<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE article PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/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>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-XLI-B1-653-2016</article-id>
<title-group>
<article-title>IMAGE CAPTURE WITH SYNCHRONIZED MULTIPLE-CAMERAS FOR EXTRACTION OF ACCURATE GEOMETRIES</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Koehl</surname>
<given-names>M.</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>Delacourt</surname>
<given-names>T.</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>Boutry</surname>
<given-names>C.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</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>
<pub-date pub-type="epub">
<day>06</day>
<month>06</month>
<year>2016</year>
</pub-date>
<volume>XLI-B1</volume>
<fpage>653</fpage>
<lpage>660</lpage>
<permissions>
<license license-type="open-access">
<license-p/>
</license>
</permissions>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/isprs-archives-XLI-B1-653-2016.html">This article is available from https://isprs-archives.copernicus.org/articles/isprs-archives-XLI-B1-653-2016.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/isprs-archives-XLI-B1-653-2016.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/isprs-archives-XLI-B1-653-2016.pdf</self-uri>
<abstract>
<p>This paper presents a project of recording and modelling tunnels, traffic circles and roads from multiple sensors. The aim is the
representation and the accurate 3D modelling of a selection of road infrastructures as dense point clouds in order to extract profiles
and metrics from it. Indeed, these models will be used for the sizing of infrastructures in order to simulate exceptional convoy truck
routes. The objective is to extract directly from the point clouds the heights, widths and lengths of bridges and tunnels, the diameter
of gyrating and to highlight potential obstacles for a convoy. Light, mobile and fast acquisition approaches based on images and
videos from a set of synchronized sensors have been tested in order to obtain useable point clouds. The presented solution is based
on a combination of multiple low-cost cameras designed on an on-boarded device allowing dynamic captures. The experimental
device containing &lt;i&gt;GoPro Hero4&lt;/i&gt; cameras has been set up and used for tests in static or mobile acquisitions. That way, various
configurations have been tested by using multiple synchronized cameras. These configurations are discussed in order to highlight the
best operational configuration according to the shape of the acquired objects. As the precise calibration of each sensor and its optics
are major factors in the process of creation of accurate dense point clouds, and in order to reach the best quality available from such
cameras, the estimation of the internal parameters of fisheye lenses of the cameras has been processed. Reference measures were
also realized by using a 3D TLS (&lt;i&gt;Faro Focus 3D&lt;/i&gt;) to allow the accuracy assessment.</p>
</abstract>
<counts><page-count count="8"/></counts>
</article-meta>
</front>
<body/>
<back>
</back>
</article>
