{"created":"2025-01-19T01:32:33.255186+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00231968","sets":["1164:4619:11539:11571"]},"path":["11571"],"owner":"44499","recid":"231968","title":["大規模3Dメタデータによる撮影スポット探索機の学習"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-01-18"},"_buckets":{"deposit":"4366d39e-4a9e-4c2a-bb98-3adc94010f75"},"_deposit":{"id":"231968","pid":{"type":"depid","value":"231968","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"大規模3Dメタデータによる撮影スポット探索機の学習","author_link":["627524","627525","627523","627522","627520","627521"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"大規模3Dメタデータによる撮影スポット探索機の学習"}]},"item_type_id":"4","publish_date":"2024-01-18","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"クラスターメタバース研究所"},{"subitem_text_value":"École polytechnique"},{"subitem_text_value":"クラスター"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Cluster Metaverse Lab","subitem_text_language":"en"},{"subitem_text_value":"École polytechnique","subitem_text_language":"en"},{"subitem_text_value":"Cluster, INC.","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/231968/files/IPSJ-CVIM24236046.pdf","label":"IPSJ-CVIM24236046.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CVIM24236046.pdf","filesize":[{"value":"2.2 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"20"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"8595f722-6943-4af0-bd5e-9e1a1e4f284a","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Institute of Electronics, Information and Communication Engineers This SIG report is only available to those in membership of the SIG."}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"早瀬, 友裕"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Braun, Sacha"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"折登, 樹"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Tomohiro, Hayase","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Braun, Sacha","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Itsuki, Orito","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":"インターネットに接続された持続的な 3DCG 空間とその利用者の増加は，深層学習においてまだ十分に活用されていない新たな学習用データセットを提供する可能性を秘めている．本研究では，マルチプレイヤーオンライン VR プラットフォームにおける 3DCG シーンの理解と利用に焦点を当てる．これらのプラットフォームでは，ユーザーが 3DCG シーンを作成し，共有し，操作することが可能であり，シーン内での写真撮影は一つの重要な活動である．この研究の目的は，3DCG 空間内の撮影スポットの質を向上させ，より良いシーン製作を支援することである．本研究では，視覚に基づく撮影スポットの予測を行うための評価関数の学習と，三次元木構造探索を用いた撮影スポット探索機を提案する．評価関数の学習には，カメラ撮影のメタデータを使用し，行動データが不足しているシーンにおいても予測を行う．研究の主な貢献は以下の通りである．まず，ユーザーが撮影した写真からアバターを除外したデータセットを作成し，これを用いて深層回路の学習を行った. 次に，このデータセットに適したデータ拡張手法を特定し，人間の判定との相関を確認した．最後に，学習済みの深層回路を評価関数として使用し，三次元階層的ブラックボックス探索の提案と解析を行った. このアルゴリズムは，未知のシーンにおいても効率的に探索を行い，質の高い撮影スポットを発見した．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","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":"2024-01-18","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"46","bibliographicVolumeNumber":"2024-CVIM-236"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":231968,"updated":"2025-01-19T10:35:08.466883+00:00","links":{}}