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公开(公告)号：US20220027639A1
公开(公告)日：2022-01-27
申请号：US17494682
申请日：2021-10-05
Inventor： Yingying LI , Xiao TAN , Hao SUN
Abstract: A lane line detection method, an electronic device, and a storage medium, related to the field of artificial intelligence, and particularly related to computer vision and deep learning technologies, which can be applied to intelligent traffic scenes, are provided. The method includes: dividing an image into a foreground region and a background region; determining a solid line and a dotted line included in the foreground region; determining, according to the solid line and the dotted line comprised in the foreground region, whether a dotted-and-solid line is included in the foreground region; and determining a lane line detection result according to the solid line, the dotted line, and whether a dotted-and-solid line is comprised in the foreground region. According to the technical solution, the accuracy of lane line detection can be improved.
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公开(公告)号：US20230030431A1
公开(公告)日：2023-02-02
申请号：US17963865
申请日：2022-10-11
Inventor： Yingying LI , Xiao TAN , Hao SUN
Abstract: A method for extracting a feature includes: acquiring a predicted object segmentation annotation image of a (T-1)-th frame in a video and a pixel-level feature map of a T-th frame in the video, T being a positive integer greater than 2; performing respectively feature mapping on the predicted object segmentation annotation image of the (T-1)-th frame and the pixel-level feature map of the T-th frame, to obtain a mapping feature map of the (T-1)-th frame and a mapping feature map of the T-th frame; and performing a convolution on the mapping feature map of the T-th frame using a convolution kernel of the mapping feature map of the (T-1)-th frame, to obtain a score map of the T-th frame.
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3.发明申请公开(公告)号：US20230005272A1
公开(公告)日：2023-01-05
申请号：US17944742
申请日：2022-09-14
Inventor： Yingying LI , Xiao TAN , Hao SUN
Abstract: The present disclosure provides a method and apparatus for detecting a traffic anomaly, a device, a storage medium and a computer program product, relates to the field of artificial intelligence, and specifically to computer vision and deep learning technologies, and can be applied to intelligent transportation scenarios. A specific implementation of the method comprises: acquiring a traffic video stream; performing vehicle detection tracking on the traffic video stream to determine whether there is an abnormally stopped vehicle, wherein a stop with a time length exceeding a preset time length belongs to an abnormal stop; and performing a traffic anomaly classification on a video frame corresponding to the abnormal stop using a decision tree to obtain a traffic anomaly type, if there is the abnormally stopped vehicle, wherein the decision tree is generated based on features for a traffic anomaly detection.
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4.发明申请公开(公告)号：US20220375118A1
公开(公告)日：2022-11-24
申请号：US17880931
申请日：2022-08-04
Inventor： Yingying LI , Xinyi DAI , Xiao TAN , Hao SUN
Abstract: Provided is a method and apparatus for identifying a vehicle cross-line. The method may include: determining, in each road condition image of a plurality of road condition images, position information of a target lane line and position information of a target vehicle; determining, based on the position information of the target lane line and the position information of the target vehicle, a relative positional relationship between the target vehicle and the target lane line corresponding to the each road condition image; and determining that the target vehicle crosses the line, if the relative positional relationships corresponding to the plurality of road condition images meet a preset condition.
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