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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-XLIII-B2-2021-419-2021</article-id>
<title-group>
<article-title>TOWARDS FREE-VIEWPOINT VIDEO CAPTURE IN CHALLENGING ENVIRONMENTS FOR COLLABORATIVE &amp;amp; IMMERSIVE ANALYSIS</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Frolov</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>Rendle</surname>
<given-names>G.</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>Kreskowski</surname>
<given-names>A.</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>Kaisheva</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>Froehlich</surname>
<given-names>B.</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>Rodehorst</surname>
<given-names>V.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Computer Vision in Engineering, Bauhaus-Universität Weimar, Germany</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Virtual Reality and Visualization Research Group, Bauhaus-Universität Weimar, Germany</addr-line>
</aff>
<pub-date pub-type="epub">
<day>28</day>
<month>06</month>
<year>2021</year>
</pub-date>
<volume>XLIII-B2-2021</volume>
<fpage>419</fpage>
<lpage>426</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2021 A. Frolov et al.</copyright-statement>
<copyright-year>2021</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/XLIII-B2-2021/419/2021/isprs-archives-XLIII-B2-2021-419-2021.html">This article is available from https://isprs-archives.copernicus.org/articles/XLIII-B2-2021/419/2021/isprs-archives-XLIII-B2-2021-419-2021.html</self-uri>
<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XLIII-B2-2021/419/2021/isprs-archives-XLIII-B2-2021-419-2021.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XLIII-B2-2021/419/2021/isprs-archives-XLIII-B2-2021-419-2021.pdf</self-uri>
<abstract>
<p>The ability to capture and explore complex real-world dynamic scenes is crucial for their detailed analysis. Tools which allow retrospective exploration of such scenes may support training of new employees or be used to evaluate industrial processes. In our work, we share insights and practical details for end-to-end acquisition of Free-Viewpoint Videos (FVV) in challenging environments and their potential for exploration in collaborative immersive virtual environments. Our lightweight capturing approach makes use of commodity DSLR cameras and focuses on improving both density and accuracy of Structure-from-Motion (SfM) reconstructions from small sets of images under difficult conditions. The integration of captured 3D models over time into a compact representation allows for efficient visualization of detailed FVVs in an immersive multi-user virtual reality system. We demonstrate our workflow on a representative acquisition of a suction excavation process and outline a use-case for exploration and interaction between collocated users and the FVV in a collaborative virtual environment.</p>
</abstract>
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