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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/isprsarchives-XL-4-W5-43-2015</article-id>
<title-group>
<article-title>GEOMETRY AND TEXTURE MEASURES FOR INTERACTIVE VIRTUALIZED REALITY INDOOR MODELER</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Thangamania</surname>
<given-names>K.</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>Ichikari</surname>
<given-names>R.</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>Okuma</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>Ishikawa</surname>
<given-names>T.</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>Kurata</surname>
<given-names>T.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>SErvice SEnsing, Assimilation, and Modeling Research Group, Human Informatics Research Institute, National Institute of Advanced Industrial Science and Technology (AIST), 1-1-1 Umezono, Tsukuba 305-8568, Japan</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Site Sensing Inc., Japan</addr-line>
</aff>
<pub-date pub-type="epub">
<day>11</day>
<month>05</month>
<year>2015</year>
</pub-date>
<volume>XL-4/W5</volume>
<fpage>43</fpage>
<lpage>48</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2015 K. Thangamania et al.</copyright-statement>
<copyright-year>2015</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/3.0/">https://creativecommons.org/licenses/by/3.0/</ext-link></license-p>
</license>
</permissions>
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<self-uri xlink:href="https://isprs-archives.copernicus.org/articles/XL-4-W5/43/2015/isprs-archives-XL-4-W5-43-2015.pdf">The full text article is available as a PDF file from https://isprs-archives.copernicus.org/articles/XL-4-W5/43/2015/isprs-archives-XL-4-W5-43-2015.pdf</self-uri>
<abstract>
<p>This paper discusses the algorithm to detect the distorted textures in the virtualized reality indoor models and automatically generate
the necessary 3D planes to hold the undistorted textures. Virtualized reality (VR) interactive indoor modeler, our previous contribution
enables the user to interactively create their desired indoor VR model from a single 2D image. The interactive modeler uses the
projective texture mapping for mapping the textures over the manually created 3D planes. If the user has not created the necessary
3D planes, then the texture that belong to various objects are projected to the available 3D planes, which leads to the presence of
distorted textures. In this paper, those distorted textures are detected automatically by the suitable principles from the shape from
texture research. The texture distortion features such as the slant, tilt and the curvature parameters are calculated from the 2D image
by means of affine transformation measured between the neighboring texture patches within the single image. This kind of affine
transform calculation from a single image is useful in the case of deficient multiple view images. The usage of superpixels in clustering
the textures corresponding to different objects, reduces the modeling labor cost. A standby database also stores the repeated basic
textures that are found in the indoor model, and provides texture choices for the distorted floor, wall and other regions. Finally, this
paper documents the prototype implementation and experiments with the automatic 3D plane creation and distortion detection with the
above mentioned principles in the virtualized reality indoor environment.</p>
</abstract>
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