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        <datestamp>2025-01-19T15:40:53Z</datestamp>
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          <dc:title>Robust Outdoor Panoramic View SLAM using Semantic View Filter</dc:title>
          <dc:title xml:lang="en">Robust Outdoor Panoramic View SLAM using Semantic View Filter</dc:title>
          <jpcoar:creator>
            <jpcoar:creatorName>Xiangyu, Chu</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName>Ryoichi, Ishikawa</jpcoar:creatorName>
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            <jpcoar:creatorName>Takeshi, Oishi</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Xiangyu, Chu</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Ryoichi, Ishikawa</jpcoar:creatorName>
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          <jpcoar:creator>
            <jpcoar:creatorName xml:lang="en">Takeshi, Oishi</jpcoar:creatorName>
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          <jpcoar:subject subjectScheme="Other">セッション1-B</jpcoar:subject>
          <datacite:description descriptionType="Other">Outdoor visual SLAM is easily affected by dynamic objects, such as moving cars and pedestrians. Moreover, panoramic view tracking has the problem of unstable feature extraction because of the image distortions. We propose a V-SLAM framework with multiple virtual cameras robust to the dynamic environment and computationally efficient while achieving stable camera tracking to solve these issues.</datacite:description>
          <datacite:description descriptionType="Other">Outdoor visual SLAM is easily affected by dynamic objects, such as moving cars and pedestrians. Moreover, panoramic view tracking has the problem of unstable feature extraction because of the image distortions. We propose a V-SLAM framework with multiple virtual cameras robust to the dynamic environment and computationally efficient while achieving stable camera tracking to solve these issues.</datacite:description>
          <dc:publisher xml:lang="ja">情報処理学会</dc:publisher>
          <datacite:date dateType="Issued">2022-03-03</datacite:date>
          <dc:language>eng</dc:language>
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          <jpcoar:sourceIdentifier identifierType="NCID">AA11131797</jpcoar:sourceIdentifier>
          <jpcoar:sourceTitle>研究報告コンピュータビジョンとイメージメディア（CVIM）</jpcoar:sourceTitle>
          <jpcoar:volume>2022-CVIM-229</jpcoar:volume>
          <jpcoar:issue>6</jpcoar:issue>
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          <jpcoar:pageEnd>5</jpcoar:pageEnd>
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            <datacite:date dateType="Available">2024-03-03</datacite:date>
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