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Method for discriminating unknown obstacles in three-dimensional semantic segmentation of road scene

A technology of semantic segmentation and discrimination method, applied in the field of image processing, can solve the problem of not being able to recognize untrained objects, etc., and achieve the effect of improving security

Pending Publication Date: 2022-03-01
HUAZHONG PHOTOELECTRIC TECH INST (CHINA SHIPBUILDING IND CORP THE NO 717 INST)
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Problems solved by technology

[0005] The present invention provides a method for discriminating unknown obstacles in three-dimensional semantic segmentation of road scenes through a fusion algorithm of three-dimensional point clouds and two-dimensional images, so as to solve the problem that the neural network model cannot recognize untrained objects and improve the safety of unmanned driving. safety

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  • Method for discriminating unknown obstacles in three-dimensional semantic segmentation of road scene
  • Method for discriminating unknown obstacles in three-dimensional semantic segmentation of road scene
  • Method for discriminating unknown obstacles in three-dimensional semantic segmentation of road scene

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[0030] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0031] In the semantic segmentation algorithm used in autonomous driving, unknown road obstacles cannot be identified. The present invention uses the fusion result of the three-dimensional point cloud and the two-dimensional image to perform plane fitting on the coordinates of the three-dimensional point cloud corresponding to the road area of ​​the image, and then calculates the distance of each point relative to the fitting plane. Mark the points whose distance is greater than a certain threshold, and then perform region growth on all the above points in 3D space. Finally, each grown 3D region block is marked as an unknown road obstacle to guide the vehicle to avoid road obstacles on the driving route.

[0032] The invention discloses a method for discriminating unknown obstacles in three-dimensional semantic segmentation of road scenes. Fir...

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Abstract

The invention discloses a method for judging an unknown obstacle in three-dimensional semantic segmentation of a road scene, which comprises the following steps of: determining a mapping relation between a two-dimensional image and a three-dimensional point cloud through a calibration method, obtaining a semantic segmentation result of the two-dimensional image through a two-dimensional image semantic segmentation algorithm, and obtaining a semantic segmentation result of the three-dimensional point cloud through the mapping relation. Then a road plane is obtained through least square platform fitting, non-road points in a road area are searched, and finally unknown road obstacles are marked through 3D area growth. Compared with a current environment perception method adopting a deep learning technology, the method can detect unknown road obstacles in the road, and improves the safety of automatic driving.

Description

technical field [0001] The invention belongs to the technical field of image processing, and relates to an environment perception method for fusion of three-dimensional point clouds and two-dimensional images in automatic driving, in particular to a method for discriminating unknown obstacles in three-dimensional semantic segmentation of road scenes. Background technique [0002] Currently, lidar and visible light cameras have been widely used in autonomous driving. Lidar provides point cloud information in the scene, and through conversion, the three-dimensional coordinates of each point in a certain coordinate system can be obtained. The visible light camera provides two-dimensional image information in the scene, and can obtain the color and texture information of the scene on the image plane. When the relative position of the visible light camera and the lidar is fixed, there is a mapping relationship between the 3D point cloud and the 2D image in space. A set of parame...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06V20/58G06V20/64G06V10/26G06V10/80
CPCG06F18/251
Inventor 雷波汤文豪王晨晟王密信李忠
Owner HUAZHONG PHOTOELECTRIC TECH INST (CHINA SHIPBUILDING IND CORP THE NO 717 INST)
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