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  <titleInfo>
    <title>Intelligent vehicle localization using GPS, compass, and machine vision</title>
  </titleInfo>
  <name type="personal">
    <namePart>Somphop Limsoonthrakul</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>
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  <name type="personal">
    <namePart>Manukid Parnichkun</namePart>
    <role>
      <roleTerm type="text">Examination Committee</roleTerm>
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  <name type="personal">
    <namePart>Kiyoshi, Honda</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>
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    <place>
      <placeTerm type="text">Pathum Thani, Thailand</placeTerm>
    </place>
    <publisher>Asian Institute of Technology</publisher>
    <dateIssued>2009</dateIssued>
    <issuance>continuing</issuance>
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  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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  <physicalDescription>
    <extent>40 p. : ill. + 1 online resource</extent>
  </physicalDescription>
  <abstract>In term of intelligent vehicle localization, GPS have many advantages to overcome other robot{u2019}s perception techniques.  It requires less data processing and is independent from distance traveled and noises in vehicle{u2019}s surrounding environment.  However, GPS data also has a limitation that its accuracy depends on the number of available satellites and the quality of signal from them.  This affects the uncertainty of GPS and quality of localization in urban area.  Therefore, other kinds of perception techniques are required to fuse with GPS in order to increase accuracy of localization.  This research proposes a technique to use machine vision with GPS and compass to improve the precision of localization in the situation that GPS is unreliable.  The technique is to classify road regions from the scene in front of the vehicle.  The information of road regions is used as an addition measurement or observation data for localization process.  A filtering technique is require to fuse data from multi sensors and in this thesis, the observation data from GPS, compass, and vision technique are fused together with particle filter method.</abstract>
  <note>A thesis submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Computer Science (Software Engineering), School of Engineering and Technology</note>
  <note>Thesis (M.Eng.) - Asian Institute of Technology, 2009</note>
  <subject authority="lcsh">
    <topic>Global Positioning System</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Computer vision</topic>
  </subject>
  <subject authority="lcsh">
    <topic>Electronics in navigation</topic>
  </subject>
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    <titleInfo>
      <title>Thesis ; no. CS-09-13</title>
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    <name type="corporate">
      <namePart>Asian Institute of Technology.</namePart>
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  <identifier type="uri">http://203.159.5.9/ait-thesis/detail.php?q=B02097</identifier>
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