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<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-XLVIII-2-W1-2022-101-2022</article-id>
<title-group>
<article-title>EVALUATION OF LOW-COST DEPTH SENSORS FOR OUTDOOR APPLICATIONS</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Haenel</surname>
<given-names>R.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<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>Semin</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>Grussenmeyer</surname>
<given-names>P.</given-names>
<ext-link>https://orcid.org/0000-0002-7292-2755</ext-link>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Tabbone</surname>
<given-names>S.</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>SYSLOR SAS, 1 Square Camoufle, 57000 Metz, France</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>University of Strasbourg, CNRS, INSA Strasbourg, ICUBE Laboratory UMR 7357, Photogramemtry and Geomatics Group, 67000, France</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>University of Lorraine, CNRS LORIA UMR7503, Campus Scientifique, F-54506 Vandoeuvre-lès-Nancy, France</addr-line>
</aff>
<pub-date pub-type="epub">
<day>08</day>
<month>12</month>
<year>2022</year>
</pub-date>
<volume>XLVIII-2/W1-2022</volume>
<fpage>101</fpage>
<lpage>108</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2022 R. Haenel et al.</copyright-statement>
<copyright-year>2022</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/XLVIII-2-W1-2022/101/2022/isprs-archives-XLVIII-2-W1-2022-101-2022.html">This article is available from https://isprs-archives.copernicus.org/articles/XLVIII-2-W1-2022/101/2022/isprs-archives-XLVIII-2-W1-2022-101-2022.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLVIII-2-W1-2022/101/2022/isprs-archives-XLVIII-2-W1-2022-101-2022.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLVIII-2-W1-2022/101/2022/isprs-archives-XLVIII-2-W1-2022-101-2022.pdf</self-uri>
<abstract>
<p>Depth information is a key component that allows a computer to reproduce human vision in plenty of applications from manufacturing, to robotics and autonomous driving. The Microsoft Kinect has brought depth sensing to another level resulting in a large number of low cost, small form factor depth sensors. Although these sensors can efficiently produce data over a wide dynamic range of sensing applications and within different environments, most of them are rather suitable for indoor applications. Operating in outdoor areas is a challenge because of undesired illumination, usually strong sunlight or surface scattering, which degrades measurement accuracy. Therefore, after presenting the different working principle of existing depth cameras, our study aims to evaluate where two very recent sensors, the AD-FXTOF1-EBZ and the flexx2, stand towards the issue of outdoor environment. In particular, measurement tests will be performed on different types of materials subjected to various illumination in order to evaluate the potential accuracy of such sensors.</p>
</abstract>
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