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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ISPRS-Archives</journal-id>
<journal-title-group>
<journal-title>ISPRS - 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-W15-1083-2019</article-id>
<title-group>
<article-title>REGISTRATION OF 2D DRAWINGS ON A 3D POINT CLOUD AS A SUPPORT FOR THE
MODELING OF COMPLEX ARCHITECTURES</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Semler</surname>
<given-names>Q.</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>Suwardhi</surname>
<given-names>D.</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>Alby</surname>
<given-names>E.</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>Murtiyoso</surname>
<given-names>A.</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>Macher</surname>
<given-names>H.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<ext-link>https://orcid.org/0000-0002-2686-0864</ext-link></contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Photogrammetry and Geomatics Group, ICube Laboratory UMR 7357 INSA Strasbourg, France</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Remote Sensing and GIS Group, Bandung Institute of Technology, Indonesia</addr-line>
</aff>
<pub-date pub-type="epub">
<day>26</day>
<month>08</month>
<year>2019</year>
</pub-date>
<volume>XLII-2/W15</volume>
<fpage>1083</fpage>
<lpage>1087</lpage>
<permissions>
<copyright-statement>Copyright: © 2019 Q. Semler 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/isprs-archives-XLII-2-W15-1083-2019.html">This article is available from https://isprs-archives.copernicus.org/articles/isprs-archives-XLII-2-W15-1083-2019.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/isprs-archives-XLII-2-W15-1083-2019.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/isprs-archives-XLII-2-W15-1083-2019.pdf</self-uri>
<abstract>
<p>&lt;p&gt;Laser scanning and photogrammetry methods have seen immense development in the last years. From bulky inaccessible systems,
these two 3D recording systems has become more or less ubiquitous, which is also the case in the heritage domain. However,
automation in point cloud classification and semantic annotation remains a much studied topic. In this paper, an approach to help
the classification of point cloud is presented using the help of existing 2D drawings. The 2D drawings are registered unto the 3D
data, to then be used as a support in the 3D modeling step. The developed approach includes the computation of the point cloud
cross section and detection of feature points. This is then used in a 3D transformation followed by ICP refinement to properly
register the vectorized 2D drawing on the 3D point cloud. Results show that the developed algorithm manages to register the 2D
drawing automatically and with promising results. The automatically registered 2D drawing, which often times already includes
semantic information, was then used to help classify the point cloud into several architectural classes.&lt;/p&gt;</p>
</abstract>
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