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公开(公告)号：US20200023973A1
公开(公告)日：2020-01-23
申请号：US16404180
申请日：2019-05-06
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Abstract: The present disclosure provides a UAV operation route planning method, a UAV pesticide spreading planning method and device for providing improvements on the operation accuracy of UAV. The UAV operation route method comprises steps of: obtaining a plurality of sub-areas of an operation area of a UAV; exhausting operation orders of the sub-areas and waypoint sequences in each of the sub-areas, respectively; planning routes according to the operation orders of the sub-areas and the waypoint sequences in each of the sub-areas to obtain all routes in the operation area; and determining a route in all the routes having a total voyage meeting a preset constraint condition as an optimal operation route.
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12.发明申请公开(公告)号：US20190088011A1
公开(公告)日：2019-03-21
申请号：US15986947
申请日：2018-05-23
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Abstract: The present disclosure provides a method, a device, a terminal, a system and a vehicle for visualization of vehicle's blind spot. The method includes: acquiring real-time image data in front of the vehicle; creating a Three-Dimension (3D) map with the acquired image data; determining a current location of the vehicle in the 3D map; acquiring the relative location information between the driver and the sight-blocking object that blocks the vision of the driver; determining the blind spot in the vision of the driver in connection with structure information of the sight-blocking object and the relative location information between the driver and the sight-blocking object that blocks the vision of the driver; and determining environmental information of the blind spot in the vision in accordance with the 3D map, the current location of the vehicle in the 3D map and the blind spot in the vision of the driver.
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Patent Agency Ranking
公开(公告)号：US20240046647A1
公开(公告)日：2024-02-08
申请号：US17642003
申请日：2021-03-24
Applicant: BOE Technology Group Co., Ltd.
Inventor： Tong LIU
CPC classification number: G06V20/52 , G06V40/10 , G06V10/751 , G06V10/28 , G06V10/457 , G06T7/73 , G06V10/273 , G06T2207/30232 , G06T2207/10016 , G06V2201/07
Abstract: The present disclosure discloses a method, apparatus and device for detecting obstacles, and a computer storage medium, which belong to the field of security monitoring. The method includes: by performing object detection and pedestrian detection on a monitored image of a monitored region, an object identification group including an object identification box and a pedestrian identification box are acquired, and upon removing an object identification box associated with the pedestrian identification box, that an obstacle is present in the monitored region based on the object identification box in the object identification group is determined. False warning caused by presence of pedestrians in the monitored region can be avoided. The problem of low accuracy of methods for detecting obstacles in the related art can be solved, and the effect of improving the accuracy of the method for detecting obstacles can be achieved.
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公开(公告)号：US20210342606A1
公开(公告)日：2021-11-04
申请号：US17263537
申请日：2020-04-30
Applicant: BOE Technology Group Co., Ltd.
Inventor： Tong LIU
Abstract: A parking detection method, a system, a processing device and a storage medium are provided. The parking detection method includes: acquiring an image to be detected; acquiring a projection area of a vehicle on the ground according to vanishing points and a vanishing line in the image to be detected in combination with outline key points of the vehicle in the image to be detected; judging whether the vehicle is parked regularly.
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公开(公告)号：US20210334574A1
公开(公告)日：2021-10-28
申请号：US16498750
申请日：2019-04-03
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Inventor： Huanhuan ZHANG , Tong LIU , Yifei ZHANG , Xiaojun TANG
Abstract: A commodity detection terminal is disclosed, the commodity detection terminal includes: an image segmentation unit configured to obtain position information of each grid of a goods shelf in an image of the goods shelf based on a first image, which is an image of the goods shelf not placed with commodities; a detector unit configured to obtain a current grid where each commodity is located and a current quantity of each commodity based on a second image, which is a current image of the goods shelf placed with commodities; and a determination unit configured to compare the current grid and the current quantity with a preset grid and a preset quantity of the each commodity, so as to determine whether a status of each commodity satisfies a preset condition. A commodity detection method, an intelligent goods shelf system, a computer device, and a readable medium are also disclosed.
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公开(公告)号：US20210334533A1
公开(公告)日：2021-10-28
申请号：US16481542
申请日：2019-01-02
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Inventor： Tong LIU , Xiangyang LIU , Zhiguo ZHANG , Hui RAO
Abstract: An object identification method and an object identification device, the object identification method comprises: capturing color images and depth images that are aligned; performing motion detection on the captured color images and depth images to acquire a motion start frame and a motion end frame; comparing the motion end frame with the motion start frame in the color images to acquire a set of motion pixels; performing connected component analysis on the acquired set of motion pixels to obtain at least one connected component; and identifying an object in the at least one connected component.
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公开(公告)号：US20200320736A1
公开(公告)日：2020-10-08
申请号：US16904800
申请日：2020-06-18
Applicant: BOE TECHNOLOGY GROUP CO., LTD.
Inventor： Huanhuan ZHANG , Tong LIU , Yifei ZHANG , Xiaojun TANG
Abstract: The present disclosure provides an image processing method, device and apparatus, and a computer-readable storage medium. The image processing method includes: obtaining an image and detecting multiple targets in the image; obtaining categories of multiple detected targets and first parameters of a detection frame corresponding to each detected target, and ranking all detected targets according to the first parameters in a descending order to obtain a dataset; obtaining a target with a highest first parameter in the dataset as a first detected target, and detecting whether the first parameter of a first detection frame corresponding to the first detected target satisfies a preset category condition of a category to which the first detected target belongs; detecting whether the first detection frame corresponding to the first detected target overlaps with a detection frame corresponding to a respective one of the plurality of detected targets except the first detected target.
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