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<article article-type="research-article">
  <front>
    <journal-meta>
      <journal-id journal-id-type="aggregator">72010604</journal-id>
      <journal-title>Electronic Imaging</journal-title>
      <issn pub-type="ppub">2470-1173</issn><issn pub-type="epub"></issn>
      <publisher>
        <publisher-name>Society for Imaging Science and Technology</publisher-name>
        <publisher-loc>7003 Kilworth Lane, Springfield, VA 22151 USA</publisher-loc>
      </publisher>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.2352/ISSN.2470-1173.2020.11.HVEI-128</article-id>
      <article-id pub-id-type="sici">2470-1173(20200126)2020:11L.1281;1-</article-id>
      <article-id pub-id-type="publisher-id">ei_24701173_v2020n11_input/s9.xml</article-id>
      <article-id pub-id-type="other">/ist/ei/2020/00002020/00000011/art00007</article-id>
      <article-categories>
        <subj-group>
          <subject>Articles</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Quality Evaluation of 3D Objects in Mixed Reality For Different Lighting Conditions</article-title>
      </title-group>
      <contrib-group>
        <contrib>
          <name>
            <surname>Gutiérrez</surname>
            <given-names>Jesús</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Vigier</surname>
            <given-names>Toinon</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Callet</surname>
            <given-names>Patrick Le</given-names>
          </name>
        </contrib>
      </contrib-group>
      <pub-date>
        <day>26</day>
        <month>01</month>
        <year>2020</year>
      </pub-date>
      <volume>2020</volume>
      <issue>11</issue>
      <fpage>128-1</fpage>
      <lpage>128-7</lpage>
      <permissions>
        <copyright-year>2020</copyright-year>
      </permissions>
      <abstract>
        <p>
          <italic>This paper presents a study on Quality of Experience (QoE) evaluation of 3D objects in Mixed Reality (MR) scenarios. In particular, a subjective test was performed with Microsoft HoloLens, considering different degradations affecting the geometry and texture of the content. Apart
 from the analysis of the perceptual effects of these artifacts, given the need for recommendations for subjective assessment of immersive media, this study was also aimed at: 1) checking the appropriateness of a single stimulus methodology (ACR-HR) for these scenarios where observers have
 less references than with traditional media, and 2) analyzing the possible impact of environment lighting conditions on the quality evaluation of 3D objects in mixed reality (MR), and 3) benchmark state-of-the-art objective metrics in this context. The subjective results provide insights for
 recommendations for subjective testing in MR/AR, showing that ACR-HR can be used in similar QoE tests and reflecting the influence among the lighting conditions, the content characteristics, and the type of degradations. The objective results show an acceptable performance of perceptual metrics
 for geometry quantization artifacts and point out the need of further research on metrics covering both geometry and texture compression degradations. </italic>
        </p>
      </abstract>
      <kwd-group>
        <kwd>Subjective evaluation</kwd>
        <kwd>mixed reality</kwd>
        <kwd>augmented reality</kwd>
        <kwd>3D objects</kwd>
        <kwd>quality of experience</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
