{"created":"2025-01-19T00:22:24.008061+00:00","updated":"2025-01-20T17:43:00.626723+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00147180","sets":["1164:4619:8450:8451"]},"path":["8451"],"owner":"11","recid":"147180","title":["GPSシグナルを利用した疎なGoogle Street View画像列の時間軸補間"],"pubdate":{"attribute_name":"公開日","attribute_value":"2016-01-14"},"_buckets":{"deposit":"33a1c6d8-c4e2-43fe-9053-a8018a1930b7"},"_deposit":{"id":"147180","pid":{"type":"depid","value":"147180","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"GPSシグナルを利用した疎なGoogle Street View画像列の時間軸補間","author_link":["232942","232939","232937","232941","232938","232943","232940","232944"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"GPSシグナルを利用した疎なGoogle Street 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University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/147180/files/IPSJ-CVIM16200040.pdf","label":"IPSJ-CVIM16200040.pdf"},"date":[{"dateType":"Available","dateValue":"2018-01-14"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CVIM16200040.pdf","filesize":[{"value":"68.4 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Ito","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Masaki, Samejima","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Takuya, Maekawa","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yasuyuki, Matsushita","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11131797","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8701","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"Google Street View は道路に沿って一定間隔で撮影された風景画像を世界規模で提供しており，その画像列を用いたタイムラプス動画の生成には一定の興味がある．しかし，Google Street View で提供されている画像列は疎であるため，直接的に動画を生成すると，隣接フレーム間の差が大きい動画が生成されてしまう．そのため，本稿では疎な画像列を入力とし，時間軸補間により密な中間画像列を生成する方法について検討する．画像列の時間軸補間において対応点探索が重要な問題となるが，既存手法では一般に，見えの差が大きい画像間の対応点を見つけることは困難であるという問題があった．提案手法では各画像に関連付けられた GPS シグナルを利用して予測できる基礎行列を手掛かりに，対応点の探索範囲を制限することで高精度な対応点探索を実現する．提案手法を用いて得られる対応点を利用することで，疎な画像列の時間軸補間の精度を向上させた．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"7","bibliographic_titles":[{"bibliographic_title":"研究報告コンピュータビジョンとイメージメディア（CVIM）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2016-01-14","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"40","bibliographicVolumeNumber":"2016-CVIM-200"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"id":147180,"links":{}}