Method, device, non-transitory computer-readable storage medium for outputting slide show by using activity information about user

Abstract

An electronic device according to an embodiment comprises: a display; at least one processor including processing circuitry; and a memory including one or more storage media storing instructions. The instructions, when executed by the at least one processor, cause the electronic device to: determine a time interval on the basis of data related to a user's activity; determine an occurrence time point of an event related to the user's activity in the time interval on the basis of the data related to the activity; select images from among a plurality of images captured within the time interval; generate an additional image related to the activity on the basis of the determined occurrence time point and the selected images; and sequentially output images including the selected images and the generated additional image.

Description

Device, method, and non-transient computer-readable storage medium for outputting a slideshow using user activity information

[0001] A technology for outputting a slideshow using user activity information is disclosed below.

[0002] As the number of digital images increases, automated services are being provided that allow users to effectively manage and view images without separate editing. These services may include grouping users' images according to various criteria by utilizing artificial intelligence and data analysis technologies.

[0003] The information described above may be provided as related art for the purpose of aiding understanding of this document. None of the foregoing is to be claimed as prior art related to this document, nor is it to be used to determine prior art.

[0004] An electronic device according to one embodiment includes a display; at least one processor including a processing circuit; and a memory including one or more storage media for storing instructions. When the instructions are executed by the at least one processor, the electronic device may determine a target time interval corresponding to the user's activity based on the user's activity information, determine an occurrence time point of an event related to the user's activity within the target time interval based on the activity information, select target images from a plurality of candidate images captured within the target time interval, generate additional images related to the activity based on the determined occurrence time point and the selected target images, and output a slide show that sequentially displays images including the selected target images and the generated additional images.

[0005] A method performed by an electronic device according to one embodiment may include: determining a target time interval corresponding to the user's activity based on the user's activity information; determining an occurrence time point of an event related to the user's activity within the target time interval based on the activity information; selecting target images among a plurality of candidate images captured within the target time interval; generating additional images related to the activity based on the determined occurrence time point and the selected target images; and outputting a slide show that sequentially displays images including the selected target images and the generated additional images.

[0006] Instructions recorded on a computer-readable recording medium according to one embodiment can enable the operation of a method performed by the electronic device when executed by at least one processor.

[0007] In relation to the description of the drawings, the same or similar reference numerals may be used for identical or similar components.

[0008] FIG. 1 is a block diagram of an electronic device in a network environment according to various embodiments.

[0009] FIG. 2 is a flowchart illustrating an example of a method in which an electronic device according to one embodiment outputs a slideshow using activity information.

[0010] FIG. 3a is a diagram illustrating an example of an operation in which an electronic device according to one embodiment determines the timing of an event using biometric information.

[0011] FIG. 3b is a diagram illustrating an example of an operation in which an electronic device according to one embodiment determines the timing of an event based on the direction of movement of a user.

[0012] FIG. 4 is a diagram illustrating an example of an operation in which an electronic device according to one embodiment selects target images.

[0013] FIG. 5 is a diagram illustrating an example of an operation in which an electronic device according to one embodiment changes a target image by adding an event object.

[0014] FIG. 6a is a diagram illustrating an example of an operation in which an electronic device according to one embodiment generates an additional image based on a map image.

[0015] FIG. 6b is a diagram illustrating an example of an operation in which an electronic device according to one embodiment generates additional images based on a topographic cross-section.

[0016] FIG. 6c is a diagram illustrating an example of an operation in which an electronic device according to one embodiment generates additional images summarizing a user's activity.

[0017] FIG. 7 is a diagram illustrating an example of an operation in which an electronic device according to one embodiment outputs a slideshow that sequentially displays images.

[0018] FIG. 8 is a diagram illustrating an example of an operation in which an electronic device according to one embodiment adds a progress object corresponding to each image to each image.

[0019] FIG. 9 is a diagram illustrating an example of an operation in which an electronic device according to one embodiment generates a slideshow title.

[0020] FIG. 10 is a block diagram illustrating an example configuration of an electronic device according to one embodiment.

[0021] FIG. 11 is a generative artificial intelligence (AI) system according to one embodiment.

[0022] FIG. 12 illustrates an AI framework having on-device AI processing capabilities according to one embodiment.

[0023] Hereinafter, embodiments will be described in detail with reference to the attached drawings. In the description with reference to the attached drawings, identical components are given the same reference numeral regardless of the drawing number, and redundant descriptions thereof will be omitted.

[0024] FIG. 1 is a block diagram of an electronic device (101) in a network environment (100) according to various embodiments. Referring to FIG. 1, in the network environment (100), the electronic device (101) may communicate with an electronic device (102) through a first network (198) (e.g., a short-range wireless communication network) or may communicate 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).

[0025] According to one embodiment, the electronic device (101) may include a processor (120), memory (130), input module (150), sound output module (155), display (160), audio module (170), sensor (176), interface (177), connection terminal (178), haptic module (179), camera (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 (176), camera (180), or antenna module (197)) may be integrated into a single component (e.g., display (160)).

[0026] The processor (120) may be implemented as one or more IC (integrated circuit (or circuitry)) chips and may perform various data processing operations. The processor (120) may include processing circuitry. The processor (120) may include at least one electrical circuit and may process instructions (or programs (140), data) stored in memory (130) individually or collectively in a distributed manner. The processor (120) may include a processor assembly comprising one or more processing circuits. The processor (120) may include any processing circuit operative to control the performance and operation of one or more components of the electronic device (101) (e.g., memory (130), display (160), camera (180), communication circuit, and / or sensor (176)).

[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 (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 (160), sensor (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 (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 number of processors (120) may be one or more. For example, the processor (120) may have the structure of a multi-core processor such as a dual core, a quad core, or a hexa core.

[0030] The processor (120) can control the operations of the electronic device (101) by executing instructions stored in memory (130). For example, the processor (120) may correspond to a plurality of processors that divide and collectively perform a plurality of operations among the processors.

[0031] The memory (130) can store various data used by at least one component of the electronic device (101) (e.g., processor (120) or sensor (176)). The data may include, for example, input data or output data for software (e.g., program (140)) and related instructions. The memory (130) may include volatile memory (132) or non-volatile memory (134).

[0032] 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).

[0033] 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).

[0034] 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.

[0035] A display (160) (e.g., a display) can visually provide information to an external (e.g., a user) outside of the electronic device (101). The display (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 (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.

[0036] 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).

[0037] The sensor (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 (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. For example, the sensor (176) may include an inertial measurement unit (IMU).

[0038] 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.

[0039] 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).

[0040] 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.

[0041] The camera (180) can capture still images and video. According to one embodiment, the camera (180) may include one or more lenses, one or more image sensors, one or more image signal processors, or one or more flashes.

[0042] 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).

[0043] 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.

[0044] A 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 circuits. The communication module (190) may include one or more communication processors (CP) that operate independently of a 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 region 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 relation)) 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., 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 a first network (198) or a second network (199), using subscriber information (e.g., International Mobile Subscriber Identifier (IMSI)) stored in the subscriber identification module (196).

[0045] 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.

[0046] 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).

[0047] 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.

[0048] 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.

[0049] 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).

[0050] Each of the external electronic devices (102, 104) and the server (108) may be the same or 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 the server (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 request may perform at least part of the requested function or service, or additional functions or services 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. To this end, for example, cloud computing, distributed computing, mobile edge computing (MEC), or client-server computing technologies may be used. The electronic device (101) may provide ultra-low latency services using, for example, distributed computing or mobile edge computing. In another 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) may be applied to intelligent services (e.g., smart home, smart city, smart car, or healthcare) based on 5G communication technology and IoT-related technology.

[0051] FIG. 2 is a flowchart illustrating an example of a method in which an electronic device according to one embodiment outputs a slideshow using activity information.

[0052] In the following embodiments, each operation may be performed sequentially, but is not necessarily performed sequentially. For example, the order of each operation may be changed, and at least two operations may be performed in parallel.

[0053] According to one embodiment, operations (210) to (250) may be understood to be performed in a processor (e.g., processor (120) of FIG. 1) of an electronic device (e.g., electronic device (101) of FIG. 1).

[0054] According to one embodiment, an electronic device (e.g., the electronic device (101) of FIG. 1) can generate and / or output a slideshow using data related to a user's activity.

[0055] In various embodiments of the present disclosure, data related to a user's activity may also be expressed as user activity information. User activity information may include information regarding the user's activity (e.g., physical activity, mental activity). User activity may mean an act involving physical movement and / or mental concentration, and may include, exemplarily, exercise (e.g., hiking, cycling), motion, movement, and / or meditation. In various embodiments of the present disclosure, user activity may include the user performing a specific exercise (e.g., hiking, cycling, swimming, yoga) and / or the user visiting a specific place (e.g., an amusement park).

[0056] For example, user activity information may include location information, biometric information, acceleration information, and / or input information.

[0057] Location information may include information indicating the user's geographical location and / or changes in location. For example, the user's geographical location may include the latitude, longitude, altitude (e.g., elevation above sea level), and / or depth of the user's location. For example, information indicating changes in the user's location may include the user's speed of movement, the user's distance traveled, and / or the user's movement path.

[0058] Biological information is information regarding the user's biological signals and may include, for example, heart rate, respiratory rate, stress index, body temperature, electrocardiogram, and / or blood pressure.

[0059] Acceleration information may refer to acceleration information obtained through a gyroscope sensor. For example, acceleration information may be used to determine information regarding the user's steps (e.g., whether the user is walking, and / or the number of steps).

[0060] The input information may include information regarding user input that directs the start or end of an activity. For example, when starting a specific activity (e.g., hiking), the user may input an activity start input to an electronic device or another electronic device (e.g., electronic device (102) of FIG. 1, electronic device (104) of FIG. 1). When a user finishes a specific activity (e.g., hiking), the user may input an activity end input to an electronic device or another electronic device (e.g., the electronic device (102) of FIG. 1, the electronic device (104) of FIG. 1). In various embodiments of the present disclosure, an activity start input may include a user input indicating the start of the user's activity. An activity end input may include a user input indicating the end of the user's activity. For example, when a user starts an activity of a specific type of activity (e.g., walking, running, cycling, hiking, swimming), the user may input an activity start input to an electronic device or another electronic device for recording the activity of the specific type of activity (e.g., storing biometric information). The activity start input may include information regarding the type of activity to be performed by the user selected from a plurality of candidate activity types (e.g., walking, running, cycling, hiking, and swimming).

[0061] According to one embodiment, user activity information may be obtained based on a sensor included in an electronic device (e.g., sensor (176) of FIG. 1) or based on a sensor included in another electronic device connected to the electronic device (e.g., electronic device (102) of FIG. 1, electronic device (104) of FIG. 1).

[0062] For example, other electronic devices connected to the electronic device may include wearable devices (e.g., smartwatches, smart rings, smart glasses). Other electronic devices may include devices for measuring physical quantities specialized for specific exercises. For example, other electronic devices may include a power meter for measuring output (in watts) generated when a rider pedals in cycling. The power meter may measure torque (e.g., force) and / or rotations per minute (RPM) at multiple sampling points.

[0063] Hereinafter, an example of a method for an electronic device according to one embodiment to generate and / or output a slideshow including images related to activity information using user activity information is described.

[0064] In operation (210), according to one embodiment, the electronic device may determine a time interval corresponding to the user's activity based on data related to the user's activity. In various embodiments of the present disclosure, the time interval corresponding to the user's activity may also be expressed as a 'target time interval'.

[0065] The electronic device can determine (e.g., detect) the start and end of a user's activity using user activity information. The electronic device can determine the time interval from the start time point of the user's activity to the end time point of the activity as the target time interval. The target time interval may refer to the time interval during which the user performs the activity. As will be described later, the electronic device can generate and / or output a slideshow based on at least one of the images acquired (e.g., captured) during the target time interval.

[0066] According to one embodiment, the electronic device may determine a target time interval based on a change in the user's location. For example, the electronic device may determine a target time interval including a time interval in which the user's location changes, based on detecting an activity in which the user's location changes using at least one of acceleration information or location information. The activity in which the user's location changes may include, for example, walking, running, hiking, and / or cycling.

[0067] For example, if the electronic device determines that the user is walking using acceleration information and / or determines that the user's location is continuously changing for a certain period of time using location information, it may determine the start time of an activity based on the start time of said certain period of time. If the electronic device determines that the user is not walking using acceleration information and / or determines that the user's location is not changing for a certain period of time using location information, it may determine the end time of an activity based on the start time of said certain period of time.

[0068] According to one embodiment, an electronic device may determine a target time interval based on a user's biometric information. For example, the electronic device may determine a target time interval that includes a time interval in which a predetermined condition is satisfied, based on the user's biometric information satisfying a predetermined condition. The predetermined condition may refer to a condition for determining that the user is active. For example, the predetermined condition may include the user's heart rate being above a threshold heart rate. For example, the predetermined condition may include the user's respiratory rate being above a threshold respiratory rate.

[0069] According to one embodiment, an electronic device may determine a target time interval based on user input information. For example, the electronic device may acquire (e.g., detect, receive) information regarding at least one of an activity start input or an activity end input. According to one embodiment, another electronic device (e.g., an accessory device) may acquire at least one of an activity start input or an activity end input and transmit information regarding at least one of the activity start input or the activity end input to the electronic device. Based on at least one of an activity start input indicating the start of a user's activity or an activity end input indicating the end of a user's activity, the electronic device may determine a target time interval including a time interval from the start of an activity to the end of an activity.

[0070] According to one embodiment, one of the activity start input and the activity end input (e.g., activity start input) may be acquired, and the other (e.g., activity end input) may not be acquired. For example, an electronic device may determine the activity start time based on the activity start input and determine the activity end time using the input information and other activity information (e.g., biometric information, location information, acceleration information).

[0071] According to one embodiment, an electronic device can determine (e.g., predict) the type of activity of an activity based on activity information acquired within a target time interval. For example, based on the activity information, the electronic device can select the type of activity of an activity (e.g., walking type) from among a plurality of candidate activity types (e.g., walking type, running type, cycling type, hiking type, and swimming type).

[0072] In operation (220), according to one embodiment, the electronic device can determine the occurrence time point of an event related to the user's activity during a time interval based on data related to the activity.

[0073] Events related to activity may refer to events appearing in the user's activity information that occurred during the user's activity.

[0074] For example, an activity-related event may include the detection of a maximum value, a minimum value, and / or a threshold value (e.g., an event occurrence value) among the biosignal values ​​detected during a target time interval. By example, the event may include an event in which the maximum heart rate is detected during the user's activity, an event in which the lowest stress index is detected, and / or an event in which a threshold heart rate corresponding to high intensity is detected.

[0075] For example, an event related to an activity may include a change in the direction of movement (e.g., the rate of change of the movement path relative to time or distance) on the user's movement path that is greater than or equal to a threshold change. For example, the event may include an event that returns or turns relative to a specific point (e.g., a mountain summit).

[0076] For example, an event related to an activity may include having a maximum value, a minimum value, and / or a threshold value among the values ​​of physical quantities (e.g., speed, acceleration, torque and / or rotational speed measured by a power meter) measured during a target time interval. By example, the event may include an event regarding the user moving at a maximum speed value among the speed values ​​of the user's activity, or an event regarding the user moving at a threshold speed.

[0077] For example, events related to activity may include updating the user's personal records. For example, the events may include updating the user's maximum distance record, updating the user's maximum heart rate record, and / or updating the user's maximum exercise time record. The user's personal records may include, for example, average heart rate, average respiratory rate, average distance traveled, minimum heart rate, minimum respiratory rate, and minimum distance traveled.

[0078] For example, events related to an activity may be defined based on the type of activity. For instance, if the activity is of the cycling type, events related to the activity may include events regarding the user moving at a maximum speed value, and / or events regarding the user's movement speed maintaining a maximum speed value (or maximum speed range). For instance, if the activity is of the hiking type, events related to the activity may include events regarding a change in the altitude (or gradient of altitude) of the user's location, and / or events regarding the user being located at a specific location (e.g., landmark, shelter, rock, viewpoint).

[0079] The operation for determining the event and / or the timing of the event is described in more detail later in FIG. 3a and FIG. 3b.

[0080] In operation (230), according to one embodiment, the electronic device may select images from among a plurality of images captured within a time interval. In various embodiments of the present disclosure, an 'image captured within a target time interval' may be expressed as a 'candidate image', and an 'image selected from a plurality of candidate images' may be expressed as a 'target image'.

[0081] Multiple candidate images may refer to image(s) among the images accessible to the electronic device whose shooting time falls within the target time interval. The images accessible to the electronic device may include images stored in the internal memory of the electronic device (e.g., memory (130) of FIG. 1) and / or an external database accessible to the electronic device (e.g., a cloud server).

[0082] According to one embodiment, a plurality of candidate images may include images acquired (e.g., captured) through an electronic device or another electronic device. For example, the other electronic device may include an XR device (mixed reality device) (e.g., an OST (optical see-through) device, a VST (video see-through) device, a VR (virtual reality) device) as a user's device. However, the other electronic device is not limited to being a user's device, and the other electronic device may be another user's device connected (e.g., communicating) to the user's electronic device via wired and / or wireless connections.

[0083] The electronic device can select target images using activity information related to each candidate image. A target image may refer to an image selected as a primary image among multiple candidate images. As will be described later, a target image may refer to an image to be included as at least part of a slide in a slideshow corresponding to a user's activity.

[0084] According to one embodiment, the electronic device can select a target image using activity information associated with each candidate image.

[0085] Activity information related to each candidate image may refer to a portion of activity information corresponding to a partial time interval corresponding to the candidate image among the activity information corresponding to the target time interval. A partial time interval corresponding to each candidate image may refer to a partial time interval that includes the time point at which the candidate image was acquired. For example, a partial time interval corresponding to each candidate image may include a time interval of a fixed length (e.g., 5 seconds) based on (e.g., center) the time point at which the candidate image was acquired.

[0086] The electronic device may select a target image based on whether an image selection condition corresponding to the selection of the target image is satisfied. For example, the image selection condition may include that at least one biosignal value (e.g., heart rate value) of the biosignal information corresponding to the image (e.g., candidate image) is greater than or less than a threshold signal value.

[0087] According to one embodiment, an image selection condition may be determined (e.g., selected, predicted) from among a plurality of candidate image selection conditions based on a determined (e.g., selected, predicted) activity type. The plurality of candidate image selection conditions may be predetermined, and each candidate image selection condition may correspond to one or more candidate activity types. Based on the activity type, the electronic device may determine (e.g., selected, acquired, extracted) one or more image selection conditions corresponding to the activity type of the user's activity from among the plurality of candidate image selection conditions. The electronic device may select a target image using the determined image selection condition(s).

[0088] According to one embodiment, an electronic device may determine at least one of a plurality of candidate images as a target image that is captured within an event time interval corresponding to the time of occurrence of an event. For example, the electronic device may determine the time of occurrence of a specific event, and if there is one or more candidate images captured within an event time interval corresponding to the time of occurrence of the specific event, it may select at least one target image from among the one or more candidate images. The event time interval corresponding to the time of occurrence of the event may include a time interval of a fixed time length (e.g., 5 minutes) based on (e.g., center) the time of occurrence of the event.

[0089] According to one embodiment, the electronic device may select target images based on an object detected in a candidate image, similarity between candidate images, and / or quality of the candidate image. The operation of selecting target images is described in more detail later in FIG. 4.

[0090] In operation (240), according to one embodiment, the electronic device may generate additional images related to the activity based on a determined time of occurrence and selected images.

[0091] Additional images may include images generated by an electronic device based on an event, in addition to the target images. For example, additional images may include images indicating an event that occurred during an activity.

[0092] For example, the electronic device may change a target image or generate an additional image depending on whether, among the target images, there exists an event image captured during an event time interval corresponding to the time of occurrence of the event. The change of the target image is described in more detail later in FIG. 5, and the generation of the additional image is described in more detail later in FIG. 6.

[0093] In operation (250), according to one embodiment, the electronic device may sequentially output images including selected images and generated additional images. For example, the electronic device may output a slide show that sequentially displays images including target images and additional images.

[0094] According to one embodiment, a slide show may include a video that sequentially displays a plurality of slides based on a plurality of images. Each slide may include at least a portion of one image. For example, the slide show may include a video generated based on the display order of a plurality of slides, the display time of each slide, and / or the display effect of each slide. In various embodiments of the present disclosure, each slide of the slide show may be interpreted as substantially the same as a corresponding image. An operation for outputting a slide show is described in more detail below in FIG. 7.

[0095] Although not explicitly illustrated in FIG. 2, according to one embodiment, an electronic device may generate a slideshow based on a video if a video is captured within at least a portion of a target time interval. For example, the electronic device may use at least one video frame among a plurality of video frames included in the video as a candidate image. For example, the electronic device may acquire a portion corresponding to a specific time interval in the video (e.g., at least one video frame among a plurality of video frames of the video) as part of a slideshow. As an example, the electronic device may add a portion captured during an event time interval corresponding to the time of occurrence of an event in the video as part of a slideshow.

[0096] In various embodiments of the present disclosure, a slideshow is primarily described as including video, but is not limited thereto. According to one embodiment, a slideshow may include one or more images or one or more videos.

[0097] FIG. 3a is a diagram illustrating an example of an operation in which an electronic device according to one embodiment determines the timing of an event using biometric information.

[0098] An electronic device according to one embodiment (e.g., the electronic device (101) of FIG. 1) can determine the occurrence of an event or the timing of the occurrence of an event by using the user's biometric information among the user's activity information.

[0099] For example, the user's biosignal may include biosignal values ​​of the biosignal corresponding to a plurality of sampling time points. As illustrated in the graph (300a) of FIG. 3a, the user's biosignal information may include the user's heart rate values ​​sensed at each of the plurality of sampling time points of the target time interval (e.g., a first sampling time point (t1) to a 25th sampling time point (t25)).

[0100] The electronic device may determine the time point determined based on at least one of a minimum value, a maximum value, or a threshold biosignal value among a plurality of biosignal values ​​in a target time interval (e.g., a first sampling time point (t1) to a 25th sampling time point (t25)) in the user's biosignal information as the time point of occurrence of the event.

[0101] In the graph (300a) of Fig. 3a, the horizontal axis represents time (unit: seconds), and the vertical axis represents heart rate (unit: bpm (beats per minute)).

[0102] Referring to the graph (300a) of FIG. 3a, for example, the electronic device can determine the 15th sampling time (t15) corresponding to the maximum value among a plurality of biosignal values ​​as the time of occurrence of the event.

[0103] Referring to the graph (300a) of FIG. 3a, for example, the electronic device may determine the earliest 11th sampling time (t11) among sampling times (e.g., 11th sampling time (t11) to 17th sampling time (t17)) having a biosignal value greater than or equal to a threshold biosignal value (e.g., 140) among a plurality of biosignal values ​​as the time of occurrence of an event. The threshold biosignal value may, for example, include a threshold biosignal value corresponding to high-intensity exercise. When the time of occurrence of an event is determined based on the threshold biosignal value corresponding to high-intensity exercise, it may be interpreted that a high-intensity exercise start event has occurred.

[0104] Although not explicitly shown in the graph (300a) of FIG. 3a, for example, if the biosignal is a stress index, the electronic device may determine the point in time corresponding to the minimum value among the plurality of biosignal values ​​(e.g., having the minimum value) as the point in time of occurrence of the event.

[0105] Although not explicitly shown in FIG. 3a, the electronic device can determine the time of occurrence of an event using location information.

[0106] For example, an electronic device can acquire velocity values ​​corresponding to multiple sampling points of a target time interval. The electronic device can determine the timing of an event based on a maximum value, a minimum value, and / or a threshold value among the multiple velocity values.

[0107] For example, an electronic device can acquire position values ​​(e.g., elevation values, depth values) corresponding to multiple sampling points of a target time interval. The electronic device can determine the time of occurrence of an event based on a maximum value, a minimum value, and / or a threshold value among the multiple elevation values ​​(or depth values).

[0108] FIG. 3b is a diagram illustrating an example of an operation in which an electronic device according to one embodiment determines the timing of an event based on the direction of movement of a user.

[0109] An electronic device according to one embodiment (e.g., the electronic device (101) of FIG. 1) can determine the occurrence of an event or the time of occurrence of an event by using location information among the user's activity information.

[0110] For example, the user's location information may include user locations corresponding to multiple sampling time points. The user's location may include at least one of latitude, longitude, altitude, and / or depth.

[0111] The electronic device can determine the user's movement path (310b) during a target time interval using the user's location information. The electronic device can determine a point within the movement path (310b) where the amount of change in the direction of movement is greater than or equal to a threshold change amount. The electronic device can determine a point corresponding to the determined point as the time of occurrence of the event. Points where the amount of change in the direction of movement is greater than or equal to a threshold change amount may include a turning point (e.g., a U-turn point), a summit (e.g., a mountain summit), and / or a turning point.

[0112] For example, the electronic device can determine a turning point in the movement path (310b). The electronic device can determine a time point corresponding to the determined turning point as the time of occurrence of the event.

[0113] Referring to FIG. 3b, the electronic device can determine the user's movement path (310b) during the target section. For example, the user's movement path (310b) may be a path that visits a starting point (e.g., point (326b)), a first point (321b), a second point (322b), a third point (323b), a fourth point (324b), a fifth point (325b), a first point (321b), and a destination point (e.g., point (326b)) in order. The third point (323b) in the user's movement path (310b) may be a point where the user changes the direction of movement by more than a threshold, and for example, may be a returning point. The electronic device can determine the user's direction of movement at a specific point on the movement path (310b) (e.g., the user's location at a specific sampling point). For example, the electronic device may determine the direction from a first position at a first sampling point to a second position at a second sampling point following the first sampling point as the direction of movement of the user from the first position. The electronic device may determine a point where the amount of change in the direction of movement is greater than a threshold change amount during a set time (e.g., for 5 minutes) or during a certain distance of movement (e.g., while moving 100m). In FIG. 3b, the electronic device may determine a first point (321b), a second point (322b), a third point (323b), a fourth point (324b), and a fifth point (325b) where the amount of change in the direction of movement is greater than the threshold change amount. The electronic device may determine the points corresponding to the first point (321b), the second point (322b), the third point (323b), the fourth point (324b), and the fifth point (325b) as the time of occurrence of an event.

[0114] Although not explicitly illustrated in FIGS. 3a and 3b, an electronic device according to various embodiments may determine the time of occurrence of an event based on updating a user's personal record.

[0115] According to one embodiment, an electronic device can acquire a user's activity history. The user's activity history may include records regarding the user's activity information (e.g., personal records). For example, the user's activity history may include the user's maximum heart rate, the user's maximum respiratory rate, the user's maximum altitude, the user's maximum depth, the user's maximum distance traveled, and / or the user's maximum activity time.

[0116] Based on activity information, the electronic device may determine the point in time when the user breaks a record appearing in the activity history during a target time interval as the point in time when the event occurs. For example, the electronic device may determine the point in time when the altitude of the user's location included in the location information among the activity information breaks the maximum altitude record appearing in the activity history as the point in time when the event occurs.

[0117] FIG. 4 is a diagram illustrating an example of an operation in which an electronic device according to one embodiment selects target images.

[0118] An electronic device according to one embodiment (e.g., the electronic device (101) of FIG. 1) can select target images from among a plurality of candidate images.

[0119] According to one embodiment, the electronic device may select a target image based on the quality of each of a plurality of candidate images. In various embodiments of the present disclosure, the quality of an image (e.g., a candidate image) may include a degree regarding the visual clarity of the image. For example, the quality of the image may include information regarding the composition of the image, whether the image is shaken, the accuracy of focus, the noise level, contrast, light blur, and / or resolution. For example, the electronic device may not select at least one candidate image as the target image if it determines that the quality of at least one of the plurality of candidate images is below a threshold quality.

[0120] For example, an electronic device may determine whether the quality of an image is below a threshold quality by using a quality score output model for determining the quality of an image. The quality score output model may refer to an artificial intelligence model trained to output a quality score representing the quality of an image from input data corresponding to an image. For example, the quality score output model may be implemented based on a convolutional neural network (CNN), a large vision model (LVM), and / or a large language model (LLM). The electronic device may obtain a quality score representing the quality of a candidate image based on the result of applying the quality score output model to each candidate image. The electronic device may select a target image from among candidate image(s) having a quality score greater than the threshold quality. The electronic device may exclude candidate images having a quality score below the threshold quality from the target image (e.g., may not select them as the target image).

[0121] According to one embodiment, the electronic device can select a target image based on an object detected in each of a plurality of candidate images.

[0122] For example, an electronic device can obtain information regarding an object detected in each candidate image as a result of analyzing a plurality of candidate images. The electronic device can select target images based on whether a registered object is detected in the plurality of candidate images. The registered object may include the user's face, the user's possessions (e.g., bicycle, clothes, car), another person's face registered by the user (e.g., mother's face, friend's face), and / or an object of a type registered by the user as a preferred object (e.g., cat, flower).

[0123] According to one embodiment, the electronic device may include a target image selection module (420). The target image selection module (420) may analyze each candidate image (e.g., determine the quality (or quality score) of each candidate image, detect an object from each candidate image, obtain a location corresponding to each candidate image, obtain a time point corresponding to each candidate image, and calculate visual similarity between a plurality of images). The target image selection module (420) may select a target image from among a plurality of candidate images using the analysis results.

[0124] A target image selection module (420) according to one embodiment may be a hardware module or a software module. If the target image selection module (420) is implemented as a software module, it may include at least one instruction stored in memory (e.g., memory (130) of FIG. 1) and executed by at least one processor (e.g., processor (120) of FIG. 1). The operation of the software module may be understood as the operation of the processor.

[0125] Referring to FIG. 4, the electronic device may acquire a plurality of candidate images including a first image (411) and a second image (412). The electronic device may determine that a registered object (e.g., a person-type object) is not identified in the first image (411). The electronic device may determine that a registered object (e.g., an object region (413)) is identified in the second image (412). Based on identifying a registered object (e.g., an object region (413)) in the second image (412), the electronic device may select the second image (412) as a target image.

[0126] According to one embodiment, an electronic device may select a target image based on differences between a plurality of candidate images. Differences between a plurality of images (e.g., candidate images, target image, and candidate image) may include differences between times when the images were taken, distances between locations where the images were taken, and / or visual similarity.

[0127] The electronic device can select a first target image from among a plurality of candidate images. For example, the electronic device can determine the image captured first among the plurality of candidate images as the first target image.

[0128] The electronic device may select a second target image from among a plurality of candidate images based on at least one of the visual similarity between each candidate image and a first target image, the difference between time points corresponding to each candidate image and the first target image, or the distance between locations corresponding to each candidate image and the first target image.

[0129] For example, an electronic device can calculate the visual similarity between a first target image and a candidate image. The visual similarity between the first target image and the candidate image can be calculated based on the accumulated difference between the pixel values ​​of the pixels of the first target image and the candidate image (e.g., the absolute values ​​of the differences). The electronic device can select a candidate image as a second target image in which the visual similarity between the first target image and the candidate image is less than a threshold similarity. In other words, the electronic device may not select a candidate image that is the same as or similar to an already selected target image (e.g., the first target image) (e.g., a candidate image with a threshold similarity or higher) as a target image (e.g., the second target image). By selecting a candidate image that is not similar to an already selected target image (e.g., the first target image) (e.g., a candidate image with a threshold similarity or lower) as a target image (e.g., the second target image), the electronic device can select various images as target images.

[0130] For example, an electronic device may calculate the difference (e.g., temporal difference) between time points corresponding to a first target image and a candidate image. In various embodiments of the present disclosure, a time point corresponding to an image (e.g., target image, candidate image) may include the time point at which the image was captured. The electronic device may select a candidate image as a second target image in which the difference between the time points corresponding to the first target image and the candidate image is greater than or equal to a threshold time difference. In other words, the electronic device may not select a candidate image corresponding to a time point that is the same as or temporally adjacent to the time point corresponding to the already selected target image (e.g., first target image) as a target image (e.g., second target image). By selecting a candidate image captured at a time point that has a difference of at least a certain time (e.g., a predetermined time length, 5 minutes) from the time point of capture of the already selected target image (e.g., first target image) as a target image (e.g., second target image), the electronic device may select images captured over the entire target time interval as target images.

[0131] For example, an electronic device may calculate the distance (e.g., spatial difference) between locations corresponding to a first target image and a candidate image. In various embodiments of the present disclosure, the location corresponding to the image (e.g., target image, candidate image) may include the location where the image was taken (e.g., latitude, longitude, altitude, depth). The electronic device may obtain the location corresponding to the first target image (e.g., the location where the first target image was taken) and the location corresponding to the candidate image (e.g., the location where the candidate image was taken). The electronic device may select a candidate image as the second target image such that the distance between the locations corresponding to the first target image and the candidate image is greater than or equal to a threshold distance. In other words, the electronic device may not select a candidate image as the target image (e.g., second target image) that is taken at the same or spatially adjacent location as the already selected target image (e.g., first target image). The electronic device can select images taken at spatially widely distributed locations as target images by selecting a candidate image taken at a location that is at least a certain distance (e.g., threshold distance, 1 km) away from the shooting location of an already selected target image (e.g., first target image) as a target image (e.g., second target image).

[0132] In FIG. 4, the electronic device primarily describes selecting a target image from among a plurality of candidate images based on an object detected in a candidate image, similarity between candidate images, and / or quality of the candidate images, but is not limited thereto. According to one embodiment, the electronic device may select a target image from a plurality of candidate images based on user input. For example, the electronic device may display a screen including a list of a plurality of candidate images. The electronic device may detect user input for selecting at least one of the plurality of candidate images. The electronic device may select at least one image selected by user input as the target image.

[0133] FIG. 5 is a diagram illustrating an example of an operation in which an electronic device according to one embodiment changes a target image by adding an event object.

[0134] An electronic device according to one embodiment (e.g., the electronic device (101) of FIG. 1) can change a target image by adding an event object to an event image (510) based on the existence of an event image (510) related to an event among the target images.

[0135] For example, the electronic device can determine an event time interval corresponding to the time of occurrence of the event. As described above in FIG. 2, the event time interval may refer to a portion of the target time interval that has a fixed time length (e.g., 5 minutes) based on (e.g., center) the time of occurrence of the event.

[0136] The electronic device may add an event object indicating an event to the event image (510) based on the existence of an event image (510) captured within a time interval related to the event among the target images. The event image (510) may refer to an image captured within the event time interval among the target images.

[0137] As described above in FIG. 2, an electronic device according to one embodiment may select at least one of the one or more candidate images captured within an event time interval as a target image (e.g., event image (510)) when a plurality of candidate images include one or more candidate images captured within an event time interval. The electronic device may change at least one target image by adding an event object indicating an event to the event image (510), which is the target image.

[0138] According to one embodiment, an event object may mean a graphic object including a visual representation (521-1, 521-2, 521-3) and / or text (522) corresponding to the event.

[0139] A visual representation corresponding to an event may include a visual representation assigned to the type of event (e.g., icon, digital badge, emoji) and a value corresponding to the event (e.g., biosignal value, speed value, position value).

[0140] For example, based on the event being a maximum speed event that occurs based on the maximum value among the speed values, the event object may include a visual representation (521-1) indicating the maximum speed. For example, based on the event being a minimum stress index event that occurs based on the minimum value among the stress index values, the event object may include a visual representation (521-2) indicating the minimum stress index. For example, based on the event being a maximum heart rate event that occurs based on the maximum value among the heart rate values, the event object may include a visual representation (521-3) indicating the maximum heart rate.

[0141] Referring to FIG. 5, the electronic device can obtain a modified event image (531) by adding an event object containing a visual representation (521-3) corresponding to the event to the event image (510).

[0142] According to one embodiment, an event object may include text (522) describing the event. Referring to FIG. 5, an electronic device may generate text (522) describing the event. An electronic device may obtain an event object containing the generated text (522). An electronic device may obtain a modified event image (532) by adding the event object containing the text (522) to an event image (510).

[0143] In FIG. 5, an electronic device according to various embodiments of the present disclosure primarily describes modifying an event image by adding an event object to at least one of the event images when an event image exists among the target images, but is not limited thereto. For example, when an event image exists among the target images, the electronic device may obtain an additional image as a result of adding an event object to the event image while maintaining the event image. The electronic device may add the event image and the additional image (e.g., the result of adding an event object to the event image) to a slideshow as individual slides.

[0144] FIG. 6a is a diagram illustrating an example of an operation in which an electronic device according to one embodiment generates an additional image based on a map image.

[0145] An electronic device according to one embodiment (e.g., the electronic device (101) of FIG. 1) can generate an additional image (600a) indicating an event based on the fact that among the target images, there is no image (e.g., an event image) taken during the event time interval.

[0146] For example, the electronic device may generate an additional image (600a) based on the result of adding an event object (620a) to a user's location corresponding to the time of occurrence of the event in the map image. The map image may include the user's location corresponding to the time of occurrence of the event. For example, the map image may include at least some of the user's locations (or user's movement path) during the target time interval.

[0147] Referring to FIG. 6a, the electronic device can determine the timing of an event (e.g., a maximum heart rate event) based on the maximum value of the heart rate values. The electronic device can generate an additional image (600a) indicating a maximum heart rate event based on the fact that among the target images, there is no event image captured during the event time interval corresponding to the timing of the maximum heart rate event.

[0148] For example, the electronic device may add an event object (620a) indicating a maximum heart rate event at a location corresponding to the time of occurrence of the maximum heart rate event in the map image. As shown in FIG. 6a, the electronic device may generate an additional image (600a) by adding a graphic object (610a) indicating the user's movement path and an event object (620a) to the map image.

[0149] FIG. 6b is a diagram illustrating an example of an operation in which an electronic device according to one embodiment generates additional images based on a topographic cross-section.

[0150] An electronic device according to one embodiment (e.g., the electronic device (101) of FIG. 1) can generate an additional image (600b) indicating an event based on the fact that among the target images, there is no image (e.g., an event image) taken during the event time interval.

[0151] For example, the electronic device may generate an additional image (600b) based on the result of adding an event object (620b) to a user's location corresponding to the time of occurrence of the event in a topographic cross-section. A topographic cross-section is a drawing showing a cross-section of terrain cut along a reference line (e.g., a transverse line, a longitudinal line), and may include an image that visually represents elevation and / or slope changing along said cross-section.

[0152] Referring to FIG. 6b, the electronic device can determine the timing of an event (e.g., a maximum heart rate event) based on the maximum value of the heart rate values. The electronic device can generate an additional image (600b) indicating a maximum heart rate event based on the fact that among the target images, there is no event image captured during the event time interval corresponding to the timing of the maximum heart rate event.

[0153] For example, the electronic device may add an event object (620b) indicating a maximum heart rate event at a location corresponding to the time of occurrence of the maximum heart rate event in the topographic cross-section. As shown in FIG. 6b, the electronic device may generate an additional image (600b) by adding a graphic object (610b) and an event object (620b) indicating a user at a location (e.g., altitude) in the topographic cross-section.

[0154] According to one embodiment, the electronic device may determine to generate an additional image (600b) based on a topographic cross-section, based on the fact that the cumulative change in altitude for the user's location (e.g., total sum of altitude movement) during a target time interval is greater than or equal to a threshold change in altitude. The cumulative change in altitude may refer to the value obtained by accumulating the absolute values ​​of the change in altitude per unit time. For example, if the cumulative change in altitude, including ascent and descent of altitude, is large during the user's activity, the electronic device may generate an additional image (600b) using a topographic cross-section to represent the altitude of the user's location at the time the event occurs.

[0155] According to one embodiment, the electronic device may determine to generate an additional image (e.g., an additional image (600a) of FIG. 6a) based on a map image based on the fact that, during a target time interval, the cumulative change in altitude for the user's location is less than a threshold change in altitude. As described above in FIG. 6a, the electronic device may generate an additional image based on a map image when the cumulative change in altitude is less than a threshold change in altitude.

[0156] However, the electronic device according to various embodiments of the present disclosure is not limited to determining whether to generate an additional image based on a map image or based on a topographic cross-section based on a cumulative change in elevation. An electronic device according to one embodiment may generate an additional image based on a topographic cross-section based on the user's activity type being configured to use a topographic cross-section in generating the additional image. For example, a mountain biking type, a hiking type, and / or a climbing type may be configured to use a topographic cross-section in generating the additional image. An electronic device may generate an additional image based on a map image based on the user's activity type being configured to use a map image in generating the additional image (e.g., not configured to use a topographic cross-section).

[0157] In various embodiments of the present disclosure, additional images are primarily described as two-dimensional images, but are not limited thereto. For example, additional images may include three-dimensional images. The three-dimensional images may include images illustrating a user's location (e.g., a three-dimensional location, the latitude, longitude, and altitude of the user's location) on a three-dimensional map (e.g., a three-dimensional map showing latitude, longitude, and altitude).

[0158] FIG. 6c is a diagram illustrating an example of an operation in which an electronic device according to one embodiment generates additional images summarizing a user's activity.

[0159] An electronic device according to one embodiment (e.g., the electronic device (101) of FIG. 1) may generate additional images corresponding to (e.g., summarizing the activity) a user's activity. The additional images may include visual representations indicating the user's locations (e.g., movement path), one or more events that occurred during the target time interval, and / or the type of activity of the activity.

[0160] For example, referring to FIG. 6c, the electronic device can add a graphic object (610c) to the map image that indicates the user's movement path during the target time interval.

[0161] For example, during a user's activity (e.g., during a target time interval), a first event (e.g., a maximum speed event) and a second event (e.g., a maximum heart rate event) may occur. The electronic device may determine the time of occurrence of the first event and the time of occurrence of the second event within the target time interval. The electronic device may add a first event object (621c) indicating the first event to a user's location in a map image corresponding to the time of occurrence of the first event. The electronic device may add a second event object (622c) indicating the second event to a user's location in a map image corresponding to the time of occurrence of the second event.

[0162] For example, the electronic device may add a graphic object (630c) including a visual representation (e.g., a bicycle drawing) indicating the type of activity (e.g., a cycling type) and / or a user's face object at a location in a map image (e.g., a location corresponding to the end time of the activity). The user's face object may include an area corresponding to the user's face detected from at least one of a plurality of candidate images and / or selected target images captured within a target section. However, it is not limited thereto, and the user's face object may include a face object that is previously stored and / or registered.

[0163] As will be described later, the electronic device can determine that an additional image corresponding to the user's activity (e.g., summarizing the activity) corresponds to the end point of the activity (e.g., the end point of the target time interval).

[0164] FIG. 7 is a diagram illustrating an example of an operation in which an electronic device according to one embodiment outputs a slideshow that sequentially displays images.

[0165] An electronic device according to one embodiment (e.g., the electronic device (101) of FIG. 1) can generate a slideshow using images including target images and additional images. As described above, the electronic device can acquire images including target images and additional images after determining a target time interval corresponding to an activity.

[0166] The electronic device can determine the display order of images based on time points corresponding to the images. The electronic device can determine the display order of images based on the result of arranging the time points corresponding to the images in chronological order. For example, if a first time point corresponding to a first image (701) precedes a second time point corresponding to a second image (702), the electronic device can determine the display order of the first image (701) to be earlier than the display order of the second image (702).

[0167] According to one embodiment, a target image selected from among candidate images may correspond to the time of capture of the target image. For example, a target image to which an event object has been added to an event image may correspond to the time of capture of the event image (e.g., the target image before the event object was added). For example, an additional image indicating an event (e.g., the additional image (600a) of FIG. 6a, the additional image (600b) of FIG. 6b)) may correspond to the time of occurrence of the event.

[0168] Referring to FIG. 7, the electronic device may acquire a first image (701), a second image (702), a third image (703), a fourth image (704), a fifth image (705), a sixth image (706), and a seventh image (707). The first image (701), the second image (702), the fourth image (704), the fifth image (705), and the sixth image (706) may be target images selected from a plurality of candidate images (or target images to which event objects have been added). The third image (703) may be an additional image indicating an event (e.g., a maximum heart rate event). The seventh image (707) may be an additional image summarizing the user's activity. Each of the first image (701), the second image (702), the fourth image (704), the fifth image (705), and the sixth image (706) may correspond to the time of capture of the corresponding image. The third image (703) may correspond to the time of occurrence of an event (e.g., a maximum heart rate event). The seventh image (707) may correspond to the time of end of an activity (e.g., the time of end of a target time interval). The electronic device may determine the display order of the first image (701) to the seventh image (707) based on the result of arranging the time points corresponding to the first image (701) to the seventh image (707) in chronological order.

[0169] The electronic device may generate a slideshow that displays images sequentially (e.g., one at a time) according to the display order of the first image (701) through the seventh image (707). For example, the electronic device may determine the display time of each image. For example, the electronic device may determine the display time of each image to be a fixed time (e.g., 3 seconds). Outputting the slideshow may include displaying a specific image among the images for which the display order has been reached, for the display time of that specific image. After the display of a specific image has started, if the display time of that specific image has elapsed, the display order of an image having the display order following that specific image may be reached. For example, the slideshow may be generated, saved, and / or output in a video format.

[0170] According to one embodiment, an electronic device may apply and display a visual effect to at least one image in a slide show. For example, the electronic device may determine a visual effect applied to at least one image in a slide show by using activity information related to at least one image among the images. The visual effect may include an on-screen effect applied while displaying the image, a transition effect of the image, and / or animation of the image's components (e.g., event objects, visual representations, text).

[0171] On-screen effects may refer to effects applied to an image while it is being displayed, and may include, for example, effects that gradually change brightness while the image is being displayed, or effects that impart motion to the image (e.g., shake, sparkle, wave effects). Transition effects may refer to visual effects applied when switching between images being displayed in a slideshow, and may include, for example, fade effects, zoom effects (e.g., zoom-in, zoom-out), and / or whip effects. Animation of components may include visual effects in which components included in the image move or change (e.g., rotate, enlarge, reduce) within the image.

[0172] An electronic device can acquire activity information related to an image. The activity information related to the image may include activity information (e.g., biometric information, location information, acceleration information) corresponding to a time interval including a point in time corresponding to the image (e.g., the time of capturing the image).

[0173] An electronic device can determine a visual effect on an image based on whether activity information related to the image satisfies the conditions for applying a specific visual effect.

[0174] For example, the conditions for applying the shaking effect may include at least one heart rate value being greater than or equal to a threshold heart rate, or at least one respiratory rate value being greater than or equal to a threshold respiratory rate. The electronic device may apply the shaking effect while displaying an image in a slideshow based on the fact that at least one heart rate value among a plurality of heart rate values ​​included in the biometric information of the activity information related to the image is greater than or equal to a threshold heart rate.

[0175] For example, the application condition for a whip effect among transition effects may include an image containing an event object indicating a maximum speed event. An electronic device may apply a whip effect when displaying an image (or when starting or ending the display of a target image or additional images) in a slideshow based on the image containing an event object indicating a maximum speed event. For reference, the image containing an event object indicating a specific event may include the image being a target image selected based on the time of occurrence of the specific event and / or an additional image created based on the time of occurrence of the specific event.

[0176] FIG. 8 is a diagram illustrating an example of an operation in which an electronic device according to one embodiment adds a progress object corresponding to each image to each image.

[0177] An electronic device according to one embodiment (e.g., the electronic device (101) of FIG. 1) can add a progress object determined based on a position corresponding to the image for each of the images.

[0178] According to one embodiment, a progress object may indicate the degree to which an activity has progressed at a point corresponding to each image within the entirety of the user's activity. For example, the progress object may indicate the degree to which an activity has progressed positionally (or spatially) at a point corresponding to each image. For example, an electronic device may determine the user's movement path (e.g., the entire movement path) during the user's activity. The electronic device may generate a progress object that indicates a location corresponding to each image within the movement path.

[0179] For example, an electronic device can acquire a map object that visually represents the user's movement path during a target time interval (e.g., during the user's activity). The electronic device can extract an area within a map image containing the user's locations during the target time interval as a map object. The electronic device can determine the user's movement path using the user's locations and add a visual representation indicating the user's movement path to the map object.

[0180] For each of the images, the electronic device can generate a progress object corresponding to that image based on the result of adding a marker indicating a position corresponding to that image to a map object. The position corresponding to the image may include the location where the image was taken and / or the user's location at the time corresponding to the image. For each of the images, the electronic device can add a progress object corresponding to that image. The electronic device can output a slideshow that sequentially displays the images to which the progress objects have been added.

[0181] Referring to FIG. 8, the electronic device can acquire a first image (811), a second image (812), and a third image (813).

[0182] For example, the electronic device may generate a first progress object (821) corresponding to the first image (811) based on the result of adding a marker (831) to a map object that indicates a location corresponding to the first image (811) for the first image (811). By adding the first progress object (821) to the first image (811), the electronic device may obtain a first image (841) with the progress object added.

[0183] For example, the electronic device may generate a second progress object (822) corresponding to the second image (812) based on the result of adding a marker (832) to a map object that indicates a location corresponding to the second image (812) to the second image (812). By adding the second progress object (822) to the second image (812), the electronic device may obtain a second image (842) with the progress object added.

[0184] For example, the electronic device may generate a third progress object (823) corresponding to the third image (813) based on the result of adding a marker (833) to a map object that indicates a location corresponding to the third image (813) for the third image (813). By adding the third progress object (823) to the third image (813), the electronic device may obtain a third image (843) with the progress object added.

[0185] The electronic device can generate and / or output a slideshow that sequentially displays a first image (841) with a progress object added, a second image (842) with a progress object added, and a third image (843) with a progress object added.

[0186] FIG. 9 is a diagram illustrating an example of an operation in which an electronic device according to one embodiment generates a slideshow title.

[0187] An electronic device according to one embodiment (e.g., the electronic device (101) of FIG. 1) can generate a title for a slide show using activity information and / or images. The title for the slide show may include text representing the slide show.

[0188] For example, an electronic device may generate a title for a slideshow using a title generation model. The title generation model may refer to an artificial intelligence model that is generated and / or trained to output output data corresponding to a slideshow title from input data corresponding to activity information and / or images. According to one embodiment, the title generation model may be implemented based on a convolutional neural network (CNN) and / or a large language model (LM). The electronic device may use information regarding events that occurred among the activity information as input data for the title generation model.

[0189] For example, during a user's activity, an event may occur that updates the user's personal record (e.g., maximum distance record for cycling). The electronic device may obtain information regarding the event that occurred during the activity (e.g., event of updating the maximum distance record for cycling) as input data for a title generation model. Based on the result of applying the title generation model to the input data, the electronic device may obtain a title for a slideshow (e.g., "Longest Cycling Record Updated!").

[0190] Referring to the screen (900) of FIG. 9, the electronic device may display a screen of a photo application. The screen of the photo application may include one of a plurality of tabs (e.g., a selected tab). When displaying the screen of the photo application, the electronic device may display a screen based on the selected tab among the plurality of tabs. Each tab may correspond to a button for selecting the corresponding tab. The screen of the photo application may include a plurality of buttons corresponding to the plurality of tabs. For example, the plurality of tabs may include a photo tab, an album tab, a story tab, and a share tab. The screen of the photo application may include a button (901) corresponding to the photo tab, a button (902) corresponding to the album tab, a button (903) corresponding to the story tab, and a button (904) corresponding to the share tab.

[0191] For example, the Photos tab may include a screen for viewing images stored on an electronic device. The Albums tab may include a screen for viewing images stored on an electronic device according to multiple albums grouped by the user's selection. The Stories tab may include a screen for viewing a slideshow generated based on images stored on the electronic device. The Share tab may display a screen for viewing images shared with other users.

[0192] The electronic device may display a screen containing an area corresponding to a slideshow when the Story tab is selected. For example, if three slideshows are created, the electronic device may display three areas corresponding individually to the three slideshows.

[0193] For example, after generating a specific slideshow, the electronic device may display an area corresponding to the specific slideshow using the representative image of the specific slideshow and the title of the specific slideshow. The electronic device may select the representative image of the slideshow as one of the images (e.g., images including target images and additional images). For example, the electronic device may select the representative image based on activity information, time points corresponding to the images, locations corresponding to the images, objects detected in the images, and / or the quality of the images.

[0194] Referring to FIG. 9, the electronic device can display a screen (900) based on the selection of a story tab in a photo application after generating a first slideshow, a second slideshow, and a third slideshow. The electronic device can display a screen corresponding to a story tab, including an area (910) corresponding to the first slideshow, an area (920) corresponding to the second slideshow, and an area (930) corresponding to the third slideshow.

[0195] The electronic device can output (e.g., play) a slideshow based on obtaining user input selecting an area corresponding to the slideshow. For example, the electronic device can display images sequentially according to the display order of the images. As described above in FIG. 7, the electronic device can display the image for which the display order has arrived during the display time. The electronic device can display the image for which the display order has arrived by applying a determined visual effect to the image for which the display order has arrived.

[0196] FIG. 10 is a block diagram illustrating an example configuration of an electronic device according to one embodiment.

[0197] An electronic device (1001) according to one embodiment (e.g., the electronic device (101) of FIG. 1) may include an image acquisition module (1010), an image analysis module (1020), an activity information analysis module (1030), a target image selection module (1040), a slideshow management module (1050), a display (1060), an image database (1071) (hereinafter, 'Image DB (1071)'), a biometric database (1072) (hereinafter, 'Biometric DB (1072)'), a location database (1073) (hereinafter, 'Location DB (1073)'), and a slideshow database (1074) (hereinafter, 'Slideshow DB (1074)').

[0198] The image acquisition module (1010) may include a module for acquiring an image. According to one embodiment, the image acquisition module (1010) may include a camera capable of capturing an image. According to one embodiment, the image acquisition module (1010) may receive (e.g., download) an image from another device (e.g., a server). The image acquisition module (1010) may use a camera included in the electronic device (1001) or a camera included in another electronic device (e.g., a video recorder, a webcam, another user's device).

[0199] The image analysis module (1020) may include a module for analyzing images. For example, the image analysis module (1020) may perform the function of detecting (or identifying) objects from an image or understanding the situation of a scene appearing in an image. Information regarding objects detected from an image (e.g., object detection information) and / or information regarding the situation of a scene appearing in an image (e.g., scene situation information) obtained by an image analysis model may be used to select an image (e.g., target image) to be displayed in a slideshow. The image analysis module (1020) may utilize technologies such as vision object detection (e.g., face detection), motion detection, scene understanding, and / or image segmentation. The image analysis module (1020) may utilize various statistical classification and / or machine learning models (e.g., neural networks) for the analysis of images.

[0200] The activity information analysis module (1030) may include a module for analyzing and / or processing activity information including biometric information and / or location information corresponding to a target time interval. As described above in FIG. 2, the activity information may include the user's biometric information (e.g., HR (heart rate), blood pressure, body temperature) and / or the user's location information (e.g., movement path, speed). The activity information analysis module (1030) may determine the time of occurrence of an event based on the result of processing the activity information. As described above, the activity information analysis module (1030) may determine the time of occurrence of an event based on the minimum value and maximum value of HR, the maximum value of blood pressure, the distance traveled, and / or the maximum value of speed.

[0201] A target image selection module (1040) (e.g., a target image selection module (420) of FIG. 4) may include a module for selecting a target image to be used for creating a slideshow from among a plurality of candidate images. The target image selection module (1040) may select a target image using activity information, a result analyzed by an image analysis module (1020), and / or a result analyzed by an activity information analysis module (1030).

[0202] The slideshow management module (1050) may include a module for creating and / or managing a slideshow. The slideshow management module (1050) may create a slideshow that displays images sequentially in a display order using images including target images and additional images.

[0203] The display (1060) (e.g., the display (160) of FIG. 1) can display the generated slideshow.

[0204] The electronic device (1001) may include a database. For example, the electronic device (1001) may include an image DB (1071), a biometric DB (1072), a location DB (1073), and a slideshow DB (1074). Each of the image DB (1071), biometric DB (1072), and location DB (1073) may store images, biometric information, and location information periodically or aperiodically, independently (e.g., regardless) of the creation of the slideshow. The slideshow DB (1074) may store information regarding a slideshow created by a user and / or a slideshow created by the electronic device (1001).

[0205] A module included in an electronic device according to one embodiment (e.g., image acquisition module (1010), image analysis module (1020), activity information analysis module (1030), target image selection module (1040), slideshow management module (1050)) may be a hardware module or a software module. If the module is implemented as a software module, it may include at least one instruction stored in memory (e.g., memory (130) of FIG. 1) and executed by at least one processor (e.g., processor (120) of FIG. 1). The operation of the software module may be understood as the operation of the processor.

[0206] FIG. 11 is a generative artificial intelligence (AI) system (1100) according to one embodiment. Referring to FIG. 11, the generative AI system (1100) may include a user interface (1110), an AI framework (1120), a generative AI model (1130), a knowledge repository (1140), and an application / service module (1150). These components may be operated on one or more of the following devices: an electronic device (e.g., the electronic device (101) of FIG. 1), an external device (e.g., the electronic device (102) of FIG. 1, the electronic device (104) of FIG. 1), or a server (e.g., the server (108) of FIG. 1). For example, the user interface (1110) and AI framework (1120) may be operated on an electronic device, while the knowledge repository (1140) and generative AI model (1130) may be operated on a server.

[0207] According to one embodiment, a user interface (1110) 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, or a combination of two or more of menu selections. The user interface (1110) may include various context information (e.g., running application or user location) related to the generative AI system (1100) at the time the user input is received, in addition to or instead of the user input. The user interface (1110) may provide user input or context information to an AI framework (1120). The user interface (1110) may provide the processing result of the user input or context information to the user through the AI ​​framework (1120). According to one embodiment, in addition to user input, the electronic device may provide context information obtained using information included on a screen to the AI ​​framework (1120). The result of processing user input or context information may be provided in the form of text, images, voice, video, or actions requested by the user (e.g., launching a specified function or app), or a combination of two or more of these.

[0208] According to one embodiment, the AI ​​framework (1120) can identify (e.g., estimate) a user intent based on at least some user input or context information received from a user interface (1110), control each of the relevant modules (e.g., 1121, 1123, or 1125) to perform a function or action corresponding to the identified user intent, and coordinate collaboration between two or more modules. The AI ​​framework (1120) may include a prompt design module (1121), an API / Plug-in management module (1123), and an output modification module (1125), as illustrated in FIG. 11.

[0209] According to one embodiment, the prompt design module (1121) can generate a prompt to be input to a generative AI model (1130) based at least partially on user input or context information received from a user interface (1110). For example, the prompt design module (1121) can generate a prompt using user preferences, a prompt library, or prompt examples stored in a knowledge repository (1140) based at least partially on user input or context information.

[0210] According to one embodiment, the API / plug-in management module (1123) may communicate, for example, via an API, with various resources (e.g., a knowledge repository (1140)) that provide said additional information when there is a request for said additional information in relation to user input. Additionally or alternatively, when a specified action (e.g., a function, app, or service) is performed in response to said user input, the API / plug-in management module (1123) may request the application / service module (1150) to perform said specified action via a corresponding API. The API / plug-in management module (1123) may provide information obtained from the knowledge repository (1140), the application / service module (1150), or another external resource to the prompt design module (1121). The obtained information may be used by the prompt design module (1121) to generate a prompt together with the user input, or provided to a generative AI model (1130).

[0211] According to one embodiment, an output modification module (1125) can fine-tune the results obtained through a generative AI model (1130) as at least part of the response to a user input (e.g., user query). For example, the output modification module (1125) can determine whether the content of the response obtained through the generative AI model (1130) is appropriate as a response to a request made by the user input. For example, the output modification module (1125) 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 (1130) and the user input. Additionally or generally, the output modification module (1125) 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 (1121) to obtain a response again through the generative AI model (1130).

[0212] According to one embodiment, the generative AI model (1130) 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 auto encoder (VAE), or a diffusion-based model using a VAE and a transformer. The language generation model may include, for example, a large language model (LM), 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 vehicle, the electronic device (101) of FIG. 1, the program (140) of FIG. 1). Additionally, at least some AI models (e.g., LLM) may include a low-rank adaptation adapter (LoRA adapter) that is fine-tuned for a specific task or a specific situation.

[0213] As illustrated in FIG. 11, the generative AI model (1130) may include one or more adapters (e.g., first adapter through ninth adapter). One adapter may be the same as or different from the other adapters.

[0214] FIG. 12 illustrates an AI framework (1220) having on-device AI processing capabilities according to one embodiment (e.g., the AI ​​framework (1120) of FIG. 11). In this case, the AI ​​framework (1320) may generate and learn a response to the user input using resources within the device, instead of sending the user input received through a user interface (e.g., the user interface (1110) of FIG. 11) operating on the same device (e.g., the electronic device (101) of FIG. 1) to a generative AI model (e.g., the generative AI model (1130) of FIG. 11) operating on an external device (e.g., the server (108) of FIG. 1)). Referring to FIG. 12, the AI ​​framework (1320) may include a cross-application action module (1210), a personal data managing module (1230), an on-device AI model (1250), and an orchestration module (1270).

[0215] According to one embodiment, the cross-application action module (1210) determines one or more additional applications required for the operation of an executed application (e.g., an assistant app) and may connect or suggest operations between the app and at least one additional application, or between a plurality of additional applications. For example, the cross-application action module (1210) may execute one or more additional applications to be used to respond to a user request through the assistant app sequentially or at least partially and simultaneously. Additionally, the cross-application action module (1210) may communicate with the additional applications so that the result of the execution of one additional application (e.g., content) can be shared with other additional applications.

[0216] According to one embodiment, the personal data management module (1230) may provide personal information (e.g., schedule, contact, or message information) about a user of the application (e.g., assistant app) or the additional application running on the device (e.g., electronic device 101) or other related individuals (e.g., family or friends) to another module of the AI ​​framework (1320) or a related module (e.g., generative AI model (1130)) running on another device.

[0217] According to one embodiment, the on-device AI model (1250) may include at least one model among one or more AI models (e.g., GAN, VAE, LLM, LMM, LVM, or LAM) operated on an external device (e.g., server (108)) or a corresponding lightweight AI model. Additionally, the model or the lightweight model may include, for example, a LoRA adapter.

[0218] As illustrated in FIG. 12, the on-device AI model (1250) may include one or more adapters (e.g., a first adapter through a ninth adapter). One adapter may be the same as or different from the other adapters.

[0219] According to one embodiment, the orchestration module (1270) may select one or more AI models to be used to obtain a response to user input (e.g., user query). For example, the orchestration module (1270) may select one or more AI models, such as an on-device AI model (1250), an AI model operating on an external device (e.g., the server (108) of FIG. 1) (e.g., the generative AI model (1130) of FIG. 11), or a third AI model (not shown) operating on another external device. When multiple AI models are selected, the orchestration module (1270) may communicate with the selected models or devices so that the operation between the selected AI models and the processing of the results thereof can be coordinated between the relevant models or devices.

[0220] According to one embodiment, two or more modules of a generative AI system (e.g., a cross-application action module (1210) and an orchestration module (1270)) may be implemented as a single module to maintain the same functionality. Various variations are possible.

[0221] According to one embodiment, the electronic device (101) may include a display (160); at least one processor (120) including a processing circuit; and a memory (130) including one or more storage media for storing instructions, and when the instructions are executed by the at least one processor (120), the electronic device (101) may determine a target time interval corresponding to the user's activity based on the user's activity information, determine an occurrence time point of an event related to the user's activity within the target time interval based on the activity information, select target images from among a plurality of candidate images captured within the target time interval, generate additional images (600a; 600b; 600c) related to the activity based on the determined occurrence time point and the selected target images, and output a slide show that sequentially displays images including the selected target images and the generated additional images (600a; 600b; 600c).

[0222] According to one embodiment, when the instructions are executed by the at least one processor (120), the electronic device (101) may be configured to determine an event time interval corresponding to the occurrence time of the event, and based on the existence of an event image (510) among the target images that was captured during the event time interval, an event object (620a; 620b; 621c; 622c) indicating the event may be added to the event image (510).

[0223] According to one embodiment, when the instructions are executed by the at least one processor (120), the electronic device (101) may be configured to determine an event time interval corresponding to the time of occurrence of the event, and to generate additional images (600a; 600b; 600c) indicating the event based on the fact that there is no image among the target images that was taken during the event time interval.

[0224] According to one embodiment, the activity information of the user includes the user's biometric information, and when the instructions are executed by the at least one processor (120), the electronic device (101) may determine the time point determined based on at least one of the minimum value among a plurality of biometric signal values ​​of the target time interval in the user's biometric information, the maximum value among the plurality of biometric signal values, or a threshold biometric signal value as the time point of occurrence of the event.

[0225] According to one embodiment, the activity information of the user includes location information of the user, and when the instructions are executed by the at least one processor (120), the electronic device (101) may determine the movement trajectory of the user during the target time interval using the location information, and based on the determined movement trajectory, determine a time point corresponding to a point where the amount of change in the user's direction of movement is greater than or equal to a threshold change amount as the time point of occurrence of the event.

[0226] According to one embodiment, when the instructions are executed by the at least one processor (120), the electronic device (101) may be configured to acquire the user's activity history and, based on the activity information, determine the time at which the user breaks a record in the activity history during the target time interval as the time of occurrence of the event.

[0227] According to one embodiment, the activity information of the user includes acceleration information or location information, and when the instructions are executed by the at least one processor (120), the electronic device (101) may determine the target time interval including the time interval in which the user's location changes based on detecting an activity in which the user's location changes using at least one of the acceleration information or the location information.

[0228] According to one embodiment, the activity information of the user includes the user's biometric information, and when the instructions are executed by the at least one processor (120), the electronic device (101) may be configured to determine the target time interval including the time interval in which the predetermined condition is satisfied, based on the user's biometric information satisfying the predetermined condition.

[0229] According to one embodiment, the activity information of the user includes input information of the user, and when the instructions are executed by the at least one processor (120), the electronic device (101) may determine a target time interval including a time interval from the start time of the activity to the end time of the activity based on at least one of an activity start input indicating the start of the user's activity or an activity end input indicating the end of the user's activity.

[0230] According to one embodiment, when the instructions are executed by the at least one processor (120), the electronic device (101) may determine the display order of the images based on time points corresponding to the images, and determine the visual effect applied to the at least one image in the slide show using activity information related to at least one image among the images.

[0231] According to one embodiment, when the instructions are executed by the at least one processor (120), the electronic device (101) may be configured to acquire a map object that visually represents the user's movement path during the target time interval, and for each of the images, create a progress object (821; 822; 823) corresponding to the image based on the result of adding a marker (831; 832; 833) indicating a position corresponding to the image to the map object, add the progress object (821; 822; 823) corresponding to the image to each of the images, and output the slide show that sequentially displays the images to which the progress object (821; 822; 823) has been added.

[0232] According to one embodiment, when the instructions are executed by the at least one processor (120), the electronic device (101) may be configured to select the target images based on whether a registered object is detected in the plurality of candidate images.

[0233] According to one embodiment, when the instructions are executed by the at least one processor (120), the electronic device (101) may be configured to select a first target image among the plurality of candidate images, and to select a second target image among the plurality of candidate images based on at least one of the visual similarity between each candidate image and the first target image, the difference between each candidate image and time points corresponding to the first target image, or the distance between each candidate image and locations corresponding to the first target image.

[0234] According to one embodiment, an operation (210) of determining a target time interval corresponding to the user's activity based on the user's activity information; an operation (220) of determining an occurrence time point of an event related to the user's activity within the target time interval based on the activity information; an operation (230) of selecting target images from among a plurality of candidate images captured within the target time interval; and an additional image related to the activity can be generated based on the determined occurrence time point and the selected target images.

[0235] According to one embodiment, the method may further include: determining an event time interval corresponding to the time of occurrence of the event; and adding an event object indicating the event to the event image based on the existence of an event image captured during the event time interval among the target images.

[0236] According to one embodiment, the operation (240) of generating the additional image may include: an operation of determining an event time interval corresponding to the time of occurrence of the event; and an operation of generating an additional image indicating the event based on the fact that there is no image among the target images that was taken during the event time interval.

[0237] According to one embodiment, the activity information of the user includes the user's biometric information, and the operation (220) for determining the time of occurrence of the event may include determining the time of occurrence of the event as a time determined based on at least one of a minimum value among a plurality of biometric signal values ​​of the target time interval in the user's biometric information, a maximum value among the plurality of biometric signal values, or a threshold biometric signal value.

[0238] According to one embodiment, the activity information of the user includes location information of the user, and the operation (220) for determining the occurrence time of the event may include: an operation to determine the movement path of the user during the target time interval using the location information; and an operation to determine the time point corresponding to the point where the amount of change in the user's movement direction is greater than or equal to a threshold change amount based on the determined movement path as the occurrence time of the event.

[0239] According to one embodiment, the operation (220) for determining the occurrence time of the event may include: the operation of obtaining the user's activity history; and the operation of determining the time when the user breaks a record that appears in the activity history during the target time interval based on the activity information as the occurrence time of the event.

[0240] 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.

[0241] 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.

[0242] 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).

[0243] 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.

[0244] According to one embodiment, the method according to the various embodiments disclosed herein may be provided as 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 distributed online (e.g., download or upload) through an application store (e.g., Play Store™) 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.

[0245] 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.

[0246] The embodiments described above may be implemented as hardware components, software components, and / or combinations of hardware and software components. For example, the devices, methods, and components described in the embodiments may be implemented using a general-purpose computer or a special-purpose computer, such as, for example, a processor, a controller, an arithmetic logic unit (ALU), a digital signal processor, a microcomputer, a field programmable gate array (FPGA), a programmable logic unit (PLU), a microprocessor, or any other device capable of executing and responding to instructions. The processing unit may execute an operating system (OS) and software applications executed on said operating system. Additionally, the processing unit may access, store, manipulate, process, and generate data in response to the execution of the software. For ease of understanding, the processing unit may be described as being used as a single unit, but those skilled in the art will understand that the processing unit may include multiple processing elements and / or multiple types of processing elements. For example, the processing unit may include multiple processors or one processor and one controller. In addition, other processing configurations, such as parallel processors, are also possible.

[0247] Software may include computer programs, code, instructions, or a combination of one or more of these, and may configure a processing unit to operate as desired or command the processing unit independently or collectively. Software and / or data may be permanently or temporarily embodied in any type of machine, component, physical device, virtual equipment, or computer storage medium or device so as to be interpreted by the processing unit or to provide instructions or data to the processing unit. Software may be distributed over networked computer systems and may be stored or executed in a distributed manner. Software and data may be stored on computer-readable storage media.

[0248] The method according to the embodiment may be implemented in the form of program instructions that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, etc., either alone or in combination, and the program instructions recorded on the medium may be those specifically designed and configured for the embodiment or may be those known and available to those skilled in the art of computer software. Examples of computer-readable storage media include magnetic media such as hard disks, floppy disks, and magnetic tapes; optical recording media such as CD-ROMs and DVDs; magneto-optical media such as floptical disks; and hardware devices specifically configured to store and execute program instructions, such as ROM, RAM, and flash memory. Examples of program instructions include machine code, such as that generated by a compiler, as well as high-level language code that can be executed by a computer using an interpreter, etc.

[0249] The hardware device described above may be configured to operate as one or more software modules to perform the operation of the embodiment, and vice versa.

Claims

1. In an electronic device (101), Display (160); At least one processor (120) including a processing circuit; and It includes a memory (130) comprising one or more storage media for storing instructions, and When the above instructions are executed by the at least one processor (120), the electronic device (101) is made to, Based on data related to user activity, determine the time interval, and Based on data related to the above activity, the occurrence time point of an event related to the user's above activity within the above time interval is determined, and Among the multiple images captured within the above time interval, select the images, and Based on the above-determined occurrence time and the above-selected images, additional images (600a; 600b; 600c) related to the activity are generated, and Images including the selected images and the generated additional images (600a; 600b; 600c) are output sequentially. making, Electronic device (101).

2. In Paragraph 1, When the above instructions are executed by the at least one processor (120), the electronic device (101) is made to, Determine the event time interval corresponding to the occurrence time of the above event, and Based on the existence of an event image (510) captured during the event time interval among the selected images, an event object (620a; 620b; 621c; 622c) indicating the event is added to the event image (510). making, Electronic device (101).

3. In any one of paragraphs 1 to 2, When the above instructions are executed by the at least one processor (120), the electronic device (101) is made to, Determine an event time interval corresponding to the time of occurrence of the above event, and Based on the fact that among the selected images, there is no image captured during the event time interval, additional images (600a; 600b; 600c) indicating the event are generated. making, Electronic device (101).

4. In any one of paragraphs 1 through 3, The data related to the above user's above activity is, Includes the biometric information of the above user, and When the above instructions are executed by the at least one processor (120), the electronic device (101) is made to, A point in time determined based on at least one of a minimum value among a plurality of biosignal values ​​of the time interval, a maximum value among the plurality of biosignal values, or a threshold biosignal value in the biosignal information of the user is determined as the point in time of occurrence of the event. making, Electronic device (101).

5. In any one of paragraphs 1 through 4, The data related to the above user's above activity is, Includes the location information of the above user, and When the above instructions are executed by the at least one processor (120), the electronic device (101) is made to, Using the above location information, the movement trajectory of the user during the above time interval is determined, and Based on the movement path determined above, the time point corresponding to the point where the amount of change in the user's direction of movement exceeds a threshold change amount is determined as the occurrence time of the event. making, Electronic device (101).

6. In any one of paragraphs 1 through 5, When the above instructions are executed by the at least one processor (120), the electronic device (101) is made to, Acquire the activity history of the above user, and Based on data related to the above activity, the point in time when the user updates (breaks) a record appearing in the activity history during the above time interval is determined as the occurrence time of the above event. making, Electronic device (101).

7. In any one of paragraphs 1 through 6, The data related to the above user's above activity is, Includes acceleration information or position information, When the above instructions are executed by the at least one processor (120), the electronic device (101) is made to, Based on detecting an activity in which the user's location changes using at least one of the acceleration information or the location information, the time interval including the time interval in which the user's location changes is determined. making, Electronic device (101).

8. In any one of paragraphs 1 through 7, The data related to the above user's above activity is, Includes the biometric information of the above user, and When the above instructions are executed by the at least one processor (120), the electronic device (101) is made to, Based on the fact that the biometric information of the above user satisfies a predetermined condition, the time interval including the time interval in which the predetermined condition is satisfied is determined. making, Electronic device (101).

9. In any one of paragraphs 1 through 8, The data related to the above user's above activity is, Includes the above user input information, When the above instructions are executed by the at least one processor (120), the electronic device (101) is made to, Based on at least one of an activity start input indicating the start of the user's activity or an activity end input indicating the end of the user's activity, a time interval including a time interval from the activity start time to the activity end time is determined. making, Electronic device (101).

10. In any one of paragraphs 1 through 9, When the above instructions are executed by the at least one processor (120), the electronic device (101) is made to, Based on time points corresponding to the images including the selected images and the additional images, the display order of the images including the selected images and the additional images is determined, and Determining a visual effect applied to at least one image using data related to an activity among at least one image including the selected images and the additional images. making, Electronic device (101).

11. In any one of paragraphs 1 through 10, When the above instructions are executed by the at least one processor (120), the electronic device (101) is made to, Acquire a map object that visually represents the user's movement path during the above time interval, and For each of the images including the selected images and the additional images, a progress object (821; 822; 823) corresponding to the image is created based on the result of adding a marker (831; 832; 833) indicating a position corresponding to the image to the map object. For each of the images including the selected images and the additional images, a progress object (821; 822; 823) corresponding to the image is added, and The images to which the above progress objects (821; 822; 823) have been added are output sequentially. making, Electronic device (101).

12. In any one of paragraphs 1 through 11, When the above instructions are executed by the at least one processor (120), the electronic device (101) is made to, Select the images based on whether a registered object is detected in the plurality of images. making, Electronic device (101).

13. In any one of paragraphs 1 through 12, When the above instructions are executed by the at least one processor (120), the electronic device (101) is made to, Among the above plurality of images, a first image is selected, and Among the plurality of images above, a second image is selected based on at least one of the visual similarity between each image and the first image, the difference between each image and time points corresponding to the first image, or the distance between each image and locations corresponding to the first image. making, Electronic device (101).

14. In a method performed by an electronic device, An action (210) for determining a time interval based on data related to user activity; An operation (220) to determine the occurrence time point of an event related to the user's activity during the time interval based on data related to the activity; Among a plurality of images captured within the above time interval, an operation (230) of selecting images; An operation (240) of generating additional images related to the activity based on the above-determined occurrence time and the above-selected images; and The operation (250) of sequentially outputting images including the selected images and the additional generated images A method including 15. A computer-readable storage medium storing one or more computer programs comprising instructions for performing the method of paragraph 14.

Images