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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>
    </journal-meta>
    <article-meta>
      <article-id pub-id-type="doi">10.2352/ISSN.2470-1173.2018.15.COIMG-271</article-id>
      <article-id pub-id-type="sici">2470-1173(20180128)2018:15L.2711;1-</article-id>
      <article-id pub-id-type="publisher-id">s20.phd</article-id>
      <article-id pub-id-type="other">/ist/ei/2018/00002018/00000015/art00020</article-id>
      <article-categories>
        <subj-group>
          <subject>Articles</subject>
        </subj-group>
      </article-categories>
      <title-group>
        <article-title>Fast, Automated Indoor Light Detection, Classification, and Measurement</article-title>
      </title-group>
      <contrib-group>
        <contrib>
          <name>
            <surname>Hiller</surname>
            <given-names>Craig</given-names>
          </name>
        </contrib>
        <contrib>
          <name>
            <surname>Zakhor</surname>
            <given-names>Avideh</given-names>
          </name>
        </contrib>
      </contrib-group>
      <pub-date>
        <day>28</day>
        <month>01</month>
        <year>2018</year>
      </pub-date>
      <volume>2018</volume>
      <issue>15</issue>
      <fpage>271-1</fpage>
      <lpage>2714</lpage>
      <permissions>
        <copyright-year>2018</copyright-year>
      </permissions>
      <abstract>
        <p>Lighting is one of the largest power consumers in the United States and around the globe. To better understand how much energy lighting uses in a building, a lighting audit can be performed. Typically, this is a long and manual process, current solutions require significant effort on
 the part of the auditor. This paper develops a system using commercially available hardware and custom algorithms that enable a single human operator to quickly cover a large area while estimating light positions, type, and surface area. These tasks are accomplished with an error rate of 6.9%
 and 13.9%, respectively, with surface area estimation within about a factor of two.</p>
      </abstract>
      <kwd-group>
        <kwd>ENERGY AUDIT</kwd>
        <kwd>LIGHTING</kwd>
        <kwd>INDOOR MAPPING</kwd>
        <kwd>MAPPING</kwd>
      </kwd-group>
    </article-meta>
  </front>
</article>
