Vehicle self-positioning method based on street view image database

Abstract

The invention discloses a vehicle self-positioning method based on a street view image database. The vehicle self-positioning method comprises the following steps of 1, collecting view images by a camera, and extracting main color feature vector information, SURF feature points and position information of the collected images, and storing the extracted information in the database; 2, taking the shot images in a vehicle driving process as to-be-matched images, extracting main color feature vectors of the to-be-matched images, obtaining an initial matched image by calculating the similarity of the main color feature vector of the to-be-matched images and the main color feature vector of the images in the original database, extracting the position information of the initial matched image, and preliminarily determining the position of the vehicle; and 3, extracting adjacent-region images of the initial matched image, forming a searching space, performing feature point matching on the to-be-matched images and the images in the searching space to obtain an optimal matched image, extracting the shooting position coordinate of the optimal matched image and position coordinates of other eight adjacent regions, calculating the weight of each coordinate, and then calculating the accurate coordinate of the vehicle position through a formula.

Description

technical field [0001] The invention belongs to the technical field of vehicle positioning, and in particular relates to a vehicle autonomous positioning method based on a street view image database in a GPS blind spot. Background technique [0002] Vehicle high-precision positioning is an important part of Intelligent Transportation System (ITS), and a key technology for safe autonomous navigation. Current vehicle navigation systems usually use civilian GPS to estimate vehicle position, however such GPS has an error of 5 to 30 meters due to building reflections and occlusion of GPS signals. On the other hand, RTK-GPS can estimate the vehicle position more accurately, but it is easy to be blocked and the cost is high. In order to overcome these problems, some research groups have proposed to use sensors such as sonar, laser scanners, and cameras to study the corresponding algorithms when GPS cannot correctly perform vehicle autonomous positioning, mainly including the follo...

AI Technical Summary

Problems solved by technology

[0006] In order to solve the technical problems existing in the existing vehicle positioning technology that need to consume a large amount of hardware equipment, so it is...

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