<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "https://jats.nlm.nih.gov/nlm-dtd/publishing/3.0/journalpublishing3.dtd">
<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="3.0" xml:lang="en">
<front>
<journal-meta>
<journal-id journal-id-type="publisher">ISPRS-Archives</journal-id>
<journal-title-group>
<journal-title>The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences</journal-title>
<abbrev-journal-title abbrev-type="publisher">ISPRS-Archives</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">2194-9034</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/isprs-archives-XLII-2-W13-1015-2019</article-id>
<title-group>
<article-title>FAST PAIRWISE COARSE REGISTRATION BETWEEN POINT CLOUDS OF CONSTRUCTION SITES USING 2D PROJECTION BASED PHASE CORRELATION</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Huang</surname>
<given-names>R.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Ye</surname>
<given-names>Z.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Boerner</surname>
<given-names>R.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Yao</surname>
<given-names>W.</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Xu</surname>
<given-names>Y.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Stilla</surname>
<given-names>U.</given-names>
<ext-link>https://orcid.org/0000-0002-1184-0924</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Photogrammetry and Remote Sensing, Technische Universität München, 80333 München, Germany</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Department of Land Surveying and Geo-Informatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China</addr-line>
</aff>
<pub-date pub-type="epub">
<day>05</day>
<month>06</month>
<year>2019</year>
</pub-date>
<volume>XLII-2/W13</volume>
<fpage>1015</fpage>
<lpage>1020</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2019 R. Huang et al.</copyright-statement>
<copyright-year>2019</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLII-2-W13/1015/2019/isprs-archives-XLII-2-W13-1015-2019.html">This article is available from https://isprs-archives.copernicus.org/articles/XLII-2-W13/1015/2019/isprs-archives-XLII-2-W13-1015-2019.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLII-2-W13/1015/2019/isprs-archives-XLII-2-W13-1015-2019.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLII-2-W13/1015/2019/isprs-archives-XLII-2-W13-1015-2019.pdf</self-uri>
<abstract>
<p>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.</p>
</abstract>
<counts><page-count count="6"/></counts>
</article-meta>
</front>
<body/>
<back>
</back>
</article>