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公开(公告)号:US20240362897A1
公开(公告)日:2024-10-31
申请号:US18634134
申请日:2024-04-12
Applicant: NVIDIA Corporation
Inventor: Tzofi Klinghoffer , Jonah Philion , Zan Gojcic , Sanja Fidler , Or Litany , Wenzheng Chen , Jose Manuel Alvarez Lopez
IPC: G06V10/774 , G06T7/55 , G06T15/20
CPC classification number: G06V10/774 , G06T7/55 , G06T15/205 , G06T2207/10016 , G06T2207/20081 , G06T2207/20084 , G06T2207/30181 , G06T2207/30252
Abstract: In various examples, systems and methods are disclosed relating to synthetic data generation using viewpoint augmentation for autonomous and semi-autonomous systems and applications. One or more circuits can identify a set of sequential images corresponding to a first viewpoint and generate a first transformed image corresponding to a second viewpoint using a first image of the set of sequential images as input to a machine-learning model. The one or more circuits can update the machine-learning model based at least on a loss determined according to the first transformed image and a second image of the set of sequential images.
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公开(公告)号:US12125142B2
公开(公告)日:2024-10-22
申请号:US17808117
申请日:2022-06-22
Applicant: TONGJI UNIVERSITY
Inventor: Bin He , Gang Li , Runjie Shen , Bin Cheng , Zhipeng Wang , Ping Lu , Zhongpan Zhu , Yanmin Zhou , Qiqi Zhu
IPC: G06T17/05 , B64C39/02 , B64U20/87 , B64U101/30 , G01C21/16 , G01S17/86 , G01S17/89 , G05D1/00 , G06T7/73 , G06T19/20
CPC classification number: G06T17/05 , B64C39/024 , B64U20/87 , G01C21/165 , G01S17/86 , G01S17/89 , G05D1/106 , G06T7/74 , G06T7/75 , G06T19/20 , B64U2101/30 , G06T2207/10028 , G06T2207/10032 , G06T2207/30181 , G06T2219/2016
Abstract: The method includes: obtaining point cloud information collected by a depth camera, laser information collected by a lidar, and motion information of an unmanned aerial vehicle (UAV); generating a raster map based on the laser information, and obtaining pose information of the UAV based on the motion information; obtaining a map model through fusing the point cloud information, the raster map, and the pose information by a Bayesian fusion method; and correcting a latest map model by feature matching based on a previous map model.
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公开(公告)号:US20240320846A1
公开(公告)日:2024-09-26
申请号:US18731336
申请日:2024-06-02
Applicant: FURUNO ELECTRIC CO., LTD.
Inventor: Yuta TAKAHASHI
CPC classification number: G06T7/60 , G01S13/08 , G01S13/867 , G06V20/60 , H04N7/181 , G06T2207/30181
Abstract: A target monitoring device includes: a data acquiring unit, acquiring image data including a ship observed by an imaging sensor; an image recognizing unit, detecting a region of the ship included in the image data; a distance acquiring unit, acquiring a distance to the ship from an observation position detected by a sensor that is different from the imaging sensor; a course acquiring unit, acquiring a course of the ship detected by the sensor that is different from the imaging sensor; and a ship body length estimating unit, estimating a ship body length of the ship based on a dimension of the region of the ship in a horizontal direction, the distance to the ship, and the course of the ship.
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公开(公告)号:US12100179B2
公开(公告)日:2024-09-24
申请号:US17456555
申请日:2021-11-24
Applicant: Furuno Electric Co., Ltd.
Inventor: Yuya Takashima , Masahiro Minowa , Shigeaki Okumura
CPC classification number: G06T7/74 , G06V10/24 , G06T2207/20224 , G06T2207/30181
Abstract: An imaging processing device includes an image acquisition module configured to acquire an image obtained by photographing the sky with a camera having a known orientation or slant; a time stamp acquisition module configured to acquire a photographing date and time of the image; a photographing position acquisition module configured to acquire position information of a photographing position of the image; a sun position determination module configured to determine a photographed sun position in the image; a reference sun position acquisition module configured to calculate a reference sun position indicating a sun position determined based on the photographing date and time and the position information; and a camera information identification module configured to determine any one of unknown orientation and slant of the camera based on any one of the known orientation and slant of the camera, the photographed sun position, and the reference sun position.
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公开(公告)号:US20240271960A1
公开(公告)日:2024-08-15
申请号:US18644680
申请日:2024-04-24
Applicant: Samsung Electronics Co., Ltd.
Inventor: Youngjun SEO
CPC classification number: G01C21/3848 , G06T7/248 , G06T7/74 , G06T17/05 , G06V10/46 , G06V20/10 , G06T2207/30181
Abstract: An electronic device and a method of operating the same are provided. The electronic device includes a camera module, memory storing one or more computer programs, and one or more processors communicatively coupled to the memory and the camera module, wherein the one or more computer programs include computer-executable instructions that, when executed by the one or more processors, cause the electronic device to acquire an image captured by the camera module, acquire a three-dimensional map, based on location information of the electronic device, identify, in the image, a first object corresponding to a celestial body and a second object corresponding to a new terrain feature that is not included in the three-dimensional map, acquire three-dimensional image data of the new terrain feature for updating the three-dimensional map, based on information related to the second object identified based on a location of the first object, and provide a three-dimensional map updated through reflection of the acquired image data.
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公开(公告)号:US12056920B2
公开(公告)日:2024-08-06
申请号:US17574458
申请日:2022-01-12
Applicant: Woven by Toyota, Inc.
Inventor: José Felix Rodrigues
IPC: G06V20/00 , G01C21/00 , G06T7/60 , G06V10/26 , G06V10/44 , G06V10/80 , G06V10/82 , G06V20/10 , G06V20/13
CPC classification number: G06V20/182 , G01C21/3852 , G06T7/60 , G06V10/267 , G06V10/457 , G06V10/80 , G06V10/82 , G06V20/13 , G06T2207/10032 , G06T2207/20044 , G06T2207/30181 , G06T2207/30242
Abstract: A method of determining a roadway map includes receiving an image from above a roadway. The method further includes generating a skeletonized map based on the received image, wherein the skeletonized map comprises a plurality of roads. The method includes identifying intersections based on joining of multiple roads of the plurality of roads in the skeletonized map. The method includes partitioning the skeletonized map based on the identified intersections, wherein partitioning the skeletonized map defines a roadway data set and an intersection data set. The method includes analyzing the roadway data set to determine a number of lanes in each roadway of the plurality of roads. The method further includes analyzing the intersection data set to lane connections in the identified intersections. The method further includes merging results of the analyzed road data set and the analyzed intersection data set to generate the roadway map.
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公开(公告)号:US20240242331A1
公开(公告)日:2024-07-18
申请号:US18563087
申请日:2022-05-25
Applicant: INSTITUT NATIONAL DE LA SANTE ET DE LA RECHERCHE MEDICALE (INSERM) , CENTRE LEON BERARD , UNIVERSITÉ CLAUDE BERNARD LYON 1 , CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE , CENTRE HOSPITALIER NATIONAL D'OPHTALMOLOGIE QUINZE-VINGTS
Inventor: Michael ATLAN , Stefan CATHELINE , Gabrielle LALOY-BORGNA , Léo PUYO
CPC classification number: G06T7/0006 , A61B3/1241 , A61B5/4851 , A61B8/06 , A61B8/488 , G06T7/0012 , G06T2207/30104 , G06T2207/30181
Abstract: This computer-implemented method allows assessing the shear elasticity modulus of a flexible tube, such as a blood vessel. In the field of medicine, this allows assessing whether a blood vessel is at risk of breakage or tearing. In the case of an artificial tube to be implanted in a patient's body, this allows verifying that this tube is compatible with the patient's body. The method includes the following further steps: a) obtaining (1002) a first dataset relating to spatiotemporal deformations of the tube; b) detecting and storing (1004) a wall inner surface of the tube and its diameter (D); c) identifying (1006) a number of transverse sections (Sij) of the tube; d) computing (1008) an average particle velocity (Vij) over each section; e) computing (1010) a wave propagation speed (C2) of an antisymmetric wave (W2); f) based on the wave propagation speed (C2) and on the diameter (D), assessing (1012) the shear elasticity modulus (μ) of the tube.
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公开(公告)号:US20240219922A1
公开(公告)日:2024-07-04
申请号:US18558540
申请日:2022-02-01
Applicant: Sony Group Corporation
Inventor: Takuto MOTOYAMA , Kohei URUSHIDO , Masaki HANDA , Masahiko TOYOSHI , Shinichiro ABE
CPC classification number: G05D1/622 , G05D1/242 , G05D1/243 , G06T7/11 , G06T7/50 , G06V20/17 , G08G5/0069 , G05D2111/10 , G06T2207/10024 , G06T2207/10028 , G06T2207/10032 , G06T2207/30181
Abstract: The present disclosure relates to a moving body, a movement control method, and a program capable of suppressing erroneous determination in obstacle detection.
A normal vector estimation unit estimates a normal vector on the basis of sensor data obtained by sensing an object in a traveling direction of the own device, and a control information estimation unit generates control information for controlling movement of the own device on the basis of the normal vector. Technology according to the present disclosure can be applied to, for example, a moving body such as a drone.-
公开(公告)号:US20240212119A1
公开(公告)日:2024-06-27
申请号:US18392112
申请日:2023-12-21
Applicant: PETRÓLEO BRASILEIRO S.A. - PETROBAS
Inventor: Ciro Dos Santos Guimaraes , Ralph Engel Piazza
IPC: G06T7/00 , E21B47/002
CPC classification number: G06T7/0002 , E21B47/002 , E21B2200/20 , E21B2200/22 , G06T2207/20084 , G06T2207/30168 , G06T2207/30181
Abstract: The present invention relates to a method for assessing the quality of LWD (Logging While Drilling) image logs, comprising the processing of a plurality of LWD image logs; subdividing the LWD image logs into smaller pseudo-images of the same size; performing the normalization of each pseudo-image of the LWD image logs; and classifying the LWD image log according to its quality, which comprises classifying a plurality of sections of the LWD image log into three quality categories, including: good, medium or poor, using a trained neural network model for quality assessment of the LWD image log.
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公开(公告)号:US20240202962A1
公开(公告)日:2024-06-20
申请号:US18590828
申请日:2024-02-28
Applicant: Pano AI, Inc.
Inventor: Sonia Kastner , Seva Safris , Kira Greco
CPC classification number: G06T7/70 , G06V10/25 , G06V20/52 , H04N5/265 , H04N7/181 , G06T2207/30181 , G06T2207/30244 , H04W4/021
Abstract: A method includes identifying an image captured by an image capture device set at a first angle about an axis, the image corresponding to a time at which the image was captured, identifying within the image, a region of interest including an object to be used for calibration, determining, an image coordinate at which the object is displayed within the image, determining a camera angle corresponding to a position of the image capture system relative to the axis when the image was captured, identifying a bearing of the object relative to the reference direction, the bearing of the object determined using a geolocation of the image capture system and the time at which the image was captured, and determining, using the image coordinate, the camera angle, and the bearing of the object, an angular offset between the first angle and the reference direction to determine a second angle.
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