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  <titleInfo>
    <title>3D modeling for agricultural field inspection robot</title>
  </titleInfo>
  <name type="personal">
    <namePart>Jednipat Moonrinta</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Dailey, Mathew N.</namePart>
    <role>
      <roleTerm type="text">Chairperson</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Mongkol Ekpanyapong</namePart>
    <role>
      <roleTerm type="text">Examination Committee</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Janecek, Paul</namePart>
    <role>
      <roleTerm type="text">Examination Committee</roleTerm>
    </role>
  </name>
  <name type="corporate">
    <namePart>Royal Thai Government</namePart>
    <role>
      <roleTerm type="text">Scholarship donor</roleTerm>
    </role>
  </name>
  <typeOfResource>text</typeOfResource>
  <genre authority="marc">series</genre>
  <genre authority="marc">technical report</genre>
  <originInfo>
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      <placeTerm type="code" authority="marccountry">th</placeTerm>
    </place>
    <place>
      <placeTerm type="text">Pathum Thani, Thailand</placeTerm>
    </place>
    <publisher>Asian Institute of Technology</publisher>
    <dateIssued>2010</dateIssued>
    <issuance>continuing</issuance>
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  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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  <physicalDescription>
    <extent>33 p. : ill.</extent>
  </physicalDescription>
  <abstract>Through automated agricultural inspection, farmers can potentially achieve better produc-tivity and accurately predict yields and crop quality. The cheapest device for collecting richinformation about a crop is the video camera. This thesis focuses on the design, implemen-tation, and evaluation of algorithms for extracting information about a pineapple crop froma monocular webcam fixed to a mobile inspection platform.  The process begins with fruitdetection and tracking in video sequence.  I propose a 3D modeling algorithm that workswith the tracking history to generate a 3D point cloud for each fruit using structure-from-motion techniques in computer vision.  The 3D modeling algorithm consists of two mainprocedures: 3D point cloud estimation and 3D fruit shape reconstruction. Once the 3D pointcloud for a fruit is obtained, the fruit shape reconstruction method estimates the shape andsize of the fruit using a robust ellipsoid estimation technique. A series of experiments showsthat the method produces a reasonably accurate 3D field map despite only partial and oc-cluded views of the fruit.  The prototype is thus a promising step towards the realization ofautomated mobile in-field agricultural inspection systems.</abstract>
  <note>A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science, School of Engineering and Technology</note>
  <note>Thesis (M.Eng.) - Asian Institute of Technology, 2010</note>
  <subject authority="lcsh">
    <topic>Three-dimensional imaging</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Robot vision</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Camcorders</topic>
  </subject>
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    <titleInfo>
      <title>Thesis ; no. CS-10-04</title>
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    <name type="corporate">
      <namePart>Asian Institute of Technology.</namePart>
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    </name>
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