Point-line combined multi-camera vision SLAM method and device and storage medium

Abstract

The invention provides a point-line combined multi-camera vision SLAM method and device, and a storage medium, and the method comprises the steps: collecting multi-angle image data of a target scene,extracting and matching point features and line features in the multi-angle image data, and obtaining the position information of the point features and the line features in a three-dimensional space;and performing camera pose preliminary estimation on each frame of image in the multi-angle image data, constructing a graph structure in combination with the extracted and matched point features, line features and camera pose preliminary estimation results, and determining a three-dimensional map according to the extracted point features, line features and the graph structure. According to the embodiment of the invention, a point and line feature joint calculation method is adopted, and the line features contain more information, so that the tracking stability and accuracy can be improved, and a sparse feature map constructed by using the line features can be used for carrying out abstract description on a scene more clearly and intuitively.

Description

technical field [0001] The present invention relates to the technical field of computer vision, in particular to a multi-camera visual SLAM method, device and storage medium combining point and line. Background technique [0002] The SLAM algorithm is widely used in robot autonomous navigation and environment recognition in augmented reality, aerospace, underwater and other scenarios, and has important theoretical significance and practical value. Among them, visual SLAM based on sequential image data has become a hot research topic due to its advantages of economy and portability. How to effectively extract representative and tracking features from image data, describe them using an appropriate algebraic language, and how to make full use of the above information to restore camera pose and scene structure are the key concerns of SLAM algorithms. [0003] The feature method is currently the mainstream method in visual SLAM. It extracts abstract geometric features from image...

AI Technical Summary

Problems solved by technology

[0005] In view of the deficiencies in the prior art, the purpose of the present invention is to provide a multi-camera visual SLAM method, device and storage medium combining points and lines, so as to overcome the problem that the stability and accuracy cannot meet the needs when using the feature method for feature tracking in the prior art defect

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