Vision-based vehicle positioning method and device and vehicle-mounted terminal

Abstract

The embodiment of the invention discloses a vision-based vehicle positioning method and device and a vehicle-mounted terminal. The method comprises the following steps: acquiring a road image acquiredby camera equipment; determining an initial positioning pose corresponding to the road image according to the data acquired by the motion detection equipment; determining a target map point corresponding to the road image from a preset map according to the initial positioning pose; extracting an edge feature map of the road image according to preset edge intensity; determining a mapping difference between the target map point and a point in the edge feature map according to the initial positioning pose, and determining a vehicle positioning pose according to the projection difference, whereinthe initial positioning pose is a pose in a world coordinate system where a preset map is located, and each map point in the preset map is obtained by performing three-dimensional reconstruction andselection on points in the edge feature map of the sample road image in advance. By applying the scheme provided by the embodiment of the invention, the effectiveness of positioning the vehicle basedon vision can be improved.

Description

technical field [0001] The present invention relates to the technical field of intelligent driving, in particular to a vision-based vehicle positioning method, device and vehicle-mounted terminal. Background technique [0002] In the field of intelligent driving technology, vehicle positioning is an important part of intelligent driving. Usually, when the vehicle is driving, the vehicle pose can be determined according to the satellite positioning system. However, when the vehicle travels to a scene with weak or no satellite signal, in order to accurately determine the positioning pose of the vehicle, it can be positioned based on visual positioning. [0003] Vision-based positioning is usually based on the matching between the semantic information of the road image collected by the camera device and the semantic information in the high-precision map. The semantic information in the high-precision map is modeled based on common landmarks on the road. Markers generally inc...

AI Technical Summary

Problems solved by technology

However, when there are few landmarks or even no landmarks in the scene, it is difficult for the high-precision map to give enough effective information for visual positioning; or, when the landmarks cannot completely match the high-precision map due to occlusion or aging, the visual positioning may not be possible

All of the above lead to less effective visual localization

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