Abstract
Abstract. For conducting change detection using 3D scans of a construction site, the registration between point clouds at different acquisition times is normally necessary. However, due to the complexity of constructing areas, the automatic registration of temporal scans is a challenging problem. In this work, we propose a fast and maker-free method for coarse registration between point clouds by converting the 3D matching problem into a 2D correlation problem, taking the special properties of building structures into consideration. Our proposed method consists of two major steps: the conversion from 3D points to 2D image data and the estimation of transformation parameters between 2D images in the frequency domain. In the conversion step, the point cloud of each scan is projected into a 2D grey image, by which the ground footprint of the point cloud is obtained. In the following step, we represent the 2D image in frequency-domain and estimate the horizontal transformation parameters by using Fourier-Mellin transformation. A real application is performed to validate the feasibility and effectiveness of our workflow using photogrammetric point clouds of a construction site in two different acquisition time. Regarding the real application of coarse registration of point clouds, our proposed method can achieve a registration error of less than 1 degree and more efficient than the classical baseline methods for the fast orientation between scans.
Highlights
In the recent decade, in the Architectural, Engineering and Construction (ACE) fields, there is an exponential increase demand for efficient and effective progress monitoring of construction sites (Boscheet al., 2015)
For construction sites, it always has a very complex environment, so that acquired point clouds could be influenced by noises and outliers resulting from errors of stereo matching, uneven point cloud density caused by varying measuring distances of camera or scanners, occlusions caused by the strained observation positions, and disturbances caused by dynamic objects are quite common
We present a 3D-to-2D coarse registration method for fast aligning point clouds of construction sites in different acquisition time, which consists of the conversion from 3D points to 2D image data and the estimation of transformation parameters of 2D images in the frequency domain
Summary
In the Architectural, Engineering and Construction (ACE) fields, there is an exponential increase demand for efficient and effective progress monitoring of construction sites (Boscheet al., 2015). An increased automation is urgently required for construction progress monitoring For this need, a large number of researchers have reported related methods using 2D imaging, 3D photogrammetry and laser scanning for automatically acquiring measurements in construction sites. Construction buildings and other structures often present symmetries and self-similarities, and the overlapping rate between different scans may be low when the acquisition time interval is large Due to these problems, the automatic registration of point clouds on construction sites is a challenging task. We present a 3D-to-2D coarse registration method for fast aligning point clouds of construction sites in different acquisition time, which consists of the conversion from 3D points to 2D image data and the estimation of transformation parameters of 2D images in the frequency domain. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-2/W13, 2019 ISPRS Geospatial Week 2019, 10–14 June 2019, Enschede, The Netherlands between two point clouds can be obtained and a balance of effectiveness and efficiency is achieved
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