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公开(公告)号：US20230298362A1
公开(公告)日：2023-09-21
申请号：US17698721
申请日：2022-03-18
Applicant: HERE Global B.V.
Inventor： Zhenhua ZHANG , Qi MAO , Xiaoying JIN , Lin GAN , Sanjay Kumar BODDHU
CPC classification number: G06V20/588 , G06T7/60 , G06T2207/30256
Abstract: An approach is provided for lane width estimation from incomplete lane marking detections of a road lane. The approach, for example, involves generating one or more perpendicular lines respectively from location centers of one or more first lane marking detections. A respective lane marking detection represents at least a portion of a boundary of the road lane as a line delimited by two location data points in accordance with detections by at least one sensor device onboard at least one vehicle. The approach also involves identifying second lane marking detections that each respectively intersect one of the one or more perpendicular lines. The approach further involves selecting one or more candidate lane widths based on one or more respective distances from the location centers to the second lane marking detections. The approach further involves determining an estimated lane width of the road lane based on the one or more candidate lane widths.
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公开(公告)号：US20250054269A1
公开(公告)日：2025-02-13
申请号：US18232107
申请日：2023-08-09
Applicant: HERE Global B.V.
Inventor： Hai YU , Xiaoying JIN , Amey AROSKAR
Abstract: An approach is provided for generating feature data. The approach, for example, involves determining a set of break points associated with at least one road feature based on mask image data. The mask image data is associated with overhead image data comprising the at least one road feature. The approach further involves generating a set of cropped feature maps based on processing of a global feature map obtained from a global feature segmentation model and the set of break points. The global feature map is associated with the overhead image data. The approach further involves generating the feature data associated with the at least one road feature based on application of a local feature detection model on the generated set of cropped feature maps and the set of break points. The approach further involves storing the generated feature data in a geographic database.
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Patent Agency Ranking
公开(公告)号：US20230266142A1
公开(公告)日：2023-08-24
申请号：US17678597
申请日：2022-02-23
Applicant: HERE Global B.V.
Inventor： Zhenhua ZHANG , Qi MAO , Lin GAN , Xiaoying JIN , Sanjay Kumar BODDHU
IPC: G01C21/00
CPC classification number: G01C21/3822 , G01C21/3859
Abstract: An approach is provided for reconstructing a road linear feature. The approach, for example, involves receiving two or more linear feature detections that respectively represent a linear feature of a road as a line segment delimited by two feature points. The approach also involves map matching the two or more linear feature detections to a road link segment of a geographic database. The approach further involves determining an orientation difference for each of the two or more linear feature detections based on an angle difference between each linear feature detection and a link orientation of the map matched road link segment. The approach further involves determining a feature orientation of the linear feature based on an aggregation of the orientation difference for each linear feature detection. The approach further involves constructing a representation of the linear feature based at least in part on the feature orientation.
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公开(公告)号：US20240355086A1
公开(公告)日：2024-10-24
申请号：US18137174
申请日：2023-04-20
Applicant: HERE Global B.V.
Inventor： Yu HAI , Xiaoying JIN
CPC classification number: G06V10/60 , G06T7/11 , G06T7/187 , G06T7/40 , G06V10/25 , G06V10/44 , G06V20/13 , G06V20/17 , G06T2207/10024
Abstract: An approach is provided for detecting road features. The approach, for example, involves receiving image data associated with one or more road features. The received image data may be associated with ground truth label data corresponding to the one or more road features. The approach further involves determining a set of shadowed regions from one or more images of the received image data. The approach further involves generating artificial shadow data based on the determined set of shadowed regions. The approach further involves augmenting the image data with the generated artificial shadow data by applying the generated artificial shadow data to the received image data. The approach further involves training a machine learning (ML) model based on the augmented image data and the ground truth label data. The ML model is trained to detect the one or more road features.
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公开(公告)号：US20230206625A1
公开(公告)日：2023-06-29
申请号：US17853445
申请日：2022-06-29
Applicant: HERE Global B.V.
Inventor： Robert LEDNER , Xiaoying JIN , Holly RUSSELL , Joseph TANKOVICH
CPC classification number: G06V20/176 , G06V10/82 , G01C11/08
Abstract: An approach is provided for pole extraction from optical imagery. The approach involves, for instance, processing a plurality of images using a machine learning model to generate a plurality of redundant observations of a pole-like object and/or their semantic keypoints respectively depicted in the plurality of images. The approach also involves performing a photogrammetric triangulation of the plurality of redundant observations to determine three-dimensional coordinate data of the pole-like object and/or their semantic keypoints. The approach further involves providing the three-dimensional coordinate data of the pole-like object as an output.
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公开(公告)号：US20230206584A1
公开(公告)日：2023-06-29
申请号：US17853464
申请日：2022-06-29
Applicant: HERE Global B.V.
Inventor： Xiaoying JIN , Robert LEDNER , Holly RUSSELL , Joseph TANKOVICH
CPC classification number: G06V10/255 , G06T7/70 , G06T7/60 , G06V20/17
Abstract: An approach is provided for pole extraction from a single image. The approach involves, for instance, processing an image using a machine learning model to detect one or more semantic keypoints associated with a pole-like object and to determine two-dimensional coordinate data for the one or more semantic keypoints. The approach also involves performing a monocular depth estimation to determine depth information for the one or more semantic keypoints based on the image. The approach further involves determining three-dimensional coordinate data for the one or more semantic keypoints based on the monocular depth information, the two-dimensional coordinate data, and camera parameter data. The approach yet further involves providing the three-dimensional coordinate data as an output.
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公开(公告)号：US20240219195A1
公开(公告)日：2024-07-04
申请号：US18090082
申请日：2022-12-28
Applicant: HERE Global B.V.
Inventor： Zhenhua ZHANG , Xiaoying JIN
CPC classification number: G01C21/3815 , G06F16/285 , G06F16/29
Abstract: The disclosure provides a system, a method, and a computer program product for optimization of lane data. The system may be configured to categorize each location of a set of locations included in the lane data of each lane marking of the plurality of lane markings, into at least one of: a first area or a second area of a topological area. The system may further determine the lane data of each lane marking to be in at least one of: a first group, a second group or a third group, based on each categorized location of the set of locations. The system may further process the lane data associated with each lane marking of the plurality of lane markings based on the determined first group, the second group or the third group.
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