Electronic device, and method for generating image story

Abstract

An electronic device according to various embodiments of the present document may comprise a display, a memory and at least one processor. The memory can store instructions that can be individually / collectively executed by the at least one processor and that, when executed, instructs the electronic device to determine, on the basis of a history of sharing, with another device, an image or an image story including at least one image and / or a generation history of the image story, the generation of an image story including the least one image corresponding to a first image. The memory can store instructions for instructing the electronic device to: generate first analysis information associated with the first image; analyze images stored in the memory so as to select at least one second image having second analysis information corresponding to the first analysis information; and generate an image story including the at least one second image. Other various embodiments are possible.

Description

Electronic device and image story creation method

[0001] This document relates to an electronic device, and, for example, to a method for an electronic device to generate an image story containing images.

[0002] A portable electronic device, such as a smartphone or tablet PC (hereinafter referred to as an electronic device), can provide various user experiences by utilizing various applications. The electronic device may include at least one camera to provide the user with an experience of capturing images (or videos), and may provide various functions, such as editing or sharing captured images, through a gallery application.

[0003] Gallery applications can provide an image story feature. This feature may allow users to collect multiple images they have taken and present them as a video or slideshow. For example, an electronic device can generate an image story through a gallery application using images taken on a specific date or at a specific location, or using images directly selected by the user. This image story feature provides an experience that allows users to reminisce about the past and can also offer the ability to share image stories with other users.

[0004] When an electronic device automatically selects images to generate an image story, an image story that the user does not want or is inappropriate for the user may be generated. Additionally, when the user manually selects the images to generate the image story, the process of direct image selection can be cumbersome for the user.

[0005] An electronic device according to various embodiments of this disclosure (or specification, invention) may include a display, memory, and at least one processor.

[0006] According to one embodiment, the memory may be executed individually or collectively by at least one processor, and may store instructions that, at the time of execution, cause the electronic device to determine the creation of an image story containing at least one image corresponding to a first image based on a shared history to another device of an image story containing at least one image and / or a creation history of an image story containing an image or at least one image.

[0007] According to one embodiment, the memory may store instructions for the electronic device to generate first analysis information associated with the first image, analyze images stored in the memory, select at least one second image having second analysis information corresponding to the first analysis information, and generate an image story including the at least one second image.

[0008] A method performed by an electronic device according to various embodiments of the present document may include: determining to create an image story including at least one image corresponding to a first image based on a history of sharing to another device of an image story including an image or at least one image and / or a history of creating an image story; creating first analysis information associated with the first image; analyzing images stored in the electronic device to select at least one second image having second analysis information corresponding to the first analysis information; and creating an image story including at least one second image.

[0009] A computer-readable non-transient recording medium according to various embodiments of the present document may store instructions for performing, based on a history of sharing to another device of an image or an image story including at least one image and / or a history of creating an image story, an operation of determining the creation of an image story including at least one image corresponding to a first image; an operation of creating first analysis information associated with the first image; an operation of analyzing images stored in the electronic device to select at least one second image having second analysis information corresponding to the first analysis information; and an operation of creating an image story including at least one second image.

[0010] According to various embodiments of the present document, by generating an image story by selecting images that meet the user's requirements based on usage information of the electronic device, an electronic device and a method for generating an image story of the electronic device can be provided, which can increase the user's satisfaction with the use of the image story.

[0011] FIG. 1 is a block diagram of an electronic device in a network environment according to various embodiments.

[0012] FIG. 2 illustrates a screen related to an image story in a gallery application according to one embodiment.

[0013] FIG. 3 is a block diagram of an electronic device according to various embodiments.

[0014] FIG. 4 is a block diagram of an AI system according to one embodiment.

[0015] FIG. 5 is a block diagram of software modules for generating an image story according to one embodiment.

[0016] FIG. 6 is a flowchart of an image story generation method according to one embodiment.

[0017] FIG. 7 illustrates the screens of an SNS application and a gallery application according to one embodiment.

[0018] FIG. 8 illustrates a method for selecting images to be included in an image story among images of a gallery application according to one embodiment.

[0019] FIG. 9 illustrates a generated image story according to one embodiment.

[0020] FIG. 10 illustrates a method for determining the attributes of an image story according to an application that shares the image story according to one embodiment.

[0021] FIG. 11 illustrates a method for determining the attributes of an image story according to a counterpart to whom the image story will be shared, according to one embodiment.

[0022] FIG. 12 illustrates a screen showing images to be shared in a gallery application according to one embodiment, visually distinguished.

[0023] FIG. 13 illustrates a screen that allows selecting an image to be shared in a gallery application according to one embodiment.

[0024] Hereinafter, embodiments of this document are described in detail with reference to the drawings so that those skilled in the art can easily implement them. However, this document may be implemented in various different forms and is not limited to the embodiments described herein. In relation to the description of the drawings, identical or similar reference numerals may be used for identical or similar components. Additionally, in the drawings and related descriptions, descriptions of well-known functions and configurations may be omitted for clarity and brevity.

[0025] FIG. 1 is a block diagram of an electronic device in a network environment according to various embodiments.

[0026] Referring to FIG. 1, in a network environment (100), an electronic device (101) may communicate with an electronic device (102) through a first network (198) (e.g., a short-range wireless communication network) or with at least one of an electronic device (104) or a server (108) through a second network (199) (e.g., a long-range wireless communication network). According to one embodiment, the electronic device (101) may communicate with the electronic device (104) through a server (108). According to one embodiment, the electronic device (101) may include a processor (120), memory (130), input module (150), sound output module (155), display module (160), audio module (170), sensor module (176), interface (177), connection terminal (178), haptic module (179), camera module (180), power management module (188), battery (189), communication module (190), subscriber identification module (196), or antenna module (197). In some embodiments, at least one of these components (e.g., connection terminal (178)) may be omitted from the electronic device (101), or one or more other components may be added. In some embodiments, some of these components (e.g., sensor module (176), camera module (180), or antenna module (197)) may be integrated into a single component (e.g., display module (160)).

[0027] The processor (120) can control at least one other component (e.g., hardware or software component) of the electronic device (101) connected to the processor (120) by executing software (e.g., program (140)), for example, and can perform various data processing or operations. According to one embodiment, as at least part of the data processing or operations, the processor (120) can store commands or data received from other components (e.g., sensor module (176) or communication module (190)) in volatile memory (132), process the commands or data stored in volatile memory (132), and store the resulting data in non-volatile memory (134). According to one embodiment, the processor (120) may include a main processor (121) (e.g., central processing unit or application processor) or an auxiliary processor (123) that can operate independently or together with it (e.g., graphics processing unit, neural processing unit (NPU), image signal processor, sensor hub processor, or communication processor). For example, if the electronic device (101) includes a main processor (121) and an auxiliary processor (123), the auxiliary processor (123) may be configured to use lower power than the main processor (121) or to be specialized for a designated function. The auxiliary processor (123) may be implemented separately from the main processor (121) or as part thereof.

[0028] The auxiliary processor (123) may control at least some of the functions or states associated with at least one component of the electronic device (101) (e.g., display module (160), sensor module (176), or communication module (190)) on behalf of the main processor (121) while the main processor (121) is in an inactive (e.g., sleep) state, or together with the main processor (121) while the main processor (121) is in an active (e.g., application execution) state. According to one embodiment, the auxiliary processor (123) (e.g., image signal processor or communication processor) may be implemented as part of another functionally related component (e.g., camera module (180) or communication module (190)). According to one embodiment, the auxiliary processor (123) (e.g., neural network processing unit) may include a hardware structure specialized for processing an artificial intelligence model. The artificial intelligence model may be generated through machine learning. Such learning may be performed, for example, on the electronic device (101) itself where the artificial intelligence model is executed, or through a separate server (e.g., server (108)). The learning algorithm may include, for example, supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but is not limited to the examples described above. The artificial intelligence model may include a plurality of artificial neural network layers.An artificial neural network may be a deep neural network (DNN), a convolutional neural network (CNN), a recurrent neural network (RNN), a restricted Boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), a deep Q-network, or a combination of two or more of the above, but is not limited to the examples described above. In addition to the hardware structure, the artificial intelligence model may include a software structure, either additionally or substantially.

[0029] The memory (130) can store various data used by at least one component of the electronic device (101) (e.g., processor (120) or sensor module (176)). The data may include, for example, input data or output data for software (e.g., program (140)) and related commands. The memory (130) may include volatile memory (132) or non-volatile memory (134).

[0030] The program (140) may be stored as software in memory (130) and may include, for example, an operating system (142), middleware (144), or an application (146).

[0031] The input module (150) can receive commands or data to be used for a component of the electronic device (101) (e.g., processor (120)) from outside the electronic device (101) (e.g., user). The input module (150) may include, for example, a microphone, a mouse, a keyboard, a key (e.g., a button), or a digital pen (e.g., a stylus pen).

[0032] The sound output module (155) can output a sound signal to the outside of the electronic device (101). The sound output module (155) may include, for example, a speaker or a receiver. The speaker may be used for general purposes, such as multimedia playback or recording playback. The receiver may be used to receive incoming calls. According to one embodiment, the receiver may be implemented separately from the speaker or as part thereof.

[0033] The display module (160) can visually provide information to an external (e.g., user) of the electronic device (101). The display module (160) may include, for example, a display, a holographic device, or a projector and a control circuit for controlling said device. According to one embodiment, the display module (160) may include a touch sensor configured to detect a touch, or a pressure sensor configured to measure the intensity of the force generated by said touch.

[0034] The audio module (170) can convert sound into an electrical signal or, conversely, convert an electrical signal into sound. According to one embodiment, the audio module (170) can acquire sound through the input module (150) or output sound through the sound output module (155) or an external electronic device (e.g., electronic device (102)) (e.g., speaker or headphones) connected directly or wirelessly to the electronic device (101).

[0035] The sensor module (176) can detect the operating state of the electronic device (101) (e.g., power or temperature) or the external environmental state (e.g., user state) and generate an electrical signal or data value corresponding to the detected state. According to one embodiment, the sensor module (176) may include, for example, a gesture sensor, a gyroscope sensor, a barometric pressure sensor, a magnetic sensor, an accelerometer sensor, a grip sensor, a proximity sensor, a color sensor, an IR (infrared) sensor, a biosensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

[0036] The interface (177) may support one or more specified protocols that can be used for the electronic device (101) to be connected directly or wirelessly to an external electronic device (e.g., electronic device (102)). According to one embodiment, the interface (177) may include, for example, a high definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

[0037] The connection terminal (178) may include a connector through which the electronic device (101) can be physically connected to an external electronic device (e.g., electronic device (102)). According to one embodiment, the connection terminal (178) may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector (e.g., a headphone connector).

[0038] The haptic module (179) can convert an electrical signal into a mechanical stimulus (e.g., vibration or movement) or an electrical stimulus that can be perceived by the user through tactile or kinesthetic senses. According to one embodiment, the haptic module (179) may include, for example, a motor, a piezoelectric element, or an electric stimulation device.

[0039] The camera module (180) can capture still images and video. According to one embodiment, the camera module (180) may include one or more lenses, image sensors, image signal processors, or flashes.

[0040] The power management module (188) can manage power supplied to the electronic device (101). According to one embodiment, the power management module (188) can be implemented, for example, as at least part of a power management integrated circuit (PMIC).

[0041] The battery (189) can supply power to at least one component of the electronic device (101). According to one embodiment, the battery (189) may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0042] The communication module (190) can support the establishment of a direct (e.g., wired) communication channel or a wireless communication channel between an electronic device (101) and an external electronic device (e.g., electronic device (102), electronic device (104), or server (108)), and the performance of communication through the established communication channel. The communication module (190) may include one or more communication processors that operate independently of the processor (120) (e.g., application processor) and support direct (e.g., wired) communication or wireless communication. According to one embodiment, the communication module (190) may include a wireless communication module (192) (e.g., cellular communication module, short-range wireless communication module, or GNSS (global navigation satellite system) communication module) or a wired communication module (194) (e.g., LAN (local area network) communication module, or power line communication module). The corresponding communication module among these communication modules can communicate with an external electronic device (104) through a first network (198) (e.g., a short-range communication network such as Bluetooth, WiFi (wireless fidelity) direct, or IrDA (infrared data association)) or a second network (199) (e.g., a legacy cellular network, a 5G network, a next-generation communication network, the Internet, or a computer network (e.g., a LAN or WAN)). These various types of communication modules may be integrated into a single component (e.g., a single chip) or implemented as multiple separate components (e.g., multiple chips). The wireless communication module (192) can identify or authenticate the electronic device (101) within a communication network such as the first network (198) or the second network (199) using subscriber information (e.g., International Mobile Subscriber Identifier (IMSI)) stored in the subscriber identification module (196).

[0043] The wireless communication module (192) can support 5G networks and next-generation communication technologies following 4G networks, for example, new radio access technology. NR access technology can support high-speed transmission of high-capacity data (enhanced mobile broadband (eMBB)), minimization of terminal power and connection of multiple terminals (massive machine type communications (mMTC)), or high reliability and low latency (ultra-reliable and low-latency communications (URLLC)). The wireless communication module (192) can support a high-frequency band (e.g., mmWave band) to achieve a high data transmission rate, for example. The wireless communication module (192) can support various technologies for securing performance in the high-frequency band, such as beamforming, massive MIMO (multiple-input and multiple-output), full-dimensional MIMO (FD-MIMO), array antenna, analog beam-forming, or large-scale antenna. The wireless communication module (192) can support various requirements specified in the electronic device (101), external electronic device (e.g., electronic device (104)), or network system (e.g., second network (199)). According to one embodiment, the wireless communication module (192) may support a Peak data rate (e.g., 20 Gbps or more) for eMBB realization, loss coverage (e.g., 164 dB or less) for mMTC realization, or U-plane latency (e.g., downlink (DL) and uplink (UL) each 0.5 ms or less, or round trip 1 ms or less) for URLLC realization.

[0044] An antenna module (197) can transmit a signal or power to or from an external source (e.g., an external electronic device). According to one embodiment, the antenna module (197) may include an antenna comprising a radiator made of a conductor or a conductive pattern formed on a substrate (e.g., a PCB). According to one embodiment, the antenna module (197) may include a plurality of antennas (e.g., an array antenna). In this case, at least one antenna suitable for a communication method used in a communication network, such as a first network (198) or a second network (199), may be selected from the plurality of antennas, for example, by a communication module (190). A signal or power may be transmitted or received between the communication module (190) and an external electronic device through the selected at least one antenna. According to some embodiments, in addition to the radiator, other components (e.g., a radio frequency integrated circuit (RFIC)) may be additionally formed as part of the antenna module (197).

[0045] According to various embodiments, the antenna module (197) may form a mmWave antenna module. According to one embodiment, the mmWave antenna module may include a printed circuit board, an RFIC disposed on or adjacent to a first surface (e.g., bottom surface) of the printed circuit board and capable of supporting a specified high frequency band (e.g., mmWave band), and a plurality of antennas (e.g., array antennas) disposed on or adjacent to a second surface (e.g., top surface or side surface) of the printed circuit board and capable of transmitting or receiving a signal of the specified high frequency band.

[0046] At least some of the above components can be connected to each other via a communication method between peripheral devices (e.g., bus, GPIO (general purpose input and output), SPI (serial peripheral interface), or MIPI (mobile industry processor interface)) and exchange signals (e.g., commands or data) with each other.

[0047] According to one embodiment, commands or data may be transmitted or received between an electronic device (101) and an external electronic device (104) through a server (108) connected to a second network (199). Each of the external electronic devices (102, or 104) may be the same or a different type of device as the electronic device (101). According to one embodiment, all or part of the operations performed on the electronic device (101) may be performed on one or more of the external electronic devices (102, 104, or 108). For example, if the electronic device (101) needs to perform a function or service automatically or in response to a request from a user or another device, the electronic device (101) may request one or more external electronic devices to perform at least part of the function or service instead of performing the function or service itself or additionally. One or more external electronic devices that receive the above request may execute at least part of the requested function or service, or additional function or service related to the request, and transmit the result of the execution to the electronic device (101). The electronic device (101) may provide the result as is or additionally processed as at least part of the response to the request. For this purpose, for example, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technology may be used. The electronic device (101) may provide ultra-low latency services using, for example, distributed computing or mobile edge computing. In one embodiment, the external electronic device (104) may include an Internet of Things (IoT) device. The server (108) may be an intelligent server using machine learning and / or neural networks. According to one embodiment, the external electronic device (104) or the server (108) may be included within a second network (199).The electronic device (101) can be applied to intelligent services (e.g., smart home, smart city, smart car, or healthcare) based on 5G communication technology and IoT-related technology.

[0048] FIG. 2 illustrates a screen related to an image story in a gallery application according to one embodiment.

[0049] According to one embodiment, the electronic device (200) may provide a gallery application that manages images (or videos) captured through a camera, images acquired from an external device or network and stored, and provides image-related functions such as editing and sharing.

[0050] According to one embodiment, the gallery application may provide an image story function. In this document, the image story function may be a function that selects two or more images from among the images stored in the electronic device (200) through the gallery application and provides them as a video, GIF (graphic interchange format) image, or slideshow. For example, the electronic device (200) may create an image story of images related to a specific subject, person, event, date, or place through the gallery application, or may create an image story of images directly selected by the user.

[0051] Referring to FIG. 2, the electronic device (200) may provide a story item (220) that displays a list of image stories at the bottom of a gallery application screen (210). When the story item (220) is selected according to user input, a list of thumbnails (232, 234, 240) of image stories that have been created and saved may be provided. For example, the electronic device (200) may create a thumbnail based on a representative image of any one of the images in the image story (240) and display the title of the image story (e.g., Gangneung City Travel) based on the image object, tag, or user input.

[0052] According to one embodiment, the electronic device (200) can play the image story (240) when a thumbnail of the image story is selected. According to one embodiment, the image story may provide a plurality of images in a form such as a video or a slideshow, and during playback, each image may be played sequentially while providing transition effects (e.g., focusing, or fade in / out). Additionally, the image story may be generated according to a theme corresponding to the included images and may provide background music.

[0053] According to one embodiment, the electronic device (200) can select images to be included in an image story based on the time of shooting, location, subject (e.g., person, or object), and / or event among images stored on a gallery application.

[0054] According to one embodiment, the electronic device (200) can create an image story by selecting a plurality of images based on the sharing history of images through a message application or a social network service (SNS) application, or the user's image story creation history.

[0055] FIG. 3 is a block diagram of an electronic device according to various embodiments.

[0056] Referring to FIG. 3, the electronic device (300) may include a display (330), a camera (340), a communication circuit (350), a processor (310), and a memory (320). Various embodiments of this document may be implemented even if at least some of the illustrated configurations are omitted or replaced with other configurations. In addition to the illustrated configurations, the electronic device (300) may further include at least some of the configurations and / or functions of the electronic device (101) of FIG. 1. At least some of each of the illustrated (or unillustrated) components of the electronic device (300) (e.g., communication circuit (350), processor (310), or memory (320)) may be placed within the housing of the electronic device (300), and at least some of the other components (e.g., display (330), or camera (340)) may be visually exposed to the outside of the housing. At least some of the components of each electronic device (300) may be operatively, functionally, and / or electrically connected to one another.

[0057] According to one embodiment, the display (330) may display image information provided by the processor (310). The display (330) may be implemented as any one of a liquid crystal display (LCD), a light-emitting diode (LED) display, or an organic light-emitting diode (OLED) display, but is not limited thereto. The display (330) may be formed as a touch screen that detects touch and / or proximity touch (or hovering) input using a part of the user's body (e.g., finger) or an input device (e.g., stylus pen). The display (330) may include at least some of the configuration and / or functions of the display module (160) of FIG. 1.

[0058] According to one embodiment, the display (330) may be a flexible display in which at least a portion is flexible. The electronic device (300) may be implemented in various form factors, such as a foldable device or a rollable device, in which the size of the display area can be changed by utilizing the characteristics of the flexible display.

[0059] According to one embodiment, the camera (340) can capture an external image including a subject. According to one embodiment, the camera (340) may include a configuration such as an image sensor (e.g., a Charged Coupled Device (CCD) sensor or a Complementary Metal-Oxide Semiconductor (CMOS) sensor) for converting transmitted light into an electrical signal to generate a digital image, a lens assembly for collecting light emitted from a subject and transmitting it to the image sensor, a flash for providing additional lighting when shooting in a dark environment, an image stabilizer for detecting shaking of the camera (340) and controlling the operating characteristics of the image sensor, a camera memory acting as a buffer for temporarily storing the captured image, and / or an image signal processor (ISP) that performs processing operations such as generating a depth map, 3D modeling, generating a panorama, extracting feature points, image synthesis, or image compensation (e.g., noise reduction, resolution adjustment, brightness adjustment, blurring, sharpening, or softing) on ​​raw data acquired from the image sensor.

[0060] According to one embodiment, the electronic device (300) may include at least one camera on the front and / or rear of the housing. The camera (340) may further include at least some of the configuration and / or functions of the camera module (180) of FIG. 1.

[0061] According to one embodiment, the communication circuit (350) may include various configurations to support wireless communication with a network or an external device. For example, the electronic device (300) may perform cellular wireless communication (e.g., 4G LTE (long term evolution), 5G NR (new radio)) and / or short-range wireless communication (e.g., Wi-Fi, Bluetooth) through the communication circuit (350), and there is no limitation on the type of wireless communication supported by the electronic device (300). The communication circuit (440) may include at least some of the configurations and / or functions of the communication module (190) of FIG. 1.

[0062] According to one embodiment, the memory (320) may include volatile memory and non-volatile memory, and may store various data temporarily or permanently. The memory (320) may include at least some of the configuration and / or functions of the memory (130) of FIG. 1 and may store the program (140) of FIG. 1. The memory (320) may store various instructions that can be executed by the processor (310). Such instructions may include control commands such as arithmetic and logical operations, data movement, and input / output that can be recognized by the processor (310).

[0063] According to one embodiment, the processor (310) is configured to perform operations or data processing regarding the control and / or communication of each component of the electronic device (300) and may be formed of one or more processors. For example, the processor (310) may correspond to a plurality of processors that collectively perform a plurality of operations by dividing them among the processors. The processor (310) may include at least some of the configuration and / or functions of the processor (120) of FIG. 1. Although there is no limitation on the operations and data processing functions that the processor (310) can implement on the electronic device (300), this document will describe in detail various embodiments for creating an image story by selecting images that meet the user's requirements based on usage information of the electronic device (300). The operations of the processor (310) described below may be performed by loading instructions stored in the memory (320).

[0064] In this document, the description that the processor (310) can perform any operation (or function, task, or operation) may be interpreted substantially as meaning that an instruction (or command, computer program) causing the electronic device (300) (or processor (310)) to perform said operation is stored in memory (320) (e.g., non-volatile memory, or storage). Additionally, the description that the processor (310) can perform any operation may be interpreted substantially as meaning that at least one processor, without a fixed number, can perform said operation individually or collectively.

[0065] According to one embodiment, the electronic device (300) can install and run a gallery application. The gallery application can provide a function to search for images and videos captured using the camera (340) or acquired from an external device, and to display them through the display (330). Additionally, the gallery application can provide various image-related functions such as editing, sharing, creating albums, creating animations, backing up, and restoring images or videos.

[0066] According to one embodiment, a gallery application may provide an image story function. The image story function may be a function that collects multiple images taken by a user and provides them as a video or slideshow. The image story function may also be defined by various names such as an image album, a story album, or a smart album.

[0067] In this document, the electronic device (300) is described as recommending a method / target for creating and sharing an image story through a gallery application, but is not limited thereto, and various embodiments of this document may be implemented through other applications.

[0068] According to one embodiment, the processor (310) can check the sharing history of images viewed in a gallery application to other devices. For example, the processor (310) can check information about images (or videos, image stories) shared by a user to another electronic device (300) or a server on a network through an application that provides services such as a social network service (SNS), blog, message, chat, community, or image sharing service. According to one embodiment, when an image is shared, the processor (310) can record information such as the sharing target, such as another electronic device or recipient, and the application used for sharing, by mapping it to the shared image.

[0069] According to one embodiment, the processor (310) can check the history related to when a user of the electronic device (300) has expressed interest in a specific image (e.g., liked it on social media), in addition to when a user has shared an image.

[0070] According to one embodiment, the processor (310) can check the creation history of an image story created on a gallery application. For example, when the image story is automatically created in the gallery application, or when the user creates an image story by selecting an image, the processor (310) can check information such as each image included in the image story, objects within the image, characteristics, or weights related to image playback.

[0071] According to one embodiment, the processor (310) can identify the sharing history of images or the image story creation history based on the analysis of data stored in the memory (320) of the electronic device (300). For example, the processor (310) can analyze application data, usage data, and system data stored in the memory (320), and identify images preferred by the user for sharing or image story creation based on personal data such as profiles, preferences, contexts, or activities identified as a result of the analysis. Based on the analysis of data stored in the memory (320), the processor (310) can identify characteristics preferred by the user regarding image characteristics such as the type of object included in the image, mood, date, or composition.

[0072] According to one embodiment, the processor (310) may determine the creation of an image story that includes at least one image corresponding to at least one image (e.g., a first image) included in the sharing history or story creation history of at least one image or image story to another device, based on the sharing history or story creation history of at least one image or image story. For example, the processor (310) may identify common characteristics of images frequently shared by the user based on the sharing history of the user's images and trigger the creation of an image story that includes images similar to at least one of the images (e.g., a first image). According to one embodiment, the processor (310) may obtain data related to the sharing history or story creation history of an image from data (e.g., usage data, application data, or system data) stored in memory (320), and through the analysis of the obtained data, determine (or guess) whether the user intends to create an image story that includes images associated with (or similar to) a specific image. For example, if the user of the electronic device (300) has a history of sharing items purchased at a department store with friends through an SNS application, the electronic device (300) can trigger the creation of an image story using images associated with a specific shared image.

[0073] According to one embodiment, when the processor (310) triggers the creation of an image story, it may generate analysis information (e.g., first analysis information) associated with at least one image (e.g., first image) among the shared images. For example, the processor (310) may generate analysis information by analyzing a specific image that has a history of sharing or creating an image story, and determining attributes of the image such as a target, object, region of interest, mood, or tag.

[0074] According to one embodiment, the processor (310) may generate first analysis information based on at least one of a profile, preference, context, or activity related to a user of the electronic device (300). For example, when the processor (310) triggers the creation of an image story, it may select at least one first image among shared images based on the sharing history of the image or image story. The processor (310) may identify information related to the sharing of the first image, such as a sharing target such as an external electronic device or a specific recipient, or a sharing application such as a blog / SNS. Based on the object or image tag information included in each of the first images, the processor (310) may generate first analysis information including information such as the relationship or intimacy between the person included in the image and the user, events identified in the image, the shooting location, the behavior or regularity of the person, and activities being performed. Alternatively, the processor (310) may identify information related to interest when the user expresses interest (e.g., likes) in other users' SNS or stories using the electronic device (300).

[0075] According to one embodiment, the processor (310) can determine which category an image belongs to for at least one of a profile, preference, context, or activity. The processor (310) can determine at least one category to which the image belongs based on an event (e.g., a meal, a party, or a sporting event), a shooting location (e.g., a home, a school, or a department store), a person's behavior (e.g., conversation, exercise, or rest), or a relationship between people (e.g., family, or colleagues) by analyzing the objects and environments included in each image. For example, the processor (310) can classify an image of a scene of going to the sea with a child into the sea category as the shooting location and the family category as the relationship between people, and an image of a scene of drinking coffee with a wife into the family category as the relationship between people and the rest category as the behavior of people, and can determine that the two images belong to the same family category.

[0076] According to one embodiment, the processor (310) may generate first analysis information of a first image using an AI model. According to one embodiment, the AI ​​model may be a generative AI model trained to output information such as a profile, preference, context, or activity for an input image. According to one embodiment, the processor (310) may generate a prompt including a request for the first image and analysis information and transmit it to the AI ​​model, and receive the first analysis information from the AI ​​model.

[0077] According to one embodiment, the processor (310) may analyze images stored in memory (320) and select at least one image (e.g., a second image) to be included in an image story. According to one embodiment, the processor (310) may analyze application data, usage data, and system data stored in memory (320), and based on personal data such as profiles, preferences, contexts, or activities identified as a result of the analysis, select at least one second image similar to (or associated with) at least one first image included in the shared history. For example, if the first image selected according to the shared history is a photo of user A of the electronic device (300) and friend B together, the processor (310) may analyze the first image to identify user A and friend B and determine the situation within the first image. The processor (310) can select at least one second image associated with the first image by using various sensor information (e.g., shooting location, time, or weather), contact patterns between user A and friend B via calls, messages, or SNS, and / or analysis of other images other than the first image.

[0078] According to one embodiment, the processor (310) can categorize images identified through a gallery application for at least one of a profile, preference, context, or activity. The processor (310) can select at least one second image that belongs to the same category as at least one first image included in the sharing history among the images stored in memory (320). For example, if an image taken with family is determined as the first image based on the sharing history of the image, images taken with family can be selected as the second image based on object analysis of the stored images or analysis of metadata. As another example, if at least one image taken of an item purchased at a department store is determined as the first image based on the sharing history of the image, an item of the same type (e.g., a bag), an item purchased at the same place (e.g., a department store), or an item purchased on the same date as the item purchased in the first image can be selected as the second image based on object analysis of the stored images or analysis of metadata.

[0079] According to one embodiment, the processor (310) may select at least one image among the stored images to be included in an image story based on an analysis of an object or metadata included in the images stored in the memory (320). For example, the metadata may include information such as information related to the shooting camera (340), image size, file format, shooting location, or time. According to one embodiment, the processor (310) may analyze objects or characters included in the image and may analyze additional information such as the time, location, or frequency of shooting. Through this, images taken in the same location may be classified according to the attributes of the object or the user's interest.

[0080] According to one embodiment, the processor (310) can check for similarity between images (or videos) of a gallery application and at least one first image that has a history of previous sharing. According to one embodiment, the processor (310) can check for similarity between each stored image and the first image through an AI model.

[0081] According to one embodiment, the processor (310) can generate an image story including at least one selected image (e.g., a second image). For example, the processor (310) can generate an image story in the form of a video or slide using the selected images.

[0082] According to one embodiment, the processor (310) may generate an image story including a first image that triggers the generation of an image story and second images associated with the first image, or generate an image story including only second images.

[0083] According to one embodiment, the processor (310) may determine playback attributes for at least some of the second images included in the image story. The processor (310) may assign weights to at least some of the second images included in the image story and determine playback attributes for each of the second images based on the assigned weights. Here, playback attributes may include the playback speed of each image in the image story, an area to be cropped, or whether focusing is applied. For example, the processor (310) may determine at least one image of a bag purchased at a department store as the first image based on the image sharing history, and if the second images determined to correspond to at least one first image include image A of a bag purchased at a department store, image B of a book purchased at a bookstore in the department store, image C of food purchased at a restaurant in the department store, and image D of a captured photo of the purchased bag, the processor may provide a high weight to image A, which has high similarity (or association) with the first image. In this case, the processor (310) can set the playback time of image A in the image story to be longer than that of other images. Additionally, the processor (310) can focus on the area in image A where the bag of high interest to the user is located.

[0084] According to one embodiment, the processor (310) may regenerate (or correct) at least some of the second images included in the image story using a generative AI model and include them in the image story. For example, the processor (310) may transmit the second images constituting the image story, shared history, and / or personalized data to the generative AI model and receive at least one second image regenerated from the generative AI model.

[0085] According to one embodiment, the processor (310) determines a recommended application or a recommended counterpart for sharing an image story, and can determine playback attributes based on the determined recommended application or recommended counterpart.

[0086] According to one embodiment, the processor (310) can identify the tendency of image uploads in each application. For example, the processor (310) can identify the tendency of image uploads in each application based on the user's personalized data (e.g., profile, preferences, context, or activity) when creating an image story. For example, the processor (310) can determine that the user tends to upload images taken in daily life in a blog application and tends to upload images of purchased items in a social media application. In this case, the processor (310) may set the playback time of each image to be the same in the image story for the blog and may not apply focus to each image. Additionally, in the image story for the social media, the processor (310) may assign a high weight to images of items of the type the user prefers or items purchased in preferred places, thereby setting a longer playback time, and / or focus on objects within the image that the user is highly interested in.

[0087] According to one embodiment, the processor (310) may determine the playback attributes of an image story based on the recipient or method of sharing the image story, based on the user's personalized data (e.g., profile, preference, context, or activity) when creating the image story. For example, for an image story intended to be shared with a wife, the processor (310) may set the playback time of each image to be the same and not apply focus to each image. Additionally, for an image story intended to be uploaded to social media, the processor (310) may consider the user's tendencies and assign a high weight to some images, set the playback time to be long, or / or focus on objects within the images that are of high interest to the user.

[0088] According to one embodiment, the electronic device (300) may provide a user interface for sharing at least some of the images stored in the memory (320). For example, the processor (310) may display thumbnails of each image and video on a gallery application and allow the user to select an image to share based on touch input. According to one embodiment, the processor (310) may display an item indicating a recommended application on the user interface for image sharing. For example, the processor (310) may check the user's tendency to upload images through applications such as social media and blogs, and for each image, if it is an image with attributes similar to images uploaded through a specific application, it may display an item indicating that application.

[0089] According to one embodiment, when at least one image is selected according to user input in a user interface for image sharing, the processor (310) may group and display images similar to the selected image and, according to additional user input, generate an image story including the grouped images. Additionally, when at least one image is selected according to user input in a user interface for image sharing, the processor (310) may display an item indicating a recommendation application for images similar to the selected image.

[0090] Instructions for performing the operation of the electronic device (300) (or processor (310)) described above may be stored in a computer-readable recording medium. The recording medium may be tangible and non-transitory. The recording medium may store one or more computer programs containing the instructions.

[0091] FIG. 4 is a block diagram of an AI system according to one embodiment.

[0092] Referring to FIG. 4, the generative AI system (400) may include a User Interface (410), an AI Framework (420), a Generative AI Model (430), a Knowledge Repository (440), and an Application / Service Module (450). These components may be operated on one or more of an electronic device (101), an external electronic device (102 or 104), or a server (108). For example, the User Interface (410) and the AI ​​Framework (420) may be operated on the electronic device (101), and the Knowledge Repository (440) and the Generative AI Model (430) may be operated on the server (108).

[0093] According to one embodiment, the User Interface (410) may receive user input (e.g., user query). User input may be received in the form of text, images, voice (e.g., natural language), video, menu selection, or a combination thereof. The User Interface (410) may include various context information (e.g., running application or user location) related to the generative artificial intelligence system (400) at the time the user input is received, in addition to or instead of the user input. The User Interface (410) may provide the user input or the context information to the AI ​​Framework (420) and provide the result of processing therefrom to the user, for example, through the AI ​​Framework (420). According to one embodiment, in addition to user input, the electronic device may provide context information obtained using information included on the screen to the AI ​​Framework (420). The result may be provided in the form of text, images, voice, video, an action requested by the user (e.g., launching a specified function or app), or a combination thereof.

[0094] According to one embodiment, the AI ​​Framework (420) can identify (e.g., estimate) a user intent based on at least part of user input or context information received from the User Interface (410), control each of the relevant modules (e.g., 221, 223, or 225) to perform a function or action corresponding to the identified user intent, and coordinate collaboration between two or more modules. The AI ​​Framework (420) may include a Prompt Design Module (421), an API / Plug-in Management Module (423), and an Output Modification Module (425), as illustrated in FIG. 2.

[0095] According to one embodiment, the Prompt Design Module (421) can generate a prompt to be input to the Generative AI Model (430) based at least partially on user input or context information received from the User Interface (410). For example, the Prompt Design Module (421) can generate a prompt using user preferences, a prompt library, or prompt examples stored in the Knowledge Repository (440) based at least partially on user input or context information.

[0096] According to one embodiment, the API / Plug-in Management Module (423) may communicate, for example, via an API, with various resources (e.g., Knowledge Repository (440)) that provide said additional information when there is a request for said additional information in relation to user input. Additionally or generally, when a specified action (e.g., function, app, or service) is performed in response to said user input, the API / Plug-in Management Module (423) may request the Application / Service Module (450) to perform said specified action via a corresponding API. The API / Plug-in Management Module (423) may provide information obtained from the Knowledge Repository (440), Application / Service Module 250, or another external resource to the Prompt Design Module (421). That obtained information may be used by the Prompt Design Module (421) to generate a prompt along with the user input, or provided to a generative AI model (430).

[0097] According to one embodiment, the Output Modification Module (425) can fine-tune the results obtained through the Generative AI Model (430) as at least part of the response to user input (e.g., user query). For example, the Output Modification Module (425) can determine whether the content of the response obtained through the Generative AI Model (430) is appropriate as a response to a request made by the user input. For example, the Output Modification Module (425) can determine the degree of relevance, degree of bias (e.g., political or social bias), or degree of harmfulness (e.g., sexual or profanity) of the difference between the response obtained through the Generative AI Model (430) and the user input. Additionally or generally, the Output Modification Module (425) can request that additional AI processing be performed on the obtained response, or provide the user with a hint to avoid unwanted output. For example, additional prompts can be generated through the Prompt Design Module to obtain a response again through the Generative AI Model (430).

[0098] According to one embodiment, the Generative AI Model (430) may form at least part of an artificial intelligence neural network and may include a model that generates images or a model that generates language. The image generation model may include, for example, a generative adversarial network (GAN), a variational autoencoder (VAE), or a Diffusion-based model using a VAE and a Transformer. The language generation model may include, for example, a large language model (LLM), a large multimodal model (LMM), a large vision model (LVM), or a large action model (LAM). The LAM may automatically generate actions for an environment (e.g., a robot, a car, an electronic device (101), or a program (140)). Additionally, for at least some AI models (e.g., LLM), there may be a low-rank adaptation (LoRA) adaptor that is fine-tuned for, for example, a specific task or a specific situation.

[0099] According to one embodiment, an electronic device (e.g., the electronic device (300) of FIG. 3) can perform operations related to the creation of an image story using a generative AI model (450). For example, the electronic device can transmit an image sharing history and / or an image story creation history to the AI ​​model to determine the creation of an image story based on a first image, and / or transmit the first image and images stored in the memory of the electronic device to the AI ​​model to select at least one second image to be included in the image story and create an image story including at least one selected second image.

[0100] FIG. 5 is a block diagram of software modules for generating an image story according to one embodiment.

[0101] Each of the blocks illustrated in FIG. 5 may be software modules that can be executed by a processor of an electronic device (e.g., processor (310) of FIG. 3) or data stored in memory (e.g., memory (320) of FIG. 3). Each software module may include an independent program unit that performs a specific function and may perform a defined function within the system by interacting with the hardware of the electronic device or interacting with other software modules.

[0102] According to one embodiment, an electronic device can generate personal data (530) by analyzing data stored in a memory (e.g., memory (320) of FIG. 3). For example, the electronic device can generate and store application data (App data) (522), usage data (524), or system data (526).

[0103] According to one embodiment, application data (522) may include data generated by a specific application or stored through a specific application. For example, application data (522) of a gallery application may include media data (e.g., images, or videos), metadata or tag information for the media data, and generated album or story information.

[0104] According to one embodiment, the usage data (524) may include the user's usage history or usage patterns for the electronic device. For example, the usage data (524) of a gallery application may include the history of viewing, sharing, editing, and deleting images, as well as the creation and sharing history of stories / albums. Additionally, the usage data (524) may include sharing history information, such as shared images and the recipient, when images are shared through an SNS application or a messaging application.

[0105] According to one embodiment, system data (526) may include data necessary for operating the hardware, operating system, and applications of an electronic device. For example, as system data (526) related to a gallery application, it may include an index related to a captured image, metadata, and user setting data for the gallery application.

[0106] The examples of the application data (522), usage data (524), and system data (526) described above are examples and are not limited thereto.

[0107] According to one embodiment, a data platform (510) can perform the function of managing various types of data stored in the memory of an electronic device. According to one embodiment, the data platform (510) can extract at least a portion of the data stored in memory (e.g., application data (522), usage data (524), or system data (526)) and generate personalized data (530) necessary for creating an image story from the extracted data. For example, the personalized data (530) may include information related to a profile, preference, context, and / or activity associated with the user of the electronic device. Additionally, the personalized data (530) may include a record of the creation of the image story, or information on the sharing of the created image story (e.g., the target of sharing, or the means of sharing). Additionally, the personalized data (530) may include analysis information (e.g., the target, relationship, place, rule, or travel of an object within the image) identified by analyzing an image (or video) included in a gallery application.

[0108] According to one embodiment, a profile may include the relationship between an object within an image or a shared counterpart and the electronic device user. According to one embodiment, a preference may include information such as the user's affinity for a specific person or object, specific events, places, people, activities, or environments preferred by the user. According to one embodiment, a context may include information such as the location where the image was taken, analyzed behavior, or regularity. According to one embodiment, an activity may include activity-related information such as travel or exercise.

[0109] According to one embodiment, the data platform (510) can generate personalized data by utilizing various types of data stored in the electronic device (e.g., application data (522), usage data (524), or system data (526)). For example, the data platform (510) can check call records obtained from a call application among the application data (522) and confirm that there are many records of sending and receiving calls / messages with a specific person, and if there are many photos taken with that person among the images in the gallery application, it can determine that the user of the electronic device and that person have a high level of intimacy. For example, the data platform (510) can check information such as the user of the electronic device's exercise tendencies or sleep patterns through a health application, and from this, determine that the user of the electronic device has a tendency to like outdoor activities at night. For example, if the user of the electronic device shares an image (or image story) of exercising at night with friend A, who is analyzed as having a high level of intimacy, the platform can trigger the creation of an image story containing images similar to that image, and / or recommend friend A as the recipient of the created image story. For example, the electronic device can recommend friend B, identified as having a high level of intimacy based on personalized data, as a target for sharing image stories.

[0110] According to one embodiment, the generated personalized data (530) may be transmitted to a story generation judgment module (540), a story generation module (550), and / or a story analysis module (560).

[0111] According to one embodiment, the story creation determination module (540) may determine the creation of an image story including at least one image (e.g., a first image) and corresponding images (e.g., a second image) based on personalization data (530). According to one embodiment, the story creation determination module (540) may trigger the creation of an image story including images that have high association or similarity with at least one image based on the sharing history to other devices or image story creation history of images identified in a gallery application. The story creation determination module (540) may obtain data related to the sharing history or story creation history of images from data stored in memory (e.g., usage data (524), application data (522), or system data (526)), and through the analysis of the obtained data, determine (or guess) whether the user intends to create an image story including images associated with (or similar to) a specific image. For example, if a user of an electronic device has a history of sharing items purchased at a department store with friends through an SNS application, the electronic device can trigger the creation of an image story using images associated with specific shared images.

[0112] According to one embodiment, the story generation module (550) can generate an image story including images. According to one embodiment, when the story generation module (550) determines the generation of an image story by the story generation determination module (540), it can identify images among the images stored in memory that have high similarity or association with at least one first image included in the shared history. For example, the story generation module (550) can analyze the images stored in memory, categorize them using personalized data (530) such as profile, preference, context, or activity, and select images belonging to the same category as the first image. For example, if at least one image taken with family members is determined as the first image based on the image sharing history, images taken with family members can be selected as the second image based on object analysis of the stored images or analysis of metadata. Alternatively, if at least one image of an item purchased at a department store is determined as the first image based on the sharing history of the image, an item of the same type (e.g., a bag), an item purchased at the same place (e.g., a department store), or an item purchased on the same date as the item purchased in the first image may be selected as the second image based on object analysis of the stored images or analysis of metadata. For example, if at least one image of an item taken during nighttime exercise is determined as the first image based on application data, an image taken outdoors at night and / or an image of exercise equipment or an exercise scene may be selected as the second image based on object analysis of the stored images or analysis of metadata.

[0113] According to one embodiment, the story generation module (550) can generate an image story including selected second images. For example, the story generation module (550) can generate an image story in the form of a video or slide using the selected images.

[0114] According to one embodiment, the story generation module (550) may assign weights to at least some of the second images included in the image story and determine playback attributes (e.g., playback time, area to crop, or focusing) for each of the second images based on the assigned weights.

[0115] According to one embodiment, the story analysis module (560) can analyze the generated image stories. The story analysis module (560) can analyze the content of the images or videos included in the image stories and analyze information related to the sharing of the generated image stories (e.g., sending to other users, or uploading to social media).

[0116] FIG. 6 is a flowchart of an image story generation method according to one embodiment.

[0117] According to one embodiment, the illustrated method may be performed by an electronic device (e.g., the electronic device (300) of FIG. 3), and the technical features described above may be omitted from the description below.

[0118] According to one embodiment, in operation 610, the electronic device can analyze the history of image sharing and story creation. According to one embodiment, the electronic device can identify the history of sharing of an image (or image story) or the history of creating an image story based on the analysis of data stored in memory. The electronic device can analyze the history of sharing of an image or image story based on the data stored in memory. For example, the electronic device can analyze application data, usage data, and system data stored in memory, and identify images preferred by the user for sharing or creating image stories based on personal data such as profiles, preferences, contexts, or activities identified as a result of the analysis. According to one embodiment, the operation of analyzing data and / or the operation of creating personal data may be performed during the process of creating an image story, or may be performed prior to the creation of an image story.

[0119] According to one embodiment, an electronic device may determine the creation of an image story comprising at least one image (e.g., a second image) corresponding to at least one image (e.g., a first image) included in the sharing history, based on the sharing history of at least one image or image story to another device or the story creation history. For example, the electronic device may identify common features of images frequently shared by a user based on the sharing history of the user's images, and trigger the creation of an image story comprising images similar to the frequently shared images.

[0120] According to one embodiment, an electronic device may generate first analysis information associated with a first image. For example, a processor may generate analysis information by analyzing a specific image that has a history of sharing or creating an image story, and determining attributes of the image such as a target, object, region of interest, mood, or tag. The electronic device may generate first analysis information based on at least one of a profile, preference, context, or activity associated with a user. The electronic device may generate first analysis information of the first image using an AI model.

[0121] According to one embodiment, the electronic device can identify information related to the sharing of the first image, such as a sharing target like an external electronic device or a specific recipient, or a sharing application like a blog or social media. Based on the object or image tag information included in each of the first images, the electronic device can generate first analysis information including information such as the relationship or intimacy between the person included in the image and the user, events identified in the image, the shooting location, the behavior or regularity of the person, and activities being performed. Alternatively, the electronic device can identify information related to interest when the user expresses interest (e.g., likes) in other users' social media or stories using the electronic device (300). The electronic device can determine which category the image belongs to for at least one of a profile, preference, context, or activity.

[0122] According to one embodiment, in operation 620, the electronic device can analyze images stored in a gallery. Based on object analysis of the stored images or analysis of tag information, the electronic device can categorize at least one of profile, preference, context, or activity.

[0123] According to one embodiment, in operation 630, the electronic device can identify images of similarity based on the analysis results. According to one embodiment, the electronic device can select at least one image as a second image having second analysis information corresponding to first analysis information generated by analyzing object analysis or metadata of at least one first image included in the shared history. For example, if the first image is a photograph of the electronic device's user A and friend B together, the electronic device can analyze the first image to identify user A and friend B and determine the situation within the first image. The electronic device can select at least one second image associated with the first image by using personalized data such as various sensor information (e.g., shooting location, time, or weather), contact patterns of user A and friend B via calls, messages, or SNS, and / or analysis of other images other than the first image.

[0124] According to one embodiment, the electronic device analyzes application data, usage data, and system data stored in memory, and based on personal data such as profiles, preferences, contexts, or activities identified as a result of the analysis, selects at least one second image that is similar to (or associated with) a first image among images stored in a gallery.

[0125] According to one embodiment, an electronic device can verify the similarity between each image stored in memory and a first image through an AI model. The electronic device can select at least one second image that belongs to the same category as the first image among the images stored in memory.

[0126] According to one embodiment, in operation 640, the electronic device may generate an image story using similar images. For example, the electronic device may generate an image story including a first image and second images associated with the first image among images of a shared history that trigger the generation of the image story, or may generate an image story including only the second images.

[0127] According to one embodiment, the electronic device may assign weights to at least some of the second images included in an image story and determine playback attributes (e.g., playback time of the image, playback order, area to be cropped, or focusing) for each of the second images based on the assigned weights. For example, if the electronic device confirms that a user frequently shares images of items purchased at a department store when uploading to social media, it may extend the playback time of the image of the purchased item in the image story containing photos taken at the department store, adjust the playback order so that it is played at the beginning, provide a cropped area of ​​the purchased item, or focus.

[0128] According to one embodiment, the electronic device determines a recommended application or a recommended recipient for sharing an image story, and can determine playback attributes based on the determined recommended application or recommended recipient. For example, in the case of an image story intended for uploading to a blog, the electronic device may determine that users tend to upload content related to their daily lives when uploading to a blog and set the playback attributes of each image to be the same. Alternatively, in the case of an image story intended for uploading to social media, the electronic device may determine that users tend to upload content related to purchased items when uploading to social media and set the playback time of images of purchased items to be longer or focus on the area of ​​the purchased items.

[0129] According to one embodiment, in operation 650, the electronic device may display the generated image story along with sharing recommendation information. For example, the electronic device may display an item corresponding to an application to upload the generated image story (e.g., social media, or a blog) or an item corresponding to a sharing method (e.g., sharing with a wife, or uploading to social media) on at least a portion of the image story. If it is determined that the user has a tendency to upload images including the first image through a social media application, the electronic device may display an item corresponding to a social media application overlapping with or adjacent to at least a portion of the thumbnail of the generated image story. The display location and / or method of displaying the item corresponding to the thumbnail of the image story is not limited thereto. For example, the item corresponding to a social media application may include an icon stored for the social media application, an icon regenerated based thereon, and / or text. The electronic device may provide a share button for the image story and may share the image story using a shared recommended application based on user input to the share button.

[0130] According to one embodiment, instructions for performing each operation included in the method may be stored on a computer-readable recording medium. The recording medium may be tangible and non-transitory. The recording medium may store one or more computer programs containing said instructions.

[0131] FIG. 7 illustrates the screens of an SNS application and a gallery application according to one embodiment.

[0132] Referring to Fig. 7(a), the electronic device (300) (e.g., the electronic device (300) of Fig. 3) can check the history of the user uploading images A (701), B (702), C (703), and D (704) at once or sequentially through an SNS application.

[0133] According to one embodiment, the electronic device (300) can identify common characteristics of images frequently shared by a user based on object analysis or tag information analysis of images uploaded by the user through an SNS application. For example, the electronic device (300) can identify a tendency for the user to upload at least some of the photos taken (e.g., photos of items purchased at the department store) through SNS when the user visits a department store to prepare for a trip, or takes various photos during the process of preparing before visiting the department store or organizing after visiting the department store. In this case, the electronic device (300) can trigger the creation of an image story containing images similar to the shared images based on the sharing history of the images. According to one embodiment, the electronic device can determine at least one of the images frequently shared by the user as a first image, and select images similar to the first image from among the images stored in memory to determine as second images to be included in the image story.

[0134] According to one embodiment, when a user selects a menu to create an image story through a gallery application, the electronic device (300) may provide information associated with an image, video, or image story that has a confirmed sharing history. For example, in the case of an image that has a sharing history through a specific application on the gallery application screen, the electronic device (300) may display an item indicating the application used for sharing in at least a portion of the image.

[0135] Referring to FIG. 7(b), the gallery application can display images 1 through 15 stored in memory. The electronic device (300) can verify that images 1 (711), 3 (713), 4 (714), and 5 (715) have been shared through an SNS application. In this case, the electronic device (300) can display items (721, 723, 724, 725) indicating an SNS application on at least a portion of images 1 (711), 3 (713), 4 (714), and 5 (715).

[0136] FIG. 8 illustrates a method for selecting images to be included in an image story among images of a gallery application according to one embodiment.

[0137] According to one embodiment, an electronic device (e.g., the electronic device (300) of FIG. 3) may determine the creation of an image story including at least one image based on a history of sharing to another device or a history of creating a story of at least one image or image story. Based on the history of sharing, the electronic device may determine at least one image among the shared images as a first image. The electronic device may generate first analysis information associated with the first image, analyze images stored in memory, select at least one second image having second analysis information corresponding to the first analysis information, and create an image story including at least one second image.

[0138] Referring to FIG. 8(a), a gallery application (800) can display images 1 to 15 (801 to 815) among images stored in memory. An electronic device can determine the category to which each image belongs by analyzing objects within the images and tag information of the stored images including images 1 to 15 (801 to 815). According to one embodiment, the electronic device can determine the category to which each image belongs by using an AI model (e.g., the generative AI model (450) of FIG. 4).

[0139] Referring to FIG. 8(b), the electronic device can classify images 1 (801), 3 (803), 4 (804), 5 (805), 6 (806), 7 (807), and 8 (808) as images taken at Department Store A based on object analysis or analysis of tag information (e.g., date of capture, or location), images 2 (802), 9 (809), and 10 (810) as screen capture images related to Department Store A, images 11 (811), 12 (812), and 13 (813) as images taken at the bookstore of Department Store A, and images 14 and 15 as images of products purchased at Department Store A taken at home.

[0140] According to one embodiment, an electronic device may select at least one second image that has similarity or association with a first image determined based on an image sharing history or an image story creation history. For example, based on an image sharing history, the electronic device may determine an image of an item purchased at Department Store A as the first image, and subsequently determine images taken at Department Store A on a specific date as the second image.

[0141] Referring to FIG. 8(c), the electronic device may recognize Image 1 (801), Image 14 (814), Image 5 (805), Image 3 (803), and Image 4 (804), which were taken at Department Store A on the same date among Images 1 to 15 (801 to 815), as images that have similarity or association with a first image that has a previously shared history. Alternatively, if the first image that triggers the creation of an image story belongs to the category of images taken at Department Store A, the electronic device may select at least one of Image 1 (801), Image 3 (803), Image 4 (804), Image 5 (805), Image 6 (806), Image 7 (807), and Image 8 (808), which are classified as images taken at Department Store A among Images 1 to 15 (801 to 815), as a second image. Alternatively, if the first image belongs to the category of images of products purchased at Department Store A taken at home, at least one of images 14 (814) and 15 (815) classified as images of products purchased at Department Store A taken at home can be selected as the second image.

[0142] According to one embodiment, the electronic device may generate an image story comprising selected second images (e.g., Image 1 (801), Image 14 (814), Image 5 (805), Image 3 (803), and Image 4 (804) of FIG. 8 (c)). Alternatively, the electronic device may display the selected second images separately from other images and provide information to guide the user in generating the image story.

[0143] FIG. 9 illustrates a generated image story according to one embodiment.

[0144] According to one embodiment, the electronic device (300) can generate an image story using selected second images and display the generated image story through a display. Referring to FIG. 9, the electronic device (300) may have generated image story 1 (932), image story 2 (934), and image story 3 (940). When a user selects a story item (920) displayed at the bottom of the gallery application (900) screen, the electronic device (300) can display thumbnails of the generated image stories (932, 934, 940).

[0145] According to one embodiment, the electronic device (300) may generate a thumbnail based on a representative image of any one of the images included in the image story and display a title of the image story (e.g., pleasant weekend shopping) (942) based on an object, tag, or user input of the image. Referring to FIG. 9, the image story 3 (940) may include image 1 (901), image 14 (914), image 5 (905), image 3 (903), and image 4 (904). The electronic device (300) may select image 14 (914) as the representative image (944) of the image story 3 (940) and display it along with the title "pleasant weekend shopping" (942).

[0146] According to one embodiment, the electronic device (300) determines a recommended application or a recommended counterpart for sharing an image story, and can display an item (950) indicating the recommended application or the recommended counterpart along with the image story. For example, a user of the electronic device may visit a department store to prepare for a trip, take various photos during the process of preparing before visiting the department store and organizing after visiting, and share at least some of the photos taken through an SNS application. Based on such image sharing history, the electronic device can generate an image story by selecting at least one image (e.g., a second image) having analysis information corresponding to at least one shared image (e.g., a first image) among the images in the gallery application according to metadata or object recognition.

[0147] Referring to FIG. 9, the images included in the generated image story 3 (940) may include images taken at a department store that has a history of sharing images previously taken at the department store. Based on the sharing history, the electronic device (300) can identify the tendency of a user to share images taken at a department store through an SNS application and determine the target of sharing for image story 3 (940) to be an SNS application. In this case, the electronic device (300) may display an item (950) indicating an SNS application overlapping or adjacent to a part of image story 3 (940). When the item (950) indicating an SNS application is selected according to user input, the electronic device (300) may provide a user interface that can execute an SNS application and upload image story 3 (940).

[0148] FIG. 10 illustrates a method for determining the attributes of an image story according to an application that shares the image story according to one embodiment.

[0149] According to one embodiment, an electronic device (e.g., the electronic device (300) of FIG. 3) may determine the attributes of an image story based on an application (or method of sharing, purpose of sharing) to share the image story. Here, the attributes of the image story may include the playback order, playback time, area to crop, or focusing of each image. For example, the electronic device may determine the images to be included in the image story and determine the playback order, playback time, area to crop, or focusing of each image, reflecting the user's intent, according to an application (e.g., a blog, or social media) that provides the sharing of the image story.

[0150] Referring to FIG. 10 (a), the electronic device can generate an image story (1010) for the purpose of uploading to a blog. The electronic device can determine that the user tends to upload content related to daily life (e.g., images, videos, or text) when uploading to a blog based on personal data (e.g., profile, preferences, context, or activity) generated by analyzing data stored in memory (e.g., application data, usage data, or system data).

[0151] According to one embodiment, the electronic device can identify related images related to daily life among the images of a gallery application and generate an image story (1010) including the identified images. According to one embodiment, for an image story (1010) intended for uploading to a blog, the electronic device can set the playback speed of each image to be substantially the same and / or set each image to its original size without focusing.

[0152] According to one embodiment, the electronic device may display an item (1020) indicating a blog on a screen of images included in an image story (1010) or on a thumbnail of a generated image story. The electronic device may provide a user interface that can execute a blog application and upload a generated image story in response to the selection of the item (1020).

[0153] Referring to FIG. 10 (b), the electronic device can generate an image story (1060) for the purpose of uploading to a social network service (SNS). Based on personalized data, the electronic device can determine that the user tends to upload content related to items purchased when uploading to SNS.

[0154] According to one embodiment, the electronic device can identify related images among the images of a gallery application that are related to a purchased item and generate an image story (1060) containing the identified images. According to one embodiment, for an image story (1060) intended for uploading to social media, the electronic device can set a longer playback time for some of the purchased items (e.g., items preferred by the user or a social media friend) and / or focus on an area of ​​the purchased item in a specific image. Referring to FIG. 10 (b), images 14 (1014) and 5 (1005) are determined to be highly related to the first image, and thus a longer playback time can be set compared to images 1 (1001), 2 (1002), and 3 (1003).

[0155] According to one embodiment, the electronic device may crop and display a major object in image 14 (1014) and image 5 (1005) that are highly relevant to the first image, or focus and display an area of ​​the major object. According to one embodiment, the electronic device may set the playback order so that the highly relevant image is played first based on its relevance to the first image.

[0156] According to one embodiment, the electronic device may display an item (1070) indicating SNS on a screen of images included in an image story (1060) or on a thumbnail of a generated image story. The electronic device may provide a user interface that can execute an SNS application and upload the generated image story (1060) in response to the selection of the item (1020).

[0157] FIG. 11 illustrates a method for determining the attributes of an image story according to a counterpart to whom the image story will be shared, according to one embodiment.

[0158] According to one embodiment, an electronic device (e.g., the electronic device (300) of FIG. 3) may determine the attributes of an image story based on the target (or counterpart) to whom the image story will be shared. Here, the attributes of the image story may include the playback order of each image, playback time, area to be cropped, or focusing. According to one embodiment, the electronic device may use generative AI to regenerate (or correct) images for at least some of the images in the image story and include them in the image story.

[0159] According to one embodiment, an electronic device can determine the relationship between a user's sharing target (or sharing partner) based on the user's personal data (e.g., profile, preference, context, or activity) generated by analyzing data stored in memory (e.g., application data, usage data, or system data), and determine the playback order, playback time, and / or focusing of an image story therefrom.

[0160] Referring to FIG. 11, the electronic device can generate an image story containing images taken at a department store based on a previous image sharing history. The electronic device can generate image stories with different attributes corresponding to the sharing partners.

[0161] Referring to FIG. 11 (a), the electronic device can generate an image story to share with the wife. In one embodiment, the electronic device may, based on the relationship with the wife who is the target of sharing, set the playback time of each image (1111, 1112, 113, 1114, 1115) included in the image story to be the same, and / or set each image (1111, 1112, 113, 1114, 1115, 1116) to its original size without focusing. For example, based on the history of sharing images or image stories with the wife, the electronic device may identify that various types of images taken in daily life are shared with the wife and generate an image story by assigning the same playback attributes without applying weights to specific images.

[0162] Referring to FIG. 11 (b), if the target of sharing the image story is the parents, the electronic device may assign weight to a photo (1114) of a baby that is of high interest to the parents, thereby setting a longer playback time or / or focusing on the area in the image where the baby appears. Alternatively, the electronic device may determine the attributes of the image story based on the number of times the image is shared with a specific target or common interests identified through transmitted and received messages. For example, the electronic device may determine the baby photo as a common interest between the electronic device user and the parents if there is a history of frequently sharing photos of the baby with the parents or if there is a lot of baby-related content in the transmitted and received messages.

[0163] Referring to FIG. 11 (b), the electronic device can generate an image story to be shared with an unspecified number of people via social media. In this case, the electronic device can set a higher weight for specific images based on the user's personal data. For example, if the electronic device determines, based on personal data, that the user tends to upload photos of purchased items to the relevant social media, it can set a higher weight for images (1113, 1115) containing photos of purchased items. The electronic device can set a longer playback time for images with high weights, and / or focus on the area of ​​the purchased items in specific images.

[0164] Referring to FIG. 11 (b), the electronic device can generate an image story containing five images (1111, 1112, 1113, 1114, 1115), and can set the playback time of the third image (1113) and the fifth image (1115), which have high weights due to their high relevance to images frequently shared on social media, to be long, and the playback time of the first, second, and fourth images (1111, 1112, 1114), which have low weights, to be relatively short.

[0165] According to one embodiment, the electronic device can set playback attributes such as playback time, playback order, and / or focusing based on the weight of each of the images (1111, 1112, 1113, 1114, 1115) included in the image story.

[0166] FIG. 12 illustrates a screen showing images to be shared in a gallery application according to one embodiment, visually distinguished.

[0167] According to one embodiment, an electronic device may provide information guiding the creation of an image story based on personalized data (e.g., profile, preference, context, or activity). For example, the electronic device may trigger the creation of an image story based on an image sharing history or an image story creation history and automatically create an image story. Alternatively, the electronic device may allow a user to manually select images to create an image story. In the case of such manual creation, the electronic device may identify the images expected to be included in the image story and provide information guiding the creation of the image story.

[0168] Referring to FIG. 12, images 1 to 15 (1201 to 1215) may be displayed on a gallery application (1290). The electronic device may determine, based on the analysis of personalized data, that the user intends to create an image story including images 1 (1201), 14 (1214), 5 (1205), 3 (1203), and 4 (1204). For example, the electronic device may determine, based on the analysis of image sharing history, that the user frequently uploads photos taken at a department store to social media, and that the user intends to create an image story including images 1 (1201), 14 (1214), 5 (1205), 3 (1203), and 4 (1204) corresponding to photos taken at a department store.

[0169] According to one embodiment, to guide the creation of an image story, the electronic device may display images expected to be included in the image story (e.g., Image 1 (1201), Image 14 (1214), Image 5 (1205), Image 3 (1203), and Image 4 (1204)) (1270) so as to be visually distinguished from other images. For example, the electronic device may provide visual effects such as borders, separators, changes in background color, shadow effects, or enlargement.

[0170] According to one embodiment, the electronic device may display an item (1275) indicating an application where the image story is expected to be shared in order to guide the creation of the image story. Referring to FIG. 12, as the electronic device is expected to upload the image story to a social media platform, it may display an item (1275) indicating a social media platform along with images expected to be included in the image story (e.g., Image 1 (1201), Image 14 (1214), Image 5 (1205), Image 3 (1203), and Image 4 (1204)) (1270).

[0171] FIG. 13 illustrates a screen that allows selecting an image to be shared in a gallery application according to one embodiment.

[0172] According to one embodiment, an electronic device (e.g., the electronic device (300) of FIG. 3) may provide a sharing recommendation method when selecting an image to share on a gallery application screen. For example, the electronic device may identify a sharing method (e.g., an application) and / or a sharing target for each image based on personalized data, and display an item indicating the identified sharing method and / or sharing target associated with the image.

[0173] Referring to FIG. 13, the electronic device can determine, based on the analysis of personalized data, that the user frequently uploads items purchased at a department store to social media, and can determine that an image F (1310) or image J (1320) of the purchased items is a target for uploading to social media. In this case, the electronic device can display an item (1315, 1325) that directs a social media application to image F (1310) or image J (1320).

[0174] For example, the electronic device may determine, based on the analysis of personalized data, that image G (1330) or image H (1340) is to be uploaded to a blog. In this case, the electronic device may display an item (1335, 1345) directing the blog for image G (1330) or image H (1340).

[0175] According to one embodiment, when at least one image (e.g., image F (1310), or image J (1320)) is selected by touch input, the electronic device may upload the selected image using an application (e.g., a social media application) corresponding to the selected image, or create and upload an image story containing the selected images.

[0176] An electronic device according to various embodiments of the present document (e.g., the electronic device (101) of FIG. 1, the electronic device (200) of FIG. 2, and the electronic device (300) of FIG. 3) may include a display (330), a memory (320), and at least one processor (310).

[0177] According to one embodiment, the memory (320) can be executed individually or collectively by at least one processor (310) and can store instructions that, at execution, cause the electronic device (e.g., electronic device (101) of FIG. 1, electronic device (200) of FIG. 2, electronic device (300) of FIG. 3) to determine the creation of an image story containing at least one image corresponding to the first image based on the sharing history to other devices of an image or an image story containing at least one image (e.g., image story (240) of FIG. 2, image story (1010) of FIG. 10, image story (1060) of FIG. 10) and / or the creation history of the image story.

[0178] According to one embodiment, the memory (320) may store instructions that cause the electronic device (e.g., electronic device (101) of FIG. 1, electronic device (200) of FIG. 2, electronic device (300) of FIG. 3) to generate first analysis information associated with the first image, analyze images stored in the memory, select at least one second image having second analysis information corresponding to the first analysis information, and generate an image story (e.g., image story (240) of FIG. 2, image story (1010) of FIG. 10, image story (1060)) including the at least one second image.

[0179] According to one embodiment, the memory (320) may store instructions that cause the electronic device (e.g., the electronic device (101) of FIG. 1, the electronic device (200) of FIG. 2, the electronic device (300) of FIG. 3) to generate the first analysis information based on at least some of the application data (522), usage data (524), and system data (526) stored in the memory (320).

[0180] According to one embodiment, the memory (320) may store instructions that cause the electronic device (e.g., the electronic device (101) of FIG. 1, the electronic device (200) of FIG. 2, the electronic device (300) of FIG. 3) to generate the first analysis information based on at least one of a profile, preference, context, or activity associated with the user of the electronic device.

[0181] According to one embodiment, the memory (320) may store instructions that cause the electronic device (e.g., the electronic device (101) of FIG. 1, the electronic device (200) of FIG. 2, the electronic device (300) of FIG. 3) to select at least one second image having the second analysis information among the images based on an analysis of an object or metadata included in the images stored in the memory.

[0182] According to one embodiment, the first analysis information includes a category to which the first image belongs, and the memory (320) may store instructions that allow the electronic device (e.g., the electronic device (101) of FIG. 1, the electronic device (200) of FIG. 2, the electronic device (300) of FIG. 3) to select at least one second image that belongs to the same category as the first image among the images stored in the memory.

[0183] According to one embodiment, the memory (320) may store instructions that allow the electronic device (e.g., the electronic device (101) of FIG. 1, the electronic device (200) of FIG. 2, the electronic device (300) of FIG. 3) to select at least one second image having the second analysis information among the images stored in the memory using an AI model (450).

[0184] According to one embodiment, the memory (320) may store instructions that cause the electronic device (e.g., the electronic device (101) of FIG. 1, the electronic device (200) of FIG. 2, the electronic device (300) of FIG. 3) to display on the display an item indicating an application for sharing the generated image story (1060) or a sharing partner.

[0185] According to one embodiment, the memory (320) may store instructions that allow the electronic device (e.g., the electronic device (101) of FIG. 1, the electronic device (200) of FIG. 2, the electronic device (300) of FIG. 3) to determine an application or a sharing partner for sharing the generated image story (1060) based on the sharing history of the image or image story and / or the creation history of the image story.

[0186] According to one embodiment, the memory (320) may store instructions that cause the electronic device (e.g., electronic device (101) of FIG. 1, electronic device (200) of FIG. 2, electronic device (300) of FIG. 3) to determine playback attributes for at least some of the second images constituting the image story (e.g., image story (240) of FIG. 2, image story (1010) of FIG. 10, image story (1060) of FIG. 10).

[0187] According to one embodiment, the memory (320) may store instructions that cause the electronic device (e.g., electronic device (101) of FIG. 1, electronic device (200) of FIG. 2, electronic device (300) of FIG. 3) to determine a recommended application or recommended counterpart for sharing the image story (e.g., image story (240) of FIG. 2, image story (1010) of FIG. 10, image story (1060) of FIG. 10), and to determine the playback attribute based on the determined recommended application or recommended counterpart.

[0188] According to one embodiment, the playback attribute may include at least one of a playback speed or focusing for playing the image story.

[0189] A method performed by an electronic device according to various embodiments of the present document may include, based on a sharing history to another device of an image or an image story (e.g., image story (240) of FIG. 2, image story (1010) of FIG. 10, image story (1060) of FIG. 10) containing at least one image and / or a creation history of an image story, an operation of determining the creation of an image story (e.g., image story (240) of FIG. 2, image story (1010) of FIG. 10, image story (1060) of FIG. 10) containing at least one image corresponding to a first image, an operation of creating first analysis information associated with the first image, an operation of analyzing images stored in the electronic device to select at least one second image having second analysis information corresponding to the first analysis information, and an operation of creating an image story (e.g., image story (240) of FIG. 2, image story (1010) of FIG. 10, image story (1060) of FIG. 10) containing at least one second image.

[0190] According to one embodiment, the operation of generating the first analysis information may include the operation of generating the first analysis information based on at least a portion of application data (522), usage data (524), and system data (526) stored in the electronic device (e.g., electronic device (101) of FIG. 1, electronic device (200) of FIG. 2, electronic device (300) of FIG. 3).

[0191] According to one embodiment, the operation of generating the first analysis information may include the operation of generating the first analysis information based on at least one of a profile, preference, context, or activity associated with a user of the electronic device (e.g., electronic device (101) of FIG. 1, electronic device (200) of FIG. 2, electronic device (300) of FIG. 3).

[0192] According to one embodiment, the operation of selecting at least one second image may include the operation of selecting at least one second image having the second analysis information among the images based on the analysis of an object or metadata included in the images stored in the memory (320).

[0193] According to one embodiment, the first analysis information includes a category to which the first image belongs, and the operation of selecting at least one second image may include selecting at least one second image that belongs to the same category as the first image among the images stored in the memory (320).

[0194] According to one embodiment, the operation of selecting at least one second image may include the operation of selecting at least one second image having the second analysis information among the images stored in the memory (320) using an AI model.

[0195] According to one embodiment, the method may further include the operation of displaying on the display (330) an item indicating an application for sharing the generated image story (1060) or a sharing partner.

[0196] According to one embodiment, the method may further include an operation to determine playback attributes for at least some of the second images constituting the image story (e.g., image story of FIG. 2 (240), image story of FIG. 10 (1010), image story of FIG. 10 (1060)).

[0197] According to one embodiment, the method may further include the operation of determining a recommended application or recommended counterpart for sharing the image story (e.g., image story of FIG. 2 (240), image story of FIG. 10 (1010), image story of FIG. 10 (1060)), and determining the playback attribute based on the determined recommended application or recommended counterpart.

[0198] A computer-readable non-transient recording medium according to various embodiments of the present document may store instructions for performing the following operations: determining the creation of an image story containing at least one image corresponding to a first image based on a history of sharing to another device of an image or at least one image (e.g., image story of FIG. 2 (240), image story of FIG. 10 (1010), image story of FIG. 10 (1060)) and / or a history of creating an image story; creating first analysis information associated with the first image; analyzing images stored in the electronic device (e.g., electronic device of FIG. 1 (101), electronic device of FIG. 2 (200), electronic device of FIG. 3 (300)) to select at least one second image having second analysis information corresponding to the first analysis information; and creating an image story containing at least one second image.

[0199] The electronic device according to the various embodiments disclosed in this document may be of various forms. The electronic device may include, for example, a portable communication device (e.g., a smartphone), a computer device, a portable multimedia device, a portable medical device, a camera, a wearable device, or a consumer electronics device. The electronic device according to the embodiments of this document is not limited to the devices described above.

[0200] The various embodiments of this document and the terms used therein are not intended to limit the technical features described in this document to specific embodiments, and should be understood to include various modifications, equivalents, or substitutions of said embodiments. In connection with the description of the drawings, similar reference numerals may be used for similar or related components. The singular form of a noun corresponding to an item may include one or more of said items unless the relevant context clearly indicates otherwise. In this document, phrases such as "A or B," "at least one of A and B," "at least one of A or B," "A, B or C," "at least one of A, B and C," and "at least one of A, B, or C" may each include any one of the items listed together in the corresponding phrase, or all possible combinations thereof. Terms such as "first," "second," or "first" or "second" may be used simply to distinguish said components from other said components and do not limit said components in any other aspect (e.g., importance or order). Where any (e.g., 1st) component is referred to as “coupled” or “connected” to another (e.g., 2nd) component, with or without the terms “functionally” or “communicationly,” it means that said any component may be connected to said other component directly (e.g., via a wire), wirelessly, or through a third component.

[0201] The term “module” as used in the various embodiments of this document may include a unit implemented in hardware, software, or firmware, and may be used interchangeably with terms such as logic, logic block, component, or circuit, for example. A module may be a component formed integrally, or a minimum unit of said component or a part thereof that performs one or more functions. For example, according to one embodiment, a module may be implemented in the form of an application-specific integrated circuit (ASIC).

[0202] Various embodiments of the present document may be implemented as software (e.g., program (140)) comprising one or more instructions stored in a storage medium (e.g., internal memory (136) or external memory (138)) readable by a machine (e.g., electronic device (101)). For example, a processor (e.g., processor (120)) of the machine (e.g., electronic device (101)) may call at least one of the one or more instructions stored in the storage medium and execute it. This enables the machine to be operated to perform at least one function according to the at least one called instruction. The one or more instructions may include code generated by a compiler or code that can be executed by an interpreter. The storage medium readable by the machine may be provided in the form of a non-transitory storage medium. Here, 'non-temporary' simply means that the storage medium is a tangible device and does not contain a signal (e.g., electromagnetic waves), and the term does not distinguish between cases where data is stored semi-permanently and cases where it is stored temporarily.

[0203] According to one embodiment, the method according to the various embodiments disclosed herein may be provided by being included in a computer program product. The computer program product may be traded between a seller and a buyer as a product. The computer program product may be distributed in the form of a device-readable storage medium (e.g., compact disc read-only memory (CD-ROM)) or an application store (e.g., Play Store). TM It can be distributed online (e.g., downloaded or uploaded) through ) or directly between two user devices (e.g., smartphones). In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily created on a device-readable storage medium, such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0204] According to various embodiments, each component (e.g., module or program) of the components described above may include a singular or multiple entities, and some of the multiple entities may be separated and placed in other components. According to various embodiments, one or more of the components or operations of the aforementioned components may be omitted, or one or more other components or operations may be added. Generally or additionally, multiple components (e.g., module or program) may be integrated into a single component. In this case, the integrated component may perform one or more functions of each of the multiple components in the same or similar manner as those performed by the corresponding component among the multiple components prior to integration. According to various embodiments, operations performed by the module, program, or other components may be executed sequentially, in parallel, iteratively, or heuristically, or one or more of the operations may be executed in a different order, omitted, or one or more other operations may be added.

Claims

1. In an electronic device, display; Memory; and It includes at least one processor, The above memory can be executed individually or collectively by at least one processor, and at the time of execution, the electronic device, Based on the sharing history to another device of an image story including an image or at least one image and / or the creation history of the image story, the creation of an image story including at least one image corresponding to the first image is determined, and Generates first analysis information associated with the above first image, and By analyzing the images stored in the memory, at least one second image having second analysis information corresponding to the first analysis information is selected, and An electronic device that stores instructions for generating an image story including at least one second image.

2. In Paragraph 1, The above memory is, the electronic device, An electronic device that stores instructions for generating the first analysis information based on at least a portion of the application data, usage data, and system data stored in the memory.

3. In Paragraph 1 or 2, The above memory is, the electronic device, An electronic device that stores instructions for generating the first analysis information based on at least one of a profile, preference, context, or activity associated with a user of the electronic device.

4. In any one of paragraphs 1 to 3, The above memory is, the electronic device, An electronic device storing instructions for selecting at least one second image having the second analysis information among the images, based on an analysis of an object or metadata included in the images stored in the memory.

5. In any one of paragraphs 1 through 4, The above first analysis information includes the category to which the above first image belongs, and The above memory is, the electronic device, An electronic device that stores instructions for selecting at least one second image belonging to the same category as the first image among the images stored in the memory.

6. In any one of paragraphs 1 through 5, The above memory is, the electronic device, An electronic device that stores instructions for selecting at least one second image having the second analysis information among the images stored in the memory using an AI model.

7. In any one of paragraphs 1 through 6, The above memory is, the electronic device, An electronic device that stores instructions for displaying on the display an item indicating an application for sharing the generated image story or a sharing partner.

8. In Paragraph 7, The above memory is, the electronic device, An electronic device that stores instructions for determining an application or a sharing partner for sharing the generated image story based on the sharing history of the image or image story and / or the creation history of the image story.

9. In Paragraph 7 or Paragraph 8, The above memory is, the electronic device, An electronic device that stores instructions for determining playback properties for at least some of the second images constituting the above image story.

10. In Paragraph 7 or 8, The above memory is, the electronic device, An electronic device that stores instructions for determining a recommended application or recommended counterpart for sharing the above image story, and determining the playback attribute based on the determined recommended application or recommended counterpart.

11. In any one of paragraphs 7 through 10, The above playback attribute is an electronic device comprising at least one of a playback speed or focusing for playing the image story.

12. In a method performed by an electronic device, An operation to determine the creation of an image story including at least one image corresponding to a first image based on the sharing history to another device of an image story including an image or at least one image and / or the creation history of the image story; The operation of generating first analysis information associated with the first image above; The operation of analyzing images stored in the electronic device and selecting at least one second image having second analysis information corresponding to the first analysis information; and A method comprising the operation of generating an image story including at least one second image.

13. In Paragraph 12, The operation of generating first analysis information is, A method comprising the operation of generating the first analysis information based on at least one of a profile, preference, context, or activity related to a user of the electronic device.

14. In Paragraph 12, A method further comprising the operation of displaying on the display of the electronic device an item indicating an application for sharing the generated image story or a sharing partner.

15. In a computer-readable non-transient recording medium, An operation to determine the creation of an image story including at least one image corresponding to a first image based on the sharing history to another device of an image story including an image or at least one image and / or the creation history of the image story; The operation of generating first analysis information associated with the first image above; The operation of analyzing images stored in the electronic device and selecting at least one second image having second analysis information corresponding to the first analysis information; and A recording medium storing instructions for performing an operation to generate an image story including at least one second image.

Images