公开(公告)号：US11915375B2

公开(公告)日：2024-02-27

申请号：US18166075

申请日：2023-02-08

Applicant: Meta Platforms Technologies, LLC

Inventor： Alexandru-Eugen Ichim ,  Matthew James Alderman ,  Alexander Sorkine Hornung ,  Manuel Werlberger ,  Gaurav Chaurasia ,  Jan Oberländer

IPC: G06T19/00 ,  G06T7/593

CPC classification number: G06T19/003 ,  G06T7/593 ,  G06T2207/10012

Abstract: In particular embodiments, a computing system may divide at least a portion of a physical space surrounding a user into a plurality of three-dimensional (3D) regions, wherein each of the 3D regions is associated with an area of a plurality of areas in a plane. The system may generate estimated locations of features of objects in the portion of the physical space. Based on the estimated locations, the system may determine an occupancy state of each of the plurality of 3D regions. Then based on the occupancy states of the plurality of 3D regions, the system may determine that one or more of the plurality of areas have respective airspaces that are likely unoccupied by objects.

公开(公告)号：US20240059295A1

公开(公告)日：2024-02-22

申请号：US18498370

申请日：2023-10-31

Applicant: NVIDIA Corporation

Inventor： Minwoo Park ,  Yue Wu ,  Cheng-Chieh Yang

IPC: B60W40/02 ,  G06T7/30 ,  G06T7/80 ,  H04N13/296 ,  H04N13/271 ,  G06T15/10 ,  G06V20/58 ,  B60W60/00 ,  G06T7/593

CPC classification number: B60W40/02 ,  G06T7/30 ,  G06T7/85 ,  H04N13/296 ,  H04N13/271 ,  G06T15/10 ,  G06V20/58 ,  B60W60/001 ,  G06T7/593 ,  B60W2420/42 ,  G06T2207/10012 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/20132 ,  G06T2207/20228 ,  G06T2207/30261 ,  G06T2207/30244

Abstract: In various examples, systems and methods are disclosed that detect hazards on a roadway by identifying discontinuities between pixels on a depth map. For example, two synchronized stereo cameras mounted on an ego-machine may generate images that may be used extract depth or disparity information. Because a hazard's height may cause an occlusion of the driving surface behind the hazard from a perspective of a camera(s), a discontinuity in disparity values may indicate the presence of a hazard. For example, the system may analyze pairs of pixels on the depth map and, when the system determines that a disparity between a pair of pixels satisfies a disparity threshold, the system may identify the pixel nearest the ego-machine as a hazard pixel.

公开(公告)号：US11908070B2

公开(公告)日：2024-02-20

申请号：US17427877

申请日：2020-02-03

Applicant: Olivier Querbes ,  Véronique Querbes-Duret

Inventor： Olivier Querbes ,  Véronique Querbes-Duret

IPC: G06T17/00 ,  G06T7/593 ,  G06T7/90

CPC classification number: G06T17/00 ,  G06T7/593 ,  G06T7/90 ,  G06T2207/10024 ,  G06T2207/10028 ,  G06T2207/20081

Abstract: Disclosed is a dynamic three-dimensional imaging method that allows the generation of a three-dimensional numerical model that represents an observed three-dimensional scene. The generated model optimally combines (404) data from two intermediate three-dimensional numerical models, respectively obtained by a stereoscopic three-dimensional reconstruction calculation method (402) and by a method of three-dimensional reconstruction calculation through learning (403). In addition, each new model that is generated helps to improve the overall performance of the method of three-dimensional reconstruction calculation by learning.

公开(公告)号：US11900619B2

公开(公告)日：2024-02-13

申请号：US17422446

申请日：2020-06-29

Applicant: ZHONGYUAN UNIVERSITY OF TECHNOLOGY

Inventor： Xiaowei Song ,  Lei Yang ,  Menglong Li ,  Jianlei Xia ,  Shan Li ,  Yiping Chang

IPC: G06T7/62 ,  G06T7/80 ,  G06T7/73 ,  G06T7/593 ,  H04N13/246 ,  H04N13/239 ,  G06V20/54 ,  G06V10/44 ,  G06V10/82 ,  G06V20/40 ,  G06V10/75 ,  G06N3/04 ,  G06N3/08 ,  G08G1/017 ,  G08G1/056 ,  G06F18/213 ,  H04N23/60 ,  G06T7/285

CPC classification number: G06T7/285 ,  G06F18/213 ,  G06N3/04 ,  G06N3/08 ,  G06T7/593 ,  G06T7/62 ,  G06T7/75 ,  G06T7/85 ,  G06V10/449 ,  G06V10/757 ,  G06V10/82 ,  G06V20/41 ,  G06V20/54 ,  G08G1/0175 ,  G08G1/056 ,  H04N13/239 ,  H04N13/246 ,  H04N23/64 ,  G06T2207/10021 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30241 ,  G06T2207/30244

Abstract: The invention provides a method for intelligently measuring vehicle trajectory based on a binocular stereo vision system, including the following steps: inputting a dataset into an SSD (Single Shot Multibox Detector) neural network to train a license plate recognition model; calibrating the binocular stereo vision system, and recording videos of moving target vehicles; detecting the license plates in the video frames with the license plate recognition model; performing stereo matching on the license plates in the subsequent frames of the same camera and in the corresponding left-view and right-view video frames by a feature-based matching algorithm; reserving correct matching point pairs after filtering with a homography matrix; screening the reserved matching point pairs, and reserving the one closest to the license plate center as the position of the target vehicle in the current frame; performing stereo measurement on the screened and reserved matching point pairs to get the spatial position coordinates of the vehicle in the video frames; and generating the moving trajectory of the vehicle in time sequence. The present invention is easy to install and adjust, and can simultaneously measure multiple target vehicles in multiple directions and on multiple lanes.

公开(公告)号：US20240046575A1

公开(公告)日：2024-02-08

申请号：US18135985

申请日：2023-04-18

Applicant: Samsung Electronics Co., Ltd.

Inventor： Yingen Xiong

IPC: G06T19/00 ,  H04N13/239 ,  G06T7/80 ,  G06T7/593 ,  H04N13/111

CPC classification number: G06T19/006 ,  H04N13/239 ,  G06T7/85 ,  G06T7/593 ,  H04N13/111 ,  H04N2013/0081

Abstract: In one embodiment, a method includes capturing, using a pair of cameras of a video see-through AR system, stereo images of a predetermined calibration object having a predetermined pose and obtaining, by a position sensor, position data for each of the pair of cameras at a time when the stereo images are captured. The method further includes generating a 3D reconstruction of the calibration object. The method further includes performing a registration process by generating, using parameters of each of a pair of stereo virtual cameras, stereo virtual views that include the predetermined calibration object and determining, for each of the stereo virtual views, one or more differences between the predetermined calibration object in the virtual images and a virtual rendering of the calibration object, and then using those differences to either adjust the virtual-camera parameters and repeat the registration process or to store the parameters for the system.

公开(公告)号：US11889047B2

公开(公告)日：2024-01-30

申请号：US17220095

申请日：2021-04-01

Applicant: SUBARU CORPORATION

Inventor： Minoru Kuraoka

IPC: G06T7/593 ,  H04N13/239 ,  G06V20/64 ,  G06V20/56 ,  G06V10/25 ,  G06V10/75

CPC classification number: H04N13/239 ,  G06T7/593 ,  G06V10/25 ,  G06V10/751 ,  G06V20/56 ,  G06V20/64 ,  G06T2207/10012 ,  G06T2207/30252 ,  G06V2201/08

Abstract: An image processing device includes a detector, a setting unit, a calculator, an estimator, and a determining unit. The detector sets a three-dimensional object region by detecting a three-dimensional object. The setting unit sets a first image region corresponding to the three-dimensional object region, a second image region including a left end of and partly overlapping the first image region, and a third image region including a right end of and partly overlapping the first image region. The calculator calculates representative values of parallax-related values in pixel columns in the image regions, and calculates an approximate line of the representative values in each of the image regions. The estimator estimates a continuous structure degree, from a slope value of the approximate line of each of the image regions. The determining unit determines whether the three-dimensional object is a vehicle, from the continuous structure degree.

公开(公告)号：US20240029288A1

公开(公告)日：2024-01-25

申请号：US18350799

申请日：2023-07-12

Applicant: CANON KABUSHIKI KAISHA

Inventor： Miki WAKUI

IPC: G06T7/593 ,  G06T7/80

CPC classification number: G06T7/593 ,  G06T7/85 ,  G06T2207/10012

Abstract: An image processing apparatus obtains a first captured image from a first image capturing device and a second captured image from a second image capturing device, and a first image capturing parameter in capturing the first captured image and a second image capturing parameter in capturing the second captured image. Three-dimensional shape data indicating a shape of an object image-captured by the first and second image capturing devices is obtained. Parallax information on the first and second captured images is obtained based on a search point included in the first captured image and a corresponding point corresponding to the search point and included in the second captured image. A search target region limiting a range of a pixel set as the search point is set in the first captured image based on the first and second image capturing parameters and the three-dimensional shape data.

公开(公告)号：US20240029287A1

公开(公告)日：2024-01-25

申请号：US18244516

申请日：2023-09-11

Applicant: Imagination Technologies Limited

Inventor： Ruan Lakemond ,  Timothy Smith

IPC: G06T7/593 ,  G06T7/73 ,  G06V20/10 ,  G06F18/22

CPC classification number: G06T7/593 ,  G06T7/73 ,  G06V20/10 ,  G06F18/22 ,  G06T2207/20164 ,  G06V10/443

Abstract: A method of feature matching in images captured from camera viewpoints uses the epipolar geometry of the viewpoints to define a geometrically-constrained region in a second image corresponding to a first feature in a first image; comparing the local descriptor of the first feature with local descriptors of features in the second image to determine respective measures of similarity; identifying, from the features located in the geometrically-constrained region, (i) a geometric best match and (ii) a geometric next-best match to the first feature; identifying a global best match to the first feature; performing a first comparison of the measures of similarity for the geometric best match and the global best match; performing a second comparison of the measures of similarity for the geometric best match and the geometric next-best match; and, if thresholds are met, selecting the geometric best match feature in the second image.

公开(公告)号：US11880993B2

公开(公告)日：2024-01-23

申请号：US16285105

申请日：2019-02-25

Applicant: TOSHIBA ELECTRONIC DEVICES & STORAGE CORPORATION ,  KABUSHIKI KAISHA TOSHIBA

Inventor： Yutaka Oki

IPC: H04N13/128 ,  G06T7/593 ,  G06T7/80 ,  G06T7/174 ,  G06V20/56 ,  B60R1/00 ,  H04N13/00

CPC classification number: G06T7/593 ,  G06T7/174 ,  G06T7/85 ,  G06V20/588 ,  H04N13/128 ,  B60R1/00 ,  B60R2300/105 ,  B60R2300/107 ,  B60R2300/30 ,  G06T2207/10012 ,  G06T2207/30256 ,  H04N2013/0081

Abstract: An image processing device used in determining a distance to an object includes a memory that stores a stereo image of the object including first and second images, and a processor configured to detect first and second reference lines in the first image, calculate disparity between the first and second images, correct, using the calculated disparity, a position of the first reference line in the second image, and calculate a parameter for determining the distance to the object, the parameter indicating a difference between the first and second images based on a distance between the first and second reference lines in the first image and disparity between the first reference line in the first image and the corrected first reference line in the second image.

公开(公告)号：US11880935B2

公开(公告)日：2024-01-23

申请号：US17951405

申请日：2022-09-23

Applicant: SHANGHAITECH UNIVERSITY

Inventor： Minye Wu ,  Jingyi Yu

IPC: G06T17/00 ,  G06V10/82 ,  G06F18/214 ,  G06F18/213 ,  G06T15/04 ,  G06T15/20 ,  G06T17/20 ,  G06V20/64 ,  G06T7/593 ,  H04N13/207

CPC classification number: G06T17/00 ,  G06F18/213 ,  G06F18/214 ,  G06T7/593 ,  G06T15/04 ,  G06T15/205 ,  G06T17/20 ,  G06V10/82 ,  G06V20/653 ,  H04N13/207 ,  G06T2200/08 ,  G06T2207/10016 ,  G06T2207/10024 ,  G06T2207/10028 ,  G06T2207/20081 ,  G06T2207/20084 ,  G06T2207/30196 ,  G06T2210/56

Abstract: An image-based method of modeling and rendering a three-dimensional model of an object is provided. The method comprises: obtaining a three-dimensional point cloud at each frame of a synchronized, multi-view video of an object, wherein the video comprises a plurality of frames; extracting a feature descriptor for each point in the point cloud for the plurality of frames without storing the feature descriptor for each frame; producing a two-dimensional feature map for a target camera; and using an anti-aliased convolutional neural network to decode the feature map into an image and a foreground mask.