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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-3-1925-2018</article-id>
<title-group>
<article-title>AUTOMATIC MATCHING OF LARGE SCALE IMAGES AND TERRESTRIAL LIDAR BASED ON APP SYNERGY OF MOBILE PHONE</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Xia</surname>
<given-names>G.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Hu</surname>
<given-names>C.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>School of Geomantic and Urban Information, Beijing University of Civil Engineering and Architecture, NO.15Yongyuan Road, Daxing District, Beijing, 102616, China</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Beijing, Key Laboratory for fine reconstruction and health monitoring of Architectural Heritage, NO.15Yongyuan Road, Daxing District, Beijing, 102616, China</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>Engineering Research Center of Representative Building and Architectural Heritage Database, Ministry of Education, Beijing, 102616, China</addr-line>
</aff>
<pub-date pub-type="epub">
<day>30</day>
<month>04</month>
<year>2018</year>
</pub-date>
<volume>XLII-3</volume>
<fpage>1925</fpage>
<lpage>1929</lpage>
<permissions>
<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-3-1925-2018.html">This article is available from https://isprs-archives.copernicus.org/articles/isprs-archives-XLII-3-1925-2018.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/isprs-archives-XLII-3-1925-2018.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/isprs-archives-XLII-3-1925-2018.pdf</self-uri>
<abstract>
<p>The digitalization of Cultural Heritage based on ground laser scanning technology has been widely applied. High-precision scanning and high-resolution photography of cultural relics are the main methods of data acquisition. The reconstruction with the complete point cloud and high-resolution image requires the matching of image and point cloud, the acquisition of the homonym feature points, the data registration, etc. However, the one-to-one correspondence between image and corresponding point cloud depends on inefficient manual search. The effective classify and management of a large number of image and the matching of large image and corresponding point cloud will be the focus of the research. In this paper, we propose automatic matching of large scale images and terrestrial LiDAR based on APP synergy of mobile phone. Firstly, we develop an APP based on Android, take pictures and record related information of classification. Secondly, all the images are automatically grouped with the recorded information. Thirdly, the matching algorithm is used to match the global and local image. According to the one-to-one correspondence between the global image and the point cloud reflection intensity image, the automatic matching of the image and its corresponding laser radar point cloud is realized. Finally, the mapping relationship between global image, local image and intensity image is established according to homonym feature point. So we can establish the data structure of the global image, the local image in the global image, the local image corresponding point cloud, and carry on the visualization management and query of image.</p>
</abstract>
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