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公开(公告)号：US20150235378A1
公开(公告)日：2015-08-20
申请号：US14611824
申请日：2015-02-02
Applicant: Samsung Electronics Co., Ltd.
Inventor： Seon Min RHEE , Seung In PARK , Yong Beom LEE , Hyong Euk LEE
CPC classification number: G06T19/006 , G06F3/0346 , G06F3/04815 , G06T7/73 , G06T15/20 , G06T2200/04 , G06T2207/10012 , G06T2207/10024 , G06T2207/10028 , G06T2207/30244
Abstract: An apparatus for estimating a camera pose includes an image acquisition unit to acquire a photographed image, a motion sensor to acquire motion information of the apparatus for estimating the camera pose, a static area detector to detect a static area of the photographed image based on the photographed image and the motion information, and a pose estimator to estimate a camera pose based on the detected static area.
Abstract translation: 一种用于估计摄像机姿势的装置，包括获取拍摄图像的图像获取单元，用于获取用于估计摄像机姿态的装置的运动信息的运动传感器，基于该摄像机姿态来检测拍摄图像的静态区域的静态区域检测器 拍摄图像和运动信息，以及姿势估计器，用于基于检测到的静态区域估计相机姿态。
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42.发明申请ELECTRONIC DEVICE INCLUDING TRANSPARENT DISPLAY AND METHOD OF CONTROLLING THE ELECTRONIC DEVICE 有权包括透明显示器的电子设备和控制电子设备的方法公开(公告)号：US20150154801A1
公开(公告)日：2015-06-04
申请号：US14551478
申请日：2014-11-24
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Yong Beom LEE , Seon Min RHEE , Hyong Euk LEE
CPC classification number: G06F3/013 , G06T11/00 , G06T2210/62 , G09G3/003 , G09G2320/028 , G09G2354/00
Abstract: Provided are an electronic device including a transparent display and a method of controlling the electronic device, the method including acquiring a first image based on an optical display mode in which light incident from an object is transmitted; acquiring a second image based on a video display mode in which an image captured from the object is displayed; and displaying the first image and the second image on the transparent display by mixing the first image and the second image.
Abstract translation: 提供了一种包括透明显示器和控制电子设备的方法的电子设备，该方法包括：基于从物体发射光的光学显示模式获取第一图像; 基于显示从对象拍摄的图像的视频显示模式获取第二图像; 以及通过混合第一图像和第二图像在透明显示器上显示第一图像和第二图像。
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43.发明申请公开(公告)号：US20130253869A1
公开(公告)日：2013-09-26
申请号：US13666518
申请日：2012-11-01
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Sang Hyun KIM , Hyong Euk LEE , Chang Kyu CHOI
CPC classification number: G01C25/00 , G01C15/002 , G01S5/021 , G01S5/0252 , G01S5/04 , G01S5/16
Abstract: Provided is a calibration apparatus and method of a three-dimensional (3D) position and direction estimation system. The calibration apparatus may receive inertia information and intensity information during a predetermined period of time, may calculate distances between a transmitter and the respective receivers, and may calibrate a signal attenuation characteristic of each receiver using the distances between the transmitter and the respective receivers.
Abstract translation: 提供了一种三维（3D）位置和方向估计系统的校准装置和方法。 校准装置可以在预定时间段期间接收惯性信息和强度信息，可以计算发射机和相应接收机之间的距离，并且可以使用发射机和各个接收机之间的距离校准每个接收机的信号衰减特性。
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公开(公告)号：US20250133299A1
公开(公告)日：2025-04-24
申请号：US18816848
申请日：2024-08-27
Applicant: Samsung Electronics Co., Ltd.
Inventor： Kinam KWON , Seo hee SO , Hyochul KIM , Sungmo AHN , Hyong Euk LEE
Abstract: A machine-perspective signal processing method and apparatus are provided. The machine-perspective signal processing method includes selecting a first sensor from among a plurality of sensors, processing output data of the first sensor using first sensor-specific signal processing having a first individual setting specialized for the first sensor and sensor-agnostic signal processing having a common setting of the plurality of sensors, and performing a first task based on the processed output data.
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公开(公告)号：US20250069210A1
公开(公告)日：2025-02-27
申请号：US18441680
申请日：2024-02-14
Applicant: Samsung Electronics Co., Ltd.
Inventor： Sangwon LEE , Nagyeong LEE , Hana LEE , Myungsub CHOI , Hyong Euk LEE
Abstract: A method of determining a focal length and an electronic device that performs the method are provided. The electronic device includes a processor, a camera comprising a lens, and a memory configured to store one or more instructions executable by the processor. The processor is configured to receive a plurality of original images with the lens in response to the one or more instructions being executed, generate a composite image based on the plurality of original images, and determine a focal length of the lens by inputting one or more original images of the plurality of original images and the composite image to an autofocus (AF) model.
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Patent Agency Ranking
公开(公告)号：US20240054606A1
公开(公告)日：2024-02-15
申请号：US18337774
申请日：2023-06-20
Applicant: Samsung Electronics Co., Ltd.
Inventor： Geonseok SEO , Sehwan KI , Jae Seok CHOI , Insoo KIM , Hyong Euk LEE
CPC classification number: G06T5/001 , G06T5/50 , G06T2207/20084
Abstract: A processor-implemented method includes: obtaining a plurality of image frames acquired for a scene within a predetermined time; determining loss values respectively corresponding to the plurality of image frames; determining a reference frame among the plurality of image frames based on the loss values; and generating a final image of the scene based on the reference frame.
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公开(公告)号：US20240020808A1
公开(公告)日：2024-01-18
申请号：US18091239
申请日：2022-12-29
Applicant: SAMSUNG ELECTRONICS CO., LTD.
Inventor： Jaehyoung YOO , Kinam KWON , Junsang YU , Hyong Euk LEE
CPC classification number: G06T5/50 , G06T5/20 , G06T2207/20084 , G06T2207/20224 , G06T2207/20024
Abstract: An image restoration method and apparatus are provided. The image restoration method includes determining auxiliary data corresponding to a plurality of filter kernels by filtering target data with the plurality of filter kernels, determining new input data by combining the auxiliary data with at least some input data of layers of a neural network-based image restoration model, generating, based on the new input data, a restored image of the input image by executing the neural network-based image restoration model, wherein the filter kernels are not part of the neural network-based image restoration model.
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公开(公告)号：US20230071693A1
公开(公告)日：2023-03-09
申请号：US17869165
申请日：2022-07-20
Applicant: Samsung Electronics Co., Ltd.
Inventor： Eunhee KANG , Sehwan KI , Nahyup KANG , Kinam KWON , Hyong Euk LEE , Jae Seok CHOI
IPC: G06T5/00
Abstract: A processor-implemented method with degraded image restoration includes: receiving a degraded training image; training a first teacher network of an image restoration network and a second teacher network of the image restoration network to infer differential images corresponding to the degraded training image, wherein each of the first teacher network and the second teacher network comprises a differentiable activation layer and a performance of the first teacher network is greater than that of the second teacher network; initially setting a student network of the image restoration network based on the second teacher network; and training the student network to infer a differential image corresponding to the degraded training image by iteratively backpropagating, to the student network, a contrastive loss that decreases a first difference between a third output of the student network and a first output of the first teacher network and increases a second difference between the third output and a second output of the second teacher network.
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公开(公告)号：US20220292635A1
公开(公告)日：2022-09-15
申请号：US17402906
申请日：2021-08-16
Applicant: Samsung Electronics Co., Ltd. , Industry-Academic Cooperation Foundation, Yonsei University
Inventor： Nahyup KANG , Seon Joo KIM , DongYoung KIM , JinWoo KIM , Yeonkyung LEE , Byung In YOO , Hyong Euk LEE
Abstract: A method and apparatus with image correction is provided. A processor-implemented method includes generating, using a neural network model provided an input image, an illumination map including illumination values dependent on respective color casts by one or more illuminants individually affecting each pixel of the input image, and generating a white-adjusted image by removing at least a portion of the color casts from the input image using the generated illumination map.
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公开(公告)号：US20220237744A1
公开(公告)日：2022-07-28
申请号：US17380648
申请日：2021-07-20
Inventor： Kinam KWON , Heewon KIM , Kyoung Mu LEE , Hyong Euk LEE
Abstract: A method with image restoration includes: receiving an input image and a first task vector indicating a first image effect among candidate image effects; extracting a common feature shared by the candidate image effects from the input image, based on a task-agnostic architecture of a source neural network; and restoring the common feature to a first restoration image corresponding to the first image effect, based on a task-specific architecture of the source neural network and the first task vector.
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