{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00212389","sets":["1164:3206:10513:10657"]},"path":["10657"],"owner":"44499","recid":"212389","title":["CGシーンの学習に基づく法線と輪郭線の推定と3次元モデリングへの応用"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-08-18"},"_buckets":{"deposit":"a2605dee-0315-4dc3-9638-fd3fb1849a76"},"_deposit":{"id":"212389","pid":{"type":"depid","value":"212389","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"CGシーンの学習に基づく法線と輪郭線の推定と3次元モデリングへの応用","author_link":["541641","541640"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"CGシーンの学習に基づく法線と輪郭線の推定と3次元モデリングへの応用"}]},"item_type_id":"4","publish_date":"2021-08-18","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"静岡大学大学院総合科学技術研究科工学専攻数理システム工学コース"},{"subitem_text_value":"静岡大学大学院総合科学技術研究科工学専攻数理システム工学コース"}]},"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/212389/files/IPSJ-CG21183002.pdf","label":"IPSJ-CG21183002.pdf"},"date":[{"dateType":"Available","dateValue":"2023-08-18"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CG21183002.pdf","filesize":[{"value":"1.2 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"28"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"a85b30ed-9198-4bda-b6f1-4a30a229030b","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"山梨, 傑"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"岡部, 誠"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10100541","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":"2188-8949","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"我々は写真や絵画などの 2 次元画像から 3 次元形状をモデリングするための手法を研究している．2 次元画像から 3 次元形状を再構築することはコンピュータビジョンにおける本質的な課題のひとつである．近年，畳み込みニューラルネットワークに基づく深層学習によって，単一画像からでも精度の高い深度マップが得られるようになった．しかし，それらの深度マップから 3 次元形状をポリゴンモデルとして起こしてみると必ずしも良い形状が得られない．そこで，我々は単一画像から深度マップではなく，法線マップと輪郭線マップを推定し，それらの情報を基にポアソン方程式を解くことで 3 次元形状を得るような手法を提案する．法線マップと輪郭線マップの推定に用いる深層学習モデルは U-Net であり，前者の推定には平均二乗誤差，後者の推定には Dice 係数を損失関数に用いる．コンピュータグラフィックスによって生成したデータセットを用いて学習と評価を行ったので報告する．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"4","bibliographic_titles":[{"bibliographic_title":"研究報告コンピュータグラフィックスとビジュアル情報学（CG）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2021-08-18","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicVolumeNumber":"2021-CG-183"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":212389,"updated":"2025-01-19T17:31:45.045828+00:00","links":{},"created":"2025-01-19T01:13:21.728102+00:00"}