characteristics of the subject. Step 2: The selection unit analyzes the photos taken by the continuous shooting mode switching unit and suggests the best shot. For example, it selects the best photo by considering factors such as face recognition, expression analysis, and compositional balance. This makes it easy for the user to choose the optimal photo. Step 3: The environmental recognition unit determines the shooting environment and optimizes the settings. For example, it automatically uses the flash in dark places and applies HDR mode in backlit situations. This makes it possible to shoot with optimal settings in a variety of shooting environments. Step 4: The user interface provides an intuitive interface for viewing and selecting suggested photos. For example, users can view details simply by tapping a photo displayed as a thumbnail on their smartphone screen. This allows users to easily select and review photos.

[0062] (Example of form 2) The photographic system according to an embodiment of the present invention is a system that reduces the effort required for taking photographs by utilizing generation AI and automatically selects the optimal photograph. This photographic system is equipped with a continuous shooting mode switching function that automatically applies various shooting modes for shooting. For example, when photographing fast-moving subjects, sports mode is automatically applied, and when photographing still landscapes, landscape mode is applied. Next, the photographic system is equipped with an AI-based optimal photograph selection function. The AI ​​analyzes the photographs taken and suggests the best shot. For example, from among multiple photographs, it selects the one in which the subject's smile is most natural and the background is well-balanced. Furthermore, the photographic system is equipped with environmental recognition technology. The AI ​​determines the shooting environment and optimizes the settings. For example, it automatically uses the flash in dark places and applies HDR mode in backlit situations. In this way, the optimal settings according to the shooting environment are automatically made. Finally, the photographic system is equipped with a user interface. It provides an interface that allows users to intuitively check and select the suggested photographs. For example, by simply tapping the photograph displayed as a thumbnail on the smartphone screen, users can check the details. This system reduces the time spent choosing photographs and allows users to capture the best moments effortlessly. It also improves the enjoyment and convenience of photography, allowing users to enjoy photography more comfortably. This allows the photo-taking system to reduce the effort involved in taking photos and automatically select the best photo.

[0063] The photographic system according to this embodiment comprises a continuous shooting mode switching unit, a selection unit, an environment recognition unit, and a user interface unit. The continuous shooting mode switching unit automatically applies various shooting modes to take photographs. For example, the continuous shooting mode switching unit applies sports mode when photographing fast-moving subjects and landscape mode when photographing still landscapes. For example, by applying sports mode, the continuous shooting mode switching unit can take clear photographs of fast-moving subjects. For example, by applying landscape mode, the continuous shooting mode switching unit can take beautiful photographs of still landscapes. For example, by applying portrait mode, the continuous shooting mode switching unit can take beautiful photographs of people. The selection unit analyzes the photographs taken by the continuous shooting mode switching unit and suggests the best shot. For example, the selection unit selects the best photograph by considering factors such as face recognition, expression analysis, and compositional balance. For example, the selection unit uses face recognition technology to detect the subject's face and selects the photograph with the most natural expression. The selection unit, for example, uses facial expression analysis technology to analyze the subject's smile and emotions and selects the photo with the best expression. The selection unit, for example, considers compositional balance and selects a photo with a good balance between the subject and background. The environment recognition unit determines the shooting environment and optimizes the settings. For example, the environment recognition unit automatically uses the flash in dark places and applies HDR mode in backlit situations. For example, the environment recognition unit can brighten the subject by using the flash when shooting in dark places. For example, the environment recognition unit can take well-balanced photos even in scenes with large differences in brightness by applying HDR mode in backlit situations. For example, the environment recognition unit can take clear photos even at night by applying night shooting mode. The user interface unit provides an interface that allows users to intuitively check and select the suggested photos. For example, the user interface unit allows users to check details by simply tapping the photo displayed as a thumbnail on the smartphone screen. For example, the user interface unit can display detailed information about a photo by tapping the thumbnail displayed. The user interface allows users to switch between photos using a swipe gesture, for example.The user interface allows, for example, the selection of a photograph using voice commands. This reduces the effort required for taking photographs and enables the system to automatically select the optimal photograph.

[0064] The continuous shooting mode switch automatically applies various shooting modes during shooting. For example, it applies sports mode when shooting fast-moving subjects and landscape mode when shooting still landscapes. Specifically, in sports mode, the shutter speed is set to a high speed, and the continuous shooting function is used to capture moving subjects clearly. This makes it possible to capture moments without missing a beat, such as sporting events or the movements of animals. On the other hand, in landscape mode, the aperture is stopped down to increase the depth of field, allowing for clear shooting of wide landscapes. Furthermore, in portrait mode, the aperture is opened to blur the background and make the subject stand out, beautifully expressing the texture of the subject's skin and facial expressions. By automatically switching between these modes, the continuous shooting mode switch eliminates the need for the user to manually set the optimal settings for each shooting scene, ensuring that the best photos are always taken. In addition, the continuous shooting mode switch utilizes AI to analyze the subject's movement and environmental changes in real time and select the optimal mode. For example, the AI ​​detects the subject's movement and automatically switches between sports mode and normal mode depending on its speed and direction. This allows the user to concentrate on shooting, and the system automatically makes the optimal settings, improving the success rate of the shot.

[0065] The selection unit analyzes photos taken by the continuous shooting mode switching unit and suggests the best shot. The selection unit selects the best photo by considering factors such as face recognition, expression analysis, and compositional balance. Specifically, it uses face recognition technology to detect the subject's face and evaluates elements such as whether the eyes are open and whether the subject is smiling. Furthermore, it uses expression analysis technology to analyze the subject's emotions and selects the photo with the most natural and appealing expression. For example, it can prioritize selecting photos with smiles or emotional expressions. It also considers compositional balance, evaluating the positional relationship between the subject and background and the harmony of colors to select a visually beautiful photo. The selection unit comprehensively evaluates these elements and suggests the optimal photo for the user. In addition, the selection unit can use AI to learn past shooting data and user preferences and suggest the best shot tailored to each individual user. For example, it can analyze the trends of photos the user has previously selected and evaluate new photos based on those trends. This allows the selection unit to suggest photos that match the user's preferences and increase satisfaction.

[0066] The environmental recognition unit assesses the shooting environment and optimizes settings. For example, it automatically uses the flash in dark places and applies HDR mode in backlit situations. Specifically, by using the flash when shooting in dark places, the subject can be photographed brightly. The flash intensity and timing are also automatically adjusted to achieve natural brightness. Furthermore, by applying HDR mode in backlit situations, it is possible to take well-balanced photos even in scenes with large differences in brightness. In HDR mode, images taken with multiple exposures are combined to achieve a balance between the details of bright and dark areas. In addition, the environmental recognition unit can take clear photos even at night by applying night shooting mode. In night shooting mode, long exposure and high sensitivity settings are used to take clear photos with reduced noise even in dark environments. By automatically switching these functions, the environmental recognition unit eliminates the need for the user to manually adjust the optimal settings according to the shooting environment, allowing for consistently high-quality photos. The environmental recognition unit also utilizes AI to analyze the shooting environment in real time and select the optimal settings. For example, the AI ​​detects the intensity and color temperature of the surrounding light and automatically adjusts the white balance and exposure accordingly. This allows the user to concentrate on shooting, and the system automatically makes the optimal settings, improving the success rate of the shot.

[0067] The user interface provides an intuitive interface for viewing and selecting suggested photos. For example, users can view details simply by tapping a thumbnail displayed on their smartphone screen. Specifically, tapping a thumbnail displays detailed information about the photo. This information includes the date and time of shooting, shooting mode, exposure settings, etc., allowing users to select photos based on this information. Furthermore, users can easily compare multiple photos by swiping to switch between them. Additionally, photos can be selected using voice commands, making it easy to operate even when hands are full or visual operation is difficult. Through these functions, the user interface provides an intuitive interface, reducing the effort required for photo selection. The user interface also utilizes AI to learn the user's operation history and preferences, providing a personalized interface. For example, it learns frequently used functions and operations and customizes the interface accordingly. This improves user usability and provides a more comfortable photo selection experience.

[0068] The continuous shooting mode switch allows you to apply sports mode when shooting fast-moving subjects and landscape mode when shooting still landscapes. For example, the continuous shooting mode switch applies sports mode when shooting fast-moving subjects. For example, when shooting fast-moving subjects such as athletes or animals, sports mode can be applied. For example, when shooting still landscapes, landscape mode can be applied. For example, when shooting still landscapes such as mountains, lakes, or parks, landscape mode can be applied. For example, by applying portrait mode, you can take beautiful photos of people. This allows the camera to automatically apply the optimal shooting mode according to the subject's movement.

[0069] The selection unit can select the best photograph by considering factors such as face recognition, expression analysis, and compositional balance. For example, the selection unit can use face recognition technology to detect the subject's face and select the photograph with the most natural expression. For example, the selection unit can use a face detection algorithm to detect the subject's face with high accuracy. For example, the selection unit can use expression analysis technology to analyze the subject's smile and emotions and select the photograph with the best expression. For example, the selection unit can use methods for estimating the type of expression and emotion to analyze the subject's expression in detail. For example, the selection unit can consider compositional balance to select a photograph with a good balance between the subject and the background. For example, the selection unit can use the rule of thirds or the golden ratio to evaluate compositional balance. In this way, the best photograph can be selected by considering face recognition, expression analysis, and compositional balance.

[0070] The environmental recognition unit can automatically use the flash in dark places and apply HDR mode in backlit situations. For example, by using the flash when shooting in dark places, the environmental recognition unit can brighten the subject. For example, the environmental recognition unit can use the flash in dark places such as at night, indoors, or in places with many shadows. For example, by applying HDR mode in backlit situations, the environmental recognition unit can take well-balanced photos even in scenes with large differences in brightness. For example, the environmental recognition unit can apply HDR mode in backlit situations such as shooting with the sun behind you or when there is a strong light source behind you. For example, by applying night shooting mode, the environmental recognition unit can take clear photos even at night. This allows the camera to automatically make optimal settings according to the shooting environment.

[0071] The user interface allows users to view details of photos simply by tapping the thumbnails displayed on the smartphone screen. For example, tapping a thumbnail displays detailed information about a photo. The user interface allows users to adjust the size and order of the thumbnails. For example, increasing the display size makes it easier to view photo details. For example, changing the display order prioritizes important photos. For example, users can switch between photos using swipe gestures. For example, users can select photos using voice commands. This allows for intuitive viewing and selection of suggested photos.

[0072] The continuous shooting mode switching unit can estimate the user's emotions and adjust the timing of the continuous shooting mode switch based on the estimated emotions. For example, if the user is excited, the continuous shooting mode switch will be faster to take more photos. For example, if the user is relaxed, the continuous shooting mode switch will be slower to take photos at a relaxed pace. For example, if the user is focused, the continuous shooting mode switch will be optimized to ensure that important moments are not missed. This allows the timing of the continuous shooting mode switch to be adjusted according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0073] The continuous shooting mode switching unit can analyze the subject's movement pattern in real time and select the optimal shooting mode. For example, if the subject suddenly starts moving, the continuous shooting mode switching unit will switch to sports mode and take the picture. For example, if the subject is stationary, the continuous shooting mode switching unit will switch to landscape mode and take the picture. For example, if the subject is moving slowly, the continuous shooting mode switching unit will switch to portrait mode and take the picture. This allows the optimal shooting mode to be selected according to the subject's movement pattern. Some or all of the above processing in the continuous shooting mode switching unit may be performed using AI, for example, or without AI. For example, the continuous shooting mode switching unit can input the subject's movement pattern into a generating AI and have the generating AI select the optimal shooting mode.

[0074] The continuous shooting mode switching unit can detect changes in the shooting scene and automatically apply the appropriate shooting mode. For example, if the camera moves from indoors to outdoors, the continuous shooting mode switching unit will switch to landscape mode and start shooting. For example, if the camera moves from a bright place to a dark place, the continuous shooting mode switching unit will switch to night mode and start shooting. For example, if the camera enters a backlit scene, the continuous shooting mode switching unit will switch to HDR mode and start shooting. This allows the camera to automatically apply the optimal shooting mode according to changes in the shooting scene. Some or all of the above processing in the continuous shooting mode switching unit may be performed using AI, for example, or without AI. For example, the continuous shooting mode switching unit can input changes in the shooting scene to a generating AI and cause the generating AI to apply the appropriate shooting mode according to the scene.

[0075] The continuous shooting mode switching unit can estimate the user's emotions and determine the priority of shooting modes based on the estimated emotions. For example, if the user is excited, the continuous shooting mode switching unit will prioritize applying sports mode. For example, if the user is relaxed, the continuous shooting mode switching unit will prioritize applying landscape mode. For example, if the user is focused, the continuous shooting mode switching unit will prioritize applying portrait mode. This allows the priority of shooting modes to be determined according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0076] The continuous shooting mode switching unit can recognize the attributes of the subject and apply the appropriate shooting mode. For example, if the continuous shooting mode switching unit recognizes a person, it will apply portrait mode. For example, if the continuous shooting mode switching unit recognizes an animal, it will apply animal mode. For example, if the continuous shooting mode switching unit recognizes a landscape, it will apply landscape mode. This allows the optimal shooting mode to be applied according to the attributes of the subject. Some or all of the above processing in the continuous shooting mode switching unit may be performed using AI, for example, or without AI. For example, the continuous shooting mode switching unit can input the attributes of the subject into a generating AI and cause the generating AI to apply the optimal shooting mode.

[0077] The continuous shooting mode switching unit can acquire weather information during shooting and apply a shooting mode appropriate to the weather. For example, the continuous shooting mode switching unit can apply landscape mode in sunny weather. For example, the continuous shooting mode switching unit can apply night mode in rainy weather. For example, the continuous shooting mode switching unit can apply snow mode on snowy days. This allows the optimal shooting mode to be applied according to the weather information. Some or all of the above processing in the continuous shooting mode switching unit may be performed using AI, for example, or without AI. For example, the continuous shooting mode switching unit can input weather information into a generating AI and cause the generating AI to execute the application of the optimal shooting mode.

[0078] The selection unit can estimate the user's emotions and adjust the selection criteria for the best shot based on the estimated emotions. For example, if the user is excited, the selection unit will prioritize selecting photos with movement. For example, if the user is relaxed, the selection unit will prioritize selecting photos with a calm atmosphere. For example, if the user is focused, the selection unit will prioritize selecting photos with a good balance of composition. In this way, the selection criteria for the best shot can be adjusted according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0079] The selection unit can analyze the subject's movements and facial expressions from the captured photographs and select the most natural moment. For example, the selection unit can select the moment when the subject is smiling. For example, the selection unit can select the moment when the subject is in the most natural pose during movement. For example, the selection unit can select the moment when the subject's expression is most relaxed. In this way, the selection unit can analyze the subject's movements and facial expressions and select the most natural moment. Some or all of the above processing in the selection unit may be performed using AI, for example, or without AI. For example, the selection unit can input the subject's movements and facial expressions into a generating AI and have the generating AI perform the selection of the most natural moment.

[0080] The selection unit can select photos from the captured images, taking into consideration the beauty of the background and the balance of colors. For example, the selection unit may select photos with vibrant background colors. For example, the selection unit may select photos with a beautiful background composition. For example, the selection unit may select photos with a good balance between the background and the subject. This allows the selection of the best photo to be made, taking into consideration the beauty of the background and the balance of colors. Some or all of the above processing in the selection unit may be performed using AI, for example, or without AI. For example, the selection unit can input the beauty of the background and the balance of colors into a generating AI and have the generating AI select the best photo.

[0081] The selection unit can estimate the user's emotions and adjust the display order of selected photos based on the estimated emotions. For example, if the user is excited, the selection unit will display dynamic photos first. If the user is relaxed, the selection unit will display photos with a calm atmosphere first. If the user is focused, the selection unit will display photos with a good compositional balance first. In this way, the display order of selected photos can be adjusted according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0082] The selection unit can select photos from the captured images, taking into account the colors of the subject's clothing and accessories. For example, the selection unit may select a photo where the colors of the subject's clothing harmonize with the background. For example, the selection unit may select a photo where the subject's accessories stand out. For example, the selection unit may select a photo where the design of the subject's clothing is most prominent. In this way, the best photo can be selected, taking into account the colors of the subject's clothing and accessories. Some or all of the above processing in the selection unit may be performed using AI, for example, or without AI. For example, the selection unit can input the colors of the subject's clothing and accessories into a generating AI and have the generating AI select the best photo.

[0083] The selection unit can select the best photograph from the captured images, taking into account variations in the subject's position and pose. For example, the selection unit might select a photograph where the subject is centered. For example, the selection unit might select a photograph where the subject is in a natural pose. For example, the selection unit might select a photograph where the subject's position harmonizes with the background. This allows the unit to select the best photograph by considering variations in the subject's position and pose. Some or all of the above processing in the selection unit may be performed using AI, for example, or without AI. For example, the selection unit can input variations in the subject's position and pose into a generating AI and have the generating AI select the best photograph.

[0084] The environmental recognition unit can estimate the user's emotions and adjust the shooting environment settings based on the estimated emotions. For example, if the user is excited, the environmental recognition unit applies a bright setting. For example, if the user is relaxed, the environmental recognition unit applies a soft light setting. For example, if the user is focused, the environmental recognition unit applies a natural light setting. This allows the shooting environment settings to be adjusted according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0085] The environmental recognition unit can analyze the intensity and direction of light in the shooting environment in real time and apply the optimal settings. For example, if the light intensity is strong, the environmental recognition unit adjusts the exposure. For example, if the light direction is backlighting, the environmental recognition unit applies HDR mode. For example, if the light intensity is weak, the environmental recognition unit uses the flash. This allows the optimal settings to be applied according to the intensity and direction of light in the shooting environment. Some or all of the above processing in the environmental recognition unit may be performed using AI, for example, or without AI. For example, the environmental recognition unit can input the light intensity and direction to a generating AI and cause the generating AI to execute the application of the optimal settings.

[0086] The environmental recognition unit can detect the effects of sound and wind in the shooting environment and apply settings accordingly. For example, if the wind is strong, the environmental recognition unit can apply settings to reduce wind noise. For example, if the ambient noise is loud, the environmental recognition unit can apply noise reduction. For example, in a quiet environment, the environmental recognition unit can apply settings to record audio clearly. This allows the system to apply optimal settings according to the effects of sound and wind in the shooting environment. Some or all of the above processing in the environmental recognition unit may be performed using AI, for example, or without AI. For example, the environmental recognition unit can input the effects of sound and wind to a generating AI and have the generating AI apply the optimal settings.

[0087] The environmental recognition unit can estimate the user's emotions and prioritize adjusting the shooting environment settings based on the estimated emotions. For example, if the user is excited, the environmental recognition unit will prioritize applying bright settings. For example, if the user is relaxed, the environmental recognition unit will prioritize applying soft lighting settings. For example, if the user is concentrating, the environmental recognition unit will prioritize applying natural lighting settings. This allows the shooting environment settings to be prioritized according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0088] The environmental recognition unit can detect the temperature and humidity of the shooting environment and apply settings accordingly. For example, in a high-temperature environment, the environmental recognition unit can apply the camera's temperature control settings. In a low-temperature environment, the environmental recognition unit can apply settings to reduce battery consumption. In a high-humidity environment, the environmental recognition unit can apply settings to prevent lens fogging. This allows the optimal settings to be applied according to the temperature and humidity of the shooting environment. Some or all of the above processing in the environmental recognition unit may be performed using AI, for example, or without AI. For example, the environmental recognition unit can input temperature and humidity to a generating AI and have the generating AI execute the application of the optimal settings.

[0089] The environmental recognition unit can recognize the background color and pattern of the shooting environment and apply settings accordingly. For example, if the background is bright, the environmental recognition unit adjusts the exposure. For example, if the background is dark, the environmental recognition unit uses the flash. For example, if the background pattern is complex, the environmental recognition unit adjusts the focus. This allows the optimal settings to be applied according to the background color and pattern of the shooting environment. Some or all of the above processing in the environmental recognition unit may be performed using AI, for example, or without AI. For example, the environmental recognition unit can input the background color and pattern to a generating AI and cause the generating AI to apply the optimal settings.

[0090] The user interface unit can estimate the user's emotions and adjust the interface display method based on the estimated user emotions. For example, if the user is excited, the user interface unit provides an interface with bright colors. For example, if the user is relaxed, the user interface unit provides an interface with calm colors. For example, if the user is focused, the user interface unit provides a simple and highly visible interface. This allows the interface display method to be adjusted according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0091] The user interface unit can select the optimal display method by referring to the user's past operation history when displaying the interface. For example, the user interface unit prioritizes providing display methods that the user has used in the past. For example, the user interface unit suggests the most frequently used display method from the user's past operation history. For example, the user interface unit analyzes the user's past operation history and automatically selects the optimal display method. This allows the optimal display method to be selected based on the user's past operation history. Some or all of the above processing in the user interface unit may be performed using AI, for example, or without AI. For example, the user interface unit can input past operation history into a generating AI and have the generating AI perform the selection of the optimal display method.

[0092] The user interface unit can track the user's eye movements when displaying the interface and enable operations that correspond to the user's gaze. For example, if the user interface unit directs its gaze to a specific photograph, it will enlarge that photograph. For example, if the user interface unit moves its gaze, it will switch to the next photograph. For example, if the user interface unit fixates its gaze on a photograph, it will display detailed information about that photograph. This makes it possible to operate the interface according to the user's eye movements. Some or all of the above-described processes in the user interface unit may be performed using AI, for example, or without AI. For example, the user interface unit can input eye movements into a generating AI and have the generating AI execute operations that correspond to the gaze.

[0093] The user interface unit can estimate the user's emotions and adjust the interface's operation procedures based on the estimated emotions. For example, if the user is excited, the user interface unit provides simple operation procedures. For example, if the user is relaxed, the user interface unit provides detailed operation procedures. For example, if the user is focused, the user interface unit provides efficient operation procedures. This allows the interface's operation procedures to be adjusted according to the user's emotions. Emotion estimation is achieved using an emotion estimation function, for example, using an emotion engine or generative AI. Generative AI is, but is not limited to, text generation AI (e.g., LLM) or multimodal generation AI.

[0094] The user interface unit can select the optimal display method when displaying the interface, taking into account the user's device information. For example, if the user is using a smartphone, the user interface unit provides a display method that matches the screen size. For example, if the user is using a tablet, the user interface unit provides a display method optimized for a large screen. For example, if the user is using a smartwatch, the user interface unit provides a concise and highly visible display method. This allows the optimal display method to be selected based on the user's device information. Some or all of the above processing in the user interface unit may be performed using AI, for example, or without AI. For example, the user interface unit can input device information into a generating AI and have the generating AI select the optimal display method.

[0095] The user interface unit can recognize user voice commands when displaying the interface and enable voice operation. For example, if the user gives a voice command to select a photo, the user interface unit will display that photo. For example, if the user gives a voice command to switch to the next photo, the user interface unit will display the next photo. For example, if the user gives a voice command to display detailed information about a photo, the user interface unit will display that information. This makes it possible to operate the interface in response to user voice commands. Some or all of the above processing in the user interface unit may be performed using AI, for example, or without AI. For example, the user interface unit can input voice commands into a generating AI and have the generating AI execute voice operations.

[0096] The system according to the embodiment is not limited to the example described above, and various modifications are possible, for example, as follows.

[0097] The photography system can also be equipped with a function to predict the movement of the subject. It predicts the subject's movement and automatically determines the optimal shutter opportunity. For example, by predicting the moment an athlete jumps at a sporting event and pressing the shutter at that moment, a more dynamic photograph can be taken. It can also predict the movement of animals and capture the moment when the animal assumes the most beautiful posture. Furthermore, it can predict the moment a child smiles while playing and capture that moment without missing it. In this way, it can predict the movement of the subject and capture the optimal shutter opportunity.

[0098] The photo-taking system can also be equipped with voice recognition capabilities. It can switch shooting modes in response to user voice commands. For example, if the user says "sports mode," the system will automatically switch to sports mode. Similarly, if they say "landscape mode," it will switch to landscape mode. Furthermore, if they say "portrait mode," it will switch to portrait mode. This allows users to easily switch shooting modes using voice commands.

[0099] The photo-taking system further enhances its facial recognition capabilities, enabling it to estimate the subject's age and gender. For example, if it recognizes a child's face, it applies a bright color filter suitable for children. If it recognizes an adult's face, it applies a natural color filter. Furthermore, if it recognizes an elderly person's face, it applies a soft color filter. This allows the system to apply the optimal filter according to the subject's age and gender.

[0100] The photo-taking system can also acquire weather information and automatically apply the appropriate shooting mode based on the weather. For example, it can apply landscape mode on sunny days and night mode on rainy days. It can also apply snow mode on snowy days and HDR mode on cloudy days. This allows the system to automatically apply the optimal shooting mode based on the weather information.

[0101] The photo shooting system can further analyze the user's past shooting history and suggest shooting modes tailored to the user's preferences. For example, if the user has taken many sports photos in the past, the system will prioritize suggesting the sports mode. Similarly, if the user has taken many landscape photos, the system will prioritize suggesting the landscape mode. Furthermore, if the user has taken many portrait photos, the system will prioritize suggesting the portrait mode. This allows the system to suggest the optimal shooting mode based on the user's past shooting history.

[0102] The photo-taking system can estimate the user's emotions and adjust the timing of switching shooting modes based on those emotions. For example, if the user is excited, it will switch to burst mode faster to take more photos. If the user is relaxed, it will switch to burst mode slower, allowing for a more relaxed shooting pace. If the user is focused, it will optimize the burst mode switching to ensure that important moments are not missed. This allows the system to adjust the timing of burst mode switching according to the user's emotions.

[0103] The photo-taking system can estimate the user's emotions and adjust the criteria for selecting the best shot based on those emotions. For example, if the user is excited, it will prioritize photos with movement. If the user is relaxed, it will prioritize photos with a calm atmosphere. If the user is focused, it will prioritize photos with a well-balanced composition. This allows the system to adjust the criteria for selecting the best shot according to the user's emotions.

[0104] The photo-taking system can estimate the user's emotions and adjust the display order of selected photos based on those emotions. For example, if the user is excited, photos with movement will be displayed first. If the user is relaxed, photos with a calm atmosphere will be displayed first. If the user is focused, photos with a well-balanced composition will be displayed first. This allows the display order of selected photos to be adjusted according to the user's emotions.

[0105] The photo-taking system can estimate the user's emotions and adjust the interface display based on those emotions. For example, if the user is excited, it can provide an interface with bright colors. If the user is relaxed, it can provide an interface with calm colors. If the user is focused, it can provide a simple and highly visible interface. This allows the interface display to be adjusted according to the user's emotions.

[0106] The photo-taking system can estimate the user's emotions and adjust the interface's operation procedures based on those emotions. For example, if the user is excited, it can provide simple operation procedures; if the user is relaxed, it can provide detailed operation procedures; and if the user is focused, it can provide efficient operation procedures. This allows the interface's operation procedures to be adjusted according to the user's emotions.

[0107] The following briefly describes the processing flow for example form 2.

[0108] Step 1: The continuous shooting mode switching section automatically applies various shooting modes when taking pictures. For example, when shooting fast-moving subjects, the sports mode is applied, and when shooting still landscapes, the landscape mode is applied. This allows for optimal shooting according to the characteristics of the subject. Step 2: The selection unit analyzes the photos taken by the continuous shooting mode switching unit and suggests the best shot. For example, it selects the best photo by considering factors such as face recognition, expression analysis, and compositional balance. This makes it easy for the user to choose the optimal photo. Step 3: The environmental recognition unit determines the shooting environment and optimizes the settings. For example, it automatically uses the flash in dark places and applies HDR mode in backlit situations. This makes it possible to shoot with optimal settings in a variety of shooting environments. Step 4: The user interface provides an intuitive interface for viewing and selecting suggested photos. For example, users can view details simply by tapping a photo displayed as a thumbnail on their smartphone screen. This allows users to easily select and review photos.

[0109] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0110] Data generation model 58 is a form of so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include text generation AI, image generation AI, and multimodal generation AI. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats from audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVMs), k-means clustering, convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each of the above parts is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example.Furthermore, processing performed by AI, including generative AI, may be replaced with rule-based processing, and rule-based processing may be replaced with processing performed by AI, including generative AI.

[0111] Furthermore, the processing performed by the data processing system 10 described above is carried out by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but it may also be carried out by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. In addition, 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.

[0112] Each of the multiple elements described above, including the continuous shooting mode switching unit, selection unit, environment recognition unit, and user interface unit, is implemented in at least one of the smart device 14 and the data processing unit 12. For example, the continuous shooting mode switching unit is implemented by the control unit 46A of the smart device 14, applying sports mode when shooting fast-moving subjects and landscape mode when shooting still landscapes. The selection unit is implemented by the identification processing unit 290 of the data processing unit 12, selecting the best photograph by considering factors such as face recognition, expression analysis, and compositional balance. The environment recognition unit is implemented by the control unit 46A of the smart device 14, automatically using the flash in dark places and applying HDR mode in backlit situations. The user interface unit is implemented by the control unit 46A of the smart device 14, allowing users to view details simply by tapping on a thumbnail of a photograph displayed on the smartphone screen. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be modified in various ways.

[0113] [Second Embodiment] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0114] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0115] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0116] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0117] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0118] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0119] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0120] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing by the processor 28. The storage 32 stores the specific processing program 56.

[0121] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0122] Storage 32 stores the data generation model 58 and the 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 the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0123] In the smart glasses 214, specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. 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 acting as a control unit 46A according to the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0124] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0125] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0126] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0127] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart glasses 214 or an external device, and the smart glasses 214 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0128] Each of the multiple elements described above, including the continuous shooting mode switching unit, selection unit, environment recognition unit, and user interface unit, is implemented in at least one of the smart glasses 214 and the data processing unit 12. For example, the continuous shooting mode switching unit is implemented by the control unit 46A of the smart glasses 214, applying sports mode when shooting fast-moving subjects and landscape mode when shooting still landscapes. The selection unit is implemented by the identification processing unit 290 of the data processing unit 12, selecting the best photograph by considering factors such as face recognition, expression analysis, and compositional balance. The environment recognition unit is implemented by the control unit 46A of the smart glasses 214, automatically using the flash in dark places and applying HDR mode in backlit situations. The user interface unit is implemented by the control unit 46A of the smart glasses 214, allowing users to view details simply by tapping on a thumbnail of a photograph displayed on the smartphone screen. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be modified in various ways.

[0129] [Third Embodiment] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0130] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0131] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0132] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0133] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0134] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0135] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0136] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0137] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0138] Storage 32 stores the data generation model 58 and the 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 the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0139] In the headset terminal 314, specific processing is performed by the processor 46. The storage 50 stores a specific program 60. The processor 46 reads the specific program 60 from the storage 50 and executes the read specific program 60 on the RAM 48. The specific processing is realized by the processor 46 acting as a control unit 46A according to the specific program 60 executed on the RAM 48. The headset terminal 314 also has a data generation model 58 and an emotion identification model 59, similar to the data generation model and emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0140] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0141] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0142] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0143] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset terminal 314, but may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset terminal 314. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the headset terminal 314 or an external device, and the headset terminal 314 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0144] Each of the multiple elements described above, including the continuous shooting mode switching unit, selection unit, environment recognition unit, and user interface unit, is implemented in at least one of the headset terminal 314 and the data processing unit 12. For example, the continuous shooting mode switching unit is implemented by the control unit 46A of the headset terminal 314, applying sports mode when shooting fast-moving subjects and landscape mode when shooting still landscapes. The selection unit is implemented by the identification processing unit 290 of the data processing unit 12, selecting the best photograph by considering factors such as face recognition, expression analysis, and compositional balance. The environment recognition unit is implemented by the control unit 46A of the headset terminal 314, automatically using the flash in dark places and applying HDR mode in backlit situations. The user interface unit is implemented by the control unit 46A of the headset terminal 314, allowing users to view details simply by tapping on the thumbnail displayed on the smartphone screen. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be modified in various ways.

[0145] [Fourth Embodiment] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0146] As shown in Figure 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.

[0147] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN and / or LAN.

[0148] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0149] The microphone 238 receives voice signals from the user and accepts instructions from the user. The microphone 238 captures the voice signals from the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0150] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS image sensor or CCD image sensor, which captures images of the area around the user (for example, an imaging range defined by a field of view equivalent to the field of vision of a typical healthy person).

[0151] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0152] The controlled 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 robot 414's emotions can be expressed by controlling these motors. The robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0153] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0154] The processor 28 reads a 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 acting as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0155] Storage 32 stores the data generation model 58 and the 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 the user's emotions using the emotion identification model 59 and perform identification processing using the user's emotions. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotions, including but not limited to these examples. Furthermore, emotion estimation and prediction also include, for example, emotion analysis.

[0156] In robot 414, specific processing is performed by processor 46. A specific program 60 is stored in storage 50. Processor 46 reads the specific program 60 from storage 50 and executes it on RAM 48. The specific processing is achieved by processor 46 acting as a control unit 46A according to the specific program 60 executed on RAM 48. Robot 414 also has data generation model 58 and emotion identification model 59, similar to those of the robot, and can perform processing similar to that of the specific processing unit 290 using these models.

[0157] Furthermore, other devices besides the data processing device 12 may also 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 obtains processing results (such as prediction results) using the data generation model 58 by communicating with the server device that has the data generation model 58. Also, the data processing device 12 may be a server device or a terminal device owned by the user (for example, a mobile phone, robot, home appliance, etc.).

[0158] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0159] The data generation model 58 is a so-called generative AI. An example of a 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 is input with prompts containing instructions, and inference data such as audio data representing speech, text data representing text, and image data representing images (e.g., still image data or video data). The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference result in one or more data formats such as audio data, text data, and image data. The data generation model 58 includes, for example, text generation AI, image generation AI, and multimodal generation AI. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization. The specific processing unit 290 performs the specific processing described above using the data generation model 58. The data generation model 58 may be a fine-tuned model that outputs inference results from prompts that do not contain instructions, in which case the data generation model 58 can output inference results from prompts that do not contain instructions. In the data processing device 12, etc., there are multiple types of data generation models 58, and the data generation model 58 includes AI other than generative AI. AI other than generative AI includes, for example, linear regression, logistic regression, decision trees, random forests, support vector machines (SVM), k-means clustering, convolutional neural networks (CNN), recurrent neural networks (RNN), generative adversarial networks (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. Also, the AI ​​may be an AI agent. Furthermore, when the processing of each part described above is performed by the AI, the processing may be performed by the AI ​​in part or in whole, but is not limited to this example. Also, processing performed by an AI including a generative AI may be replaced by rule-based processing, and rule-based processing may be replaced by processing performed by an AI including a generative AI.

[0160] 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 performed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but it may also be performed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. In addition, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the robot 414 or an external device, and the robot 414 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0161] Each of the multiple elements described above, including the continuous shooting mode switching unit, selection unit, environment recognition unit, and user interface unit, is implemented in at least one of the robot 414 and the data processing unit 12. For example, the continuous shooting mode switching unit is implemented by the control unit 46A of the robot 414, applying sports mode when shooting fast-moving subjects and landscape mode when shooting still landscapes. The selection unit is implemented by the identification processing unit 290 of the data processing unit 12, selecting the best photograph by considering factors such as face recognition, expression analysis, and compositional balance. The environment recognition unit is implemented by the control unit 46A of the robot 414, automatically using the flash in dark places and applying HDR mode in backlit situations. The user interface unit is implemented by the control unit 46A of the robot 414, allowing users to view details simply by tapping on a thumbnail of a photograph displayed on a smartphone screen. The correspondence between each unit and the device or control unit is not limited to the examples described above and can be modified in various ways.

[0162] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0163] Figure 9 shows the emotion map 400, in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0164] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0165] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0166] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, and motorcycles, emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated based, for example, on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0167] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0168] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0169] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing method for the specific process may be used, which includes computer 22 and multiple other computers.

[0170] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0171] 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.

[0172] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0173] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0174] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0175] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0176] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0177] Furthermore, although the above-described examples were divided into four embodiments, some or all of these embodiments may be combined. Also, the smart device 14, smart glasses 214, headset terminal 314, and robot 414 are just examples, and they may be combined, or other devices may be used. Also, although the above-described examples were divided into two embodiments, Embodiment 1 and Embodiment 2, these may be combined.

[0178] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and other things that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0179] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted to be incorporated by reference.

[0180] (Note 1) A continuous shooting mode switching unit that automatically applies various shooting modes to take pictures, The continuous shooting mode switching unit analyzes the photos taken and a selection unit suggests the best shot, An environment recognition unit that determines the shooting environment and optimizes the settings, It includes a user interface section that allows users to intuitively view and select proposed photos. A system characterized by the following features. (Note 2) The continuous shooting mode switching unit is, When photographing fast-moving subjects, apply sports mode; when photographing still landscapes, apply landscape mode. The system described in Appendix 1, characterized by the features described herein. (Note 3) The aforementioned selection unit is The best photograph is selected by considering factors such as facial recognition, expression analysis, and compositional balance. The system described in Appendix 1, characterized by the features described herein. (Note 4) The aforementioned environment recognition unit, The flash is automatically used in dark places, and HDR mode is applied in backlit situations. The system described in Appendix 1, characterized by the features described herein. (Note 5) The user interface unit is You can view details simply by tapping the thumbnail image displayed on your smartphone screen. The system described in Appendix 1, characterized by the features described herein. (Note 6) The continuous shooting mode switching unit is, It estimates the user's emotions and adjusts the timing of switching to continuous shooting mode based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 7) The continuous shooting mode switching unit is, The camera analyzes the subject's movement patterns in real time and selects the optimal shooting mode. The system described in Appendix 1, characterized by the features described herein. (Note 8) The continuous shooting mode switching unit is, It detects changes in the shooting scene and automatically applies the appropriate shooting mode for that scene. The system described in Appendix 1, characterized by the features described herein. (Note 9) The continuous shooting mode switching unit is, It estimates the user's emotions and determines the priority of shooting modes based on the estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 10) The continuous shooting mode switching unit is, The system recognizes the attributes of the subject and applies the appropriate shooting mode. The system described in Appendix 1, characterized by the features described herein. (Note 11) The continuous shooting mode switching unit is, The system acquires weather information at the time of shooting and applies a shooting mode appropriate to the weather. The system described in Appendix 1, characterized by the features described herein. (Note 12) The aforementioned selection unit is The system estimates the user's emotions and adjusts the criteria for selecting the best shot based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 13) The aforementioned selection unit is The system analyzes the subject's movements and facial expressions from the captured photographs to select the most natural moment. The system described in Appendix 1, characterized by the features described herein. (Note 14) The aforementioned selection unit is From the photographs taken, select the best ones, taking into consideration the beauty of the background and the balance of colors. The system described in Appendix 1, characterized by the features described herein. (Note 15) The aforementioned selection unit is It estimates the user's emotions and adjusts the display order of selected photos based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 16) The aforementioned selection unit is From the photographs taken, select the best ones, taking into consideration the subject's clothing and the colors of their accessories. The system described in Appendix 1, characterized by the features described herein. (Note 17) The aforementioned selection unit is From the photographs taken, select the best ones, taking into consideration the variations in the subject's position and pose. The system described in Appendix 1, characterized by the features described herein. (Note 18) The aforementioned environment recognition unit, It estimates the user's emotions and adjusts the shooting environment settings based on the estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 19) The aforementioned environment recognition unit, The system analyzes the light intensity and direction of the shooting environment in real time and applies the optimal settings. The system described in Appendix 1, characterized by the features described herein. (Note 20) The aforementioned environment recognition unit, It detects the effects of sound and wind in the shooting environment and applies settings accordingly. The system described in Appendix 1, characterized by the features described herein. (Note 21) The aforementioned environment recognition unit, It estimates the user's emotions and prioritizes adjusting the shooting environment settings based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 22) The aforementioned environment recognition unit, It detects the temperature and humidity of the shooting environment and applies settings accordingly. The system described in Appendix 1, characterized by the features described herein. (Note 23) The aforementioned environment recognition unit, It recognizes the background color and pattern of the shooting environment and applies settings accordingly. The system described in Appendix 1, characterized by the features described herein. (Note 24) The user interface unit is It estimates the user's emotions and adjusts the interface display based on those estimated emotions. The system described in Appendix 1, characterized by the features described herein. (Note 25) The user interface unit is When displaying the interface, the system selects the optimal display method by referring to the user's past operation history. The system described in Appendix 1, characterized by the features described herein. (Note 26) The user interface unit is When the interface is displayed, it tracks the user's eye movements and enables operations that correspond to their gaze. The system described in Appendix 1, characterized by the features described herein. (Note 27) The user interface unit is It estimates the user's emotions and adjusts the interface operation procedures based on the estimated user emotions. The system described in Appendix 1, characterized by the features described herein. (Note 28) The user interface unit is When displaying the interface, the optimal display method is selected considering the user's device information. The system described in Appendix 1, characterized by the features described herein. (Note 29) The user interface unit is When the interface is displayed, it recognizes the user's voice commands and enables voice control. The system described in Appendix 1, characterized by the features described herein. [Explanation of symbols]

[0181] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots

Claims

1. A continuous shooting mode switching unit that automatically applies various shooting modes to take pictures, The continuous shooting mode switching unit analyzes the photos taken and a selection unit suggests the best shot, An environment recognition unit that determines the shooting environment and optimizes the settings, It includes a user interface section that allows users to intuitively view and select proposed photos. A system characterized by the following features.

2. The continuous shooting mode switching unit is, When photographing fast-moving subjects, apply sports mode; when photographing still landscapes, apply landscape mode. The system according to feature 1.

3. The aforementioned selection unit is The best photograph is selected by considering factors such as facial recognition, expression analysis, and compositional balance. The system according to feature 1.

4. The aforementioned environment recognition unit, The flash is automatically used in dark places, and HDR mode is applied in backlit situations. The system according to feature 1.

5. The user interface unit is You can view details simply by tapping the thumbnail image displayed on your smartphone screen. The system according to feature 1.

6. The continuous shooting mode switching unit is, It estimates the user's emotions and adjusts the timing of switching to continuous shooting mode based on the estimated user emotions. The system according to feature 1.

7. The continuous shooting mode switching unit is, The camera analyzes the subject's movement patterns in real time and selects the optimal shooting mode. The system according to feature 1.

8. The continuous shooting mode switching unit is, It detects changes in the shooting scene and automatically applies the appropriate shooting mode for that scene. The system according to feature 1.

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