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公开(公告)号：US20220148184A1
公开(公告)日：2022-05-12
申请号：US17094501
申请日：2020-11-10
Applicant: HERE Global B.V.
Inventor： Souham BISWAS , Sanjay Kumar BODDHU
Abstract: An approach is provided for using a machine learning model for identifying planar region(s) in an image. The approach involves, for example, determining the model for performing image segmentation. The model comprises at least: a trainable filter that convolves the image to generate an input volume comprising a projection of the image at different resolution scales; and feature(s) to identify image region(s) having a texture within a similarity threshold. The approach also involves processing the image using the model by generating the input volume from the image using the trainable filter and extracting the feature(s) from the input volume to determine the region(s) having the texture. The approach further involves determining the planar region(s) by clustering the image regions. The approach further involves generating a planar mask based on the planar region(s). The approach further involves providing the planar mask as an output of the image segmentation.
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Patent Agency Ranking
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：US20220276618A1
公开(公告)日：2022-09-01
申请号：US17637361
申请日：2020-08-28
Applicant: HERE Global B.V.
Inventor： Amey AROSKAR , Sanjay Kumar BODDHU , Luke SMORON , Erika RODWELL
Abstract: An approach is provided for providing dynamic model switching and/or model parameter switching (e.g., for object detection). The approach, for example, involves providing a plurality of machine learning models trained to detect one or more objects (e.g., vehicles, pedestrians, etc.) and/or road attributes (e.g., road hazards, road furniture, road signs, etc.). The approach also involves processing sensor data to determine at least one context (e.g., location), at least one use of the one or more road attributes, or a combination thereof. The approach further involves selecting at least one machine learning model of the plurality of machine learning models based on at least one context. The approach further involves providing the selected at least one machine learning model to detect the one or more objects and/or road attributes.
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4.发明公开公开(公告)号：US20240344846A1
公开(公告)日：2024-10-17
申请号：US18133343
申请日：2023-04-11
Applicant: HERE Global B.V.
Inventor： Landis HUFFMAN , Nilesh KADAM , Dennis Scott WILLIAMSON , Roberto RAGGI , James D. LYNCH , Prasad KAVURI , Shishir B. SAXENA , Sanjay Kumar BODDHU
IPC: G01C21/00
CPC classification number: G01C21/3844
Abstract: An approach is provided for generating synthetic ground truth drive and sensor observation data. The approach, for instance, receiving, by a processor, a first input specifying ground truth data indicating one or more ground truth locations of one or more map features. The approach also involves receiving a second input specifying one or more simulation characteristics. The approach further involves generating simulated drive data based on the ground truth data and the one or more simulation characteristics. For example, the simulated drive data includes (a) one or more simulated drive paths within a region of interest encompassing the one or more ground truth locations and (b) one or more simulated sensor observations of the one or more map features. The approach further involves providing the simulated drive data as an output.
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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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6.发明申请公开(公告)号：US20210019897A1
公开(公告)日：2021-01-21
申请号：US16511892
申请日：2019-07-15
Applicant: HERE GLOBAL B.V.
Inventor： Souham BISWAS , Sanjay Kumar BODDHU
Abstract: An approach is provided for estimating a real-world depth information from a monocular image. The approach, for example, involves determining a vanishing point of the monocular image captured by a camera. The approach also involves generating a vanishing point ray from an optical center of the camera through the vanishing point on an image plane of the monocular image to infinity. The approach further involves generating a center line ray from the optical center through a geometric center of the image plane to a feature line that is parallel to the vanishing point ray at a lateral distance. The approach further involves generating a feature ray from the optical center through a location of the feature on the image plane to the feature line. The approach further involves computing the real-world distances of the feature based on image coordinates of the rays, lines, angles derived therefrom, and a known pixel-wise distance of the monocular image.
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