Unmanned aerial vehicle scene dense reconstruction method based on VI-SLAM and depth estimation network

Abstract

The invention relates to an unmanned aerial vehicle scene dense reconstruction method based on VISLAM and depth estimation, and the method comprises the steps: (1) fixing an inertial navigation unit IMU to an unmanned aerial vehicle, and calibrating the internal parameters and external parameters of a monocular camera of the unmanned aerial vehicle and the external parameters of the IMU; (2) collecting an image sequence and IMU information of an unmanned aerial vehicle scene by using an unmanned aerial vehicle monocular camera and an IMU; (3) processing the image and the IMU information acquired in the step (2) by using VISLAM to obtain a camera pose with scale information; (4) inputting the monocular image information as an original view into a viewpoint generation network to obtain a right view, and inputting the original view and the right view into a depth estimation network to obtain depth information of the image; (5) combining the camera attitude obtained in the step (3) with the depth map obtained in the step (4) to obtain a local point cloud; and (6) through point cloud optimization and registration, fusing the SLAM tracking trajectory with the local point cloud to obtainan unmanned aerial vehicle scene dense point cloud model.

Description

technical field [0001] The invention relates to a dense reconstruction method of unmanned aerial vehicle scenes based on VI-SLAM (Visual Inertial Navigation Fusion Simultaneous Positioning and Mapping) and a depth estimation network, belonging to the field of virtual reality. Background technique [0002] Three-dimensional reconstruction refers to the establishment of a mathematical model suitable for computer representation and processing of three-dimensional objects. It is the basis for processing, operating and analyzing its properties in a computer environment. It is also a key technology for establishing a virtual reality that expresses the objective world in a computer. With the increasing demand for 3D reconstruction and the increasing popularity of UAV aerial photography, point cloud reconstruction based on UAV aerial images has become a research hotspot. [0003] The traditional dense reconstruction methods using depth cameras or SfM require relatively complex hardw...

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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