Guideboard generation method and device and electronic equipment

Abstract

The invention relates to a guideboard generation method and device and electronic equipment. The method comprises the following steps: acquiring multiple frames of target images; respectively extracting feature points in each target image, and matching the feature points in two adjacent frames of target images to obtain relative poses of the two adjacent frames of target images and three-dimensional coordinates corresponding to the feature points; according to a preset absolute pose and each relative pose of one frame of target image, respectively determining absolute poses of other target images; performing graph optimization according to the absolute pose and the three-dimensional coordinates and the pixel coordinates of the feature points to obtain an optimized absolute pose; obtaining an optimized relative pose corresponding to each target image according to the optimized absolute pose; and triangulation is carried out according to the optimized relative pose and the pixel coordinates corresponding to the angular points of the target guideboard, and optimized three-dimensional coordinates of the angular points are obtained. According to the scheme provided by the invention, the coordinate precision of the guideboard angular points can be improved, and the method has relatively high robustness so as to deal with the processing of each guideboard.

Description

technical field [0001] The present application relates to the technical field of image processing, and in particular, to a method, device and electronic device for generating street signs. Background technique [0002] Compared with traditional electronic maps, high-precision maps can display real road feature information such as lanes, guardrails, and traffic signs, and provide lane-level navigation. [0003] In the related art, various map surveying companies collect road feature information by using special surveying and mapping vehicles, which usually use lidar technology, to create vehicle route navigation maps on a global scale. However, taking a street sign in a traffic sign as an example, when collecting a street sign, it is usually only accurate to a few meters, and the location of the street sign cannot be accurately located in a high-precision map. Although such a vehicle route navigation map is sufficient for route navigation, the location of the street signs in...

AI Technical Summary

Problems solved by technology

However, taking the street signs in traffic signs as an example, when collecting street signs, it is usually only accurate to a few meters, and it is impossible to accurately locate the position of the street signs in the high-precision map

Although such a vehicle route navigation map is sufficient for route navigation, the location of road signs in such a map is not accurate enough, which is unfavorable for high-speed vehicles to accurately identify street signs on the roadside in a timely manner

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