Unmanned aerial vehicle sequence image batch processing three-dimensional reconstruction method

Abstract

The invention discloses an unmanned aerial vehicle sequence image batch processing three-dimensional reconstruction method comprising: first, integrating the matching of images with low-precision GPS / INS information; second, creating a pole chart; third, calculating a globally consistent rotation set; forth, initializing the central point of a camera; fifth, generating a trajectory corresponding to the characteristic points; sixth, initializing a 3D structure; seventh, performing beam method difference leveling; eighth, reconstructing the dense points; and ninth, mapping the texture. According to the technical schemes of the invention, it is possible for the large field batch processing three-dimensional reconstruction of large data unmanned aerial vehicle sequence images. Through the utilization of the low-precision GPS / INS priori information to match the images, to create a pole chart, to draw the trajectory of the central point of multi-views as well as the new beam method difference leveling for function optimization, the precision and efficiency for three-dimensional reconstruction are increased.

Description

technical field [0001] The invention relates to a batch-processing three-dimensional reconstruction method of unmanned aerial vehicle sequence images, in particular to a batch-processing three-dimensional reconstruction method for unmanned aerial vehicle sequence images fused with low-precision GPS / IMU information. Background technique [0002] UAVs can continuously acquire high-precision sequential images with a large degree of overlap, but the acquired images will lose depth information. Image-based 3D reconstruction refers to the method and technology for automatically recovering the 3D structure of a scene by using multiple digital camera images. In recent years, 3D reconstruction technology has achieved great success in the field of video and image 3D reconstruction processing. Applying it to the field of UAV image processing and fully automatic reconstruction of UAV images can expand the application of UAVs. range and improve the application level of drones. However,...

AI Technical Summary

Problems solved by technology

However, the current research on 3D reconstruction of UAV sequence images is still in its infancy, and there are mainly the following problems: (1) Compared with ground images, 3D reconstruction based on UAV sequence images is generally a 3D reconstruction of a large amount of data and a large scene; (2) Most of the mature algorithms in computer vision are directly applied to the 3D reconstruction of UAV sequence images; (3) The auxiliary information with low precision is not fully utilized

However, these systems rely on high-precision geolocation devices, and the calibration and pose and position data obtained by these devices are generally more accurate than image methods (eg, sub-pixel image registration)

On the other hand, the current geolocation and orientation systems can generally provide continuous but often inaccurate and sometimes even inaccurate position and attitude information, just like the geolocation and attitude determination system carried by drones.

Unfortunately, the GPS / IMU data obtained from these devices cannot meet the pixel-level image matching accuracy requirements that are directly used in some computer vision tasks such as 3D object reconstruction and navigation.

Images