Dense reconstruction method of UAV scene based on vi-slam and depth estimation network

Abstract

The present invention relates to a dense reconstruction method of unmanned aerial vehicle scenes based on VI-SLAM and depth estimation. External parameters and IMU external parameters are calibrated; (2) use the UAV monocular camera and IMU to collect the image sequence and IMU information of the UAV scene; (3) use VI‑SLAM to process the images and Process the IMU information to obtain the camera pose with scale information; (4) Input the monocular image information as the original view into the viewpoint generation network to obtain the right view, and then input the original view and the right view into the depth estimation network to obtain the depth of the image (5) Combine the camera pose obtained in step (3) with the depth map in step (4) to obtain a local point cloud; (6) After point cloud optimization and registration, combine the SLAM tracking trajectory with the local point cloud Cloud fusion to obtain a dense point cloud model of the UAV scene.

Description

technical field [0001] The invention relates to a dense reconstruction method of unmanned aerial vehicle scene based on VI-SLAM (Visual Inertial Navigation Fusion Simultaneous Positioning and Mapping) and depth estimation network, and belongs to the field of virtual reality. Background technique [0002] 3D reconstruction refers to the establishment of a mathematical model suitable for computer representation and processing of 3D objects. It is the basis for processing, operating and analyzing its properties in a computer environment. With the increasing demand for 3D reconstruction and the continuous popularization of UAV aerial photography, point cloud reconstruction based on UAV aerial images has become a research hotspot. [0003] The traditional dense reconstruction method based on depth camera or SfM requires more complex hardware equipment and relatively huge computing resources, which cannot well meet the needs of lightweight equipment and rapid reconstruction in lar...

AI Technical Summary

Problems solved by technology

[0006] The technology of the present invention solves the problem: overcomes the problem of the prior art that large-scale scenes cannot be quickly and densely reconstructed, and provides a dense reconstruction method for unmanned aerial vehicle scenes based on VI-SLAM and depth estimation network, by tracking the camera pose in real time, and Estimate the depth information of the scene through the depth estimation of a single image, which can achieve faster operating efficiency during heavy and dense construction.

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