<?xml version="1.0" encoding="utf-8"?>
<export-example>
  <doc>
    <id>1425</id>
    <completedYear/>
    <publishedYear>2011</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst/>
    <pageLast/>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>reportzib</type>
    <publisherName/>
    <publisherPlace/>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>0</belongsToBibliography>
    <completedDate>2011-11-05</completedDate>
    <publishedDate>2011-11-05</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Level of Detail for Trees Using Clustered Ellipsoids</title>
    <abstract language="eng">We present a level of detail method for trees based on ellipsoids and lines. We leverage the Expectation Maximization algorithm with a Gaussian Mixture Model to create a hierarchy of high-quality leaf clusterings, while the branches are simplified using agglomerative bottom-up clustering to preserve the connectivity. The simplification runs in a preprocessing step and requires no human interaction. For a fly by over and through a scene of 10k trees, our method renders on average at 40 ms/frame, up to 6 times faster than billboard clouds with comparable artifacts.</abstract>
    <identifier type="issn">1438-0064</identifier>
    <identifier type="serial">11-41</identifier>
    <identifier type="urn">urn:nbn:de:0297-zib-14251</identifier>
    <enrichment key="PeerReviewed">no</enrichment>
    <author>Malte Clasen</author>
    <submitter>Steffen Prohaska</submitter>
    <author>Philip Paar</author>
    <author>Steffen Prohaska</author>
    <series>
      <title>ZIB-Report</title>
      <number>11-41</number>
    </series>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>level of detail</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>rendering</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>natural scene</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Gaussian mixture model</value>
    </subject>
    <collection role="ccs" number="I.">Computing Methodologies</collection>
    <collection role="pacs" number="80.00.00">INTERDISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY</collection>
    <collection role="msc" number="65-XX">NUMERICAL ANALYSIS</collection>
    <collection role="msc" number="68-XX">COMPUTER SCIENCE (For papers involving machine computations and programs in a specific mathematical area, see Section -04 in that area)</collection>
    <collection role="institutes" number="vis">Visual Data Analysis</collection>
    <collection role="institutes" number="vissys">Image Analysis in Biology and Materials Science</collection>
    <collection role="persons" number="prohaska">Prohaska, Steffen</collection>
    <collection role="institutes" number="VDcC">Visual and Data-centric Computing</collection>
    <file>https://opus4.kobv.de/opus4-zib/files/1425/zibreport.pdf</file>
  </doc>
</export-example>
