# US 12,764,416 B2 · Electronic device and controlling method of electronic device > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 12,764,416 B2 - Document ID: US12764416B2 - Status: Granted - Kind: B2 - Application number: 18/977,369 - Filed: 2024-12-11 - Published: 2025-04-03 - Granted: 2026-10-13 - Earliest claimed: 2020-06-10 - Assignees: Samsung Electronics Co., Ltd. - Applicants: Samsung Electronics Co., Ltd. - Inventors: Jaeyeop Lee; Dongchan Kim; Jongmyeong Ban; Hyechan Bae; Dongnam Byun; Seongwo Oh; Haedong Yeo; Jinyoung Hwang - Web page: https://patentgrep.com/patent/US12764416B2 ## CPC - H04N 23/64: {Computer-aided capture of images, e.g. transfer from script file into camera, check of taken image quality, advice or proposal for image composition or decision on when to take image} - H04N 1/2129: {Recording in, or reproducing from, a specific memory area or areas, or recording or reproducing at a specific moment} - H04N 5/2628: {Alteration of picture size, shape, position or orientation, e.g. zooming, rotation, rolling, perspective, translation} - H04N 23/45: for generating image signals from two or more image sensors being of different type or operating in different modes, e.g. with a CMOS sensor for moving images in combination with a charge-coupled device [CCD] for still images - H04N 23/62: Control of parameters via user interfaces - H04N 23/631: {Graphical user interfaces [GUI] specially adapted for controlling image capture or setting capture parameters} - H04N 23/667: Camera operation mode switching, e.g. between still and video, sport and normal or high- and low-resolution modes - H04N 23/951: by using two or more images to influence resolution, frame rate or aspect ratio - H04N 23/57: Mechanical or electrical details of cameras or camera modules specially adapted for being embedded in other devices - H04N: PICTORIAL COMMUNICATION, e.g. TELEVISION ## Abstract An electronic device and a controlling method of the electronic device are provided. The controlling method of an electronic device according to the disclosure includes the steps of, based on a first user input for or related to acquiring a live view image through a camera including a plurality of lenses different from one another being received, acquiring a plurality of image frames for each of the plurality of lenses and storing the image frames in a first memory, inputting the plurality of image frames for each lens stored in the first memory into a neural network model, by a predetermined time interval, and acquiring score information including composition preference information of each of the input image frames, selecting at least one lens among the plurality of lenses based on the score information, storing image frames acquired through the selected at least one lens in a second memory during the predetermined time interval, and based on a second user input for initiating recording of the live view image being received, storing an image related to the image frames stored in the second memory in a third memory until a time point when a third user input for ending the recording is received. ## Claims ### Claim 1 An electronic device comprising: a camera system comprising a plurality of lenses that are different; memory storing one or more instructions; and at least one processor configured to execute the one or more instructions, wherein the one or more instructions, when executed by the at least one processor, cause the electronic device to: control the camera system to acquire a plurality of image frames through each of the plurality of lenses, select at least one lens among the plurality of lenses based on an aesthetic of the plurality of image frames, store image frames acquired through the selected at least one lens in the memory; based on that the selected at least one lens in a first section and the selected at least one lens in a second section being different, identify a type of a scene corresponding to image frames before and after a boundary of the first section and the second section, apply an effect corresponding to the identified type of the scene to at least one image frame of the stored image frames before and after the boundary stored in the memory, and acquire an image in which at least some of stored image frames in the first section and the second section are merged and the effect is not applied. ### Claim 2 (depends on 1) The electronic device of claim 1, wherein the one or more instructions, when executed by the at least one processor, cause the electronic device to: based on that the selected at least one lens in the first section and the selected at least one lens in the second section are not different, acquire an image in which at least some of image frames stored in the memory in the first section and the second section are merged and the effect is not applied. ### Claim 3 (depends on 1) The electronic device of claim 1, wherein the one or more instructions, when executed by the at least one processor, cause the electronic device to: identify the type of the scene corresponding to image frames by inputting, into a trained scene recognition model, the image frames in a predetermined number before and after the boundary when image frames acquired through a first lens of the plurality of lenses are switched to image frames acquired through a second lens of the plurality of lenses. ### Claim 4 (depends on 1) The electronic device of claim 1, wherein the effect is applied to the at least one image frame stored in the memory by inserting a prestored image into the at least one image frame. ### Claim 5 (depends on 1) The electronic device of claim 1, wherein the effect is applied to the at least one image frame stored in the memory by applying a predetermined editing technique to the at least one image frame. ### Claim 6 (depends on 5) The electronic device of claim 5, wherein the predetermined editing technique includes at least one of fade in, fade out, zoom in, zoom out, or screen rotation. ### Claim 7 (depends on 3) The electronic device of claim 3, wherein the effect is applied to the at least one image frame stored in the memory by decreasing a ratio of the image frames acquired through the first lens and increasing the ratio of the image frames acquired through the second lens. ### Claim 8 (depends on 1) The electronic device of claim 1, wherein the one or more instructions, when executed by the at least one processor, cause the electronic device to: select the at least one lens among the plurality of lenses by inputting an image frame of the plurality of image frames into at least one neural network model comprising a first neural network model based on a location of an object in the input image frame, and acquire score information by using the at least one neural network model, the score information indicating the aesthetic of each of the input image frames. ### Claim 9 (depends on 8) The electronic device of claim 8, wherein the at least one neural network model further comprises a second neural network model based on how much similar an input image frame of the input image frames, is to learning data, and a third neural network model based on a type of the object and the location of the object in the input image frame. ### Claim 10 (depends on 8) The electronic device of claim 8, wherein the plurality of lenses comprises a first lens and a second lens, and wherein the one or more instructions, when executed by the at least one processor, cause the electronic device to: based on score information of a first image frame acquired through the first lens being higher than or identical to score information of a second image frame acquired through the second lens at a time point when the first image frame was acquired, select the first lens, and based on the score information of the first image frame being lower than the score information of the second image frame, select the second lens. ### Claim 11 A method of controlling an electronic device, the method comprising: acquiring, a camera system comprising a plurality of lenses that are different, a plurality of image frames through each of the plurality of lenses; selecting at least one lens among the plurality of lenses based on an aesthetic of the plurality of image frames; storing image frames acquired through the selected at least one lens in a memory of the electronic device; based on that the selected at least one lens in a first section and the selected at least one lens in a second section being different, identifying a type of a scene corresponding to image frames before and after a boundary of the first section and the second section; applying an effect corresponding to the identified type of the scene to at least one image frame of the image frames before and after the boundary stored in the memory; and acquiring an image in which at least some of image frames stored in the memory in the first section and the second section are merged and the effect not applied. ### Claim 12 (depends on 11) The method of claim 11, further comprising: based on that the selected at least one lens in the first section and the selected at least one lens in the second section are not different, acquiring an image in which at least some of image frames stored in the memory in the first section and the second section are merged and the effect is not applied. ### Claim 13 (depends on 11) The method of claim 11, further comprising: identifying the type of the scene corresponding to image frames by inputting, into a trained scene recognition model, the image frames in a predetermined number before and after the boundary when image frames acquired through a first lens of the plurality of lenses are switched to image frames acquired through a second lens of the plurality of lenses. ### Claim 14 (depends on 11) The method of claim 11, wherein the effect is applied to the at least one image frame stored in the memory by inserting a prestored image into the at least one image frame. ### Claim 15 (depends on 11) The method of claim 11, wherein the effect is applied to the at least one image frame stored in the memory by applying a predetermined editing technique to the at least one image frame. ### Claim 16 (depends on 15) The method of claim 15, wherein the predetermined editing technique includes at least one of fade in, fade out, zoom in, zoom out, or screen rotation. ### Claim 17 (depends on 13) The method of claim 13, wherein the effect is applied to the at least one image frame stored in the memory by decreasing a ratio of the image frames acquired through the first lens and increasing the ratio of the image frames acquired through the second lens. ### Claim 18 (depends on 11) The method of claim 11, further comprising: selecting the at least one lens among the plurality of lenses by inputting image frame of the plurality of image frames into at least one neural network model comprising a first neural network model based on a location of an object in the input image frame, and acquire score information by using the at least one neural network model, the score information indicating the aesthetic of each of the input image frames. ### Claim 19 (depends on 18) The method of claim 18, wherein the at least one neural network model further comprises a second neural network model based on how much similar an input image frame of the input image frames, is to learning data, and a third neural network model based on a type of the object and the location of the object in the input image frame. ### Claim 20 (depends on 18) The method of claim 18, wherein the plurality of lenses comprises a first lens and a second lens, and wherein the method further comprises: based on score information of a first image frame acquired through the first lens being higher than or identical to score information of a second image frame acquired through the second lens at a time point when the first image frame was acquired, selecting the first lens; and based on the score information of the first image frame being lower than the score information of the second image frame, selecting the second lens.