{"created":"2025-01-19T01:29:14.404237+00:00","updated":"2025-01-19T11:23:48.499513+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00229838","sets":["6504:11436:11440"]},"path":["11440"],"owner":"44499","recid":"229838","title":["部分欠損した骨格データにおけるGANを用いた補間手法に関する検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-02-16"},"_buckets":{"deposit":"1c2fd6d7-0699-4027-9b26-17f956c32221"},"_deposit":{"id":"229838","pid":{"type":"depid","value":"229838","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"部分欠損した骨格データにおけるGANを用いた補間手法に関する検討","author_link":["618268","618271","618274","618270","618269","618273","618272"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"部分欠損した骨格データにおけるGANを用いた補間手法に関する検討"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"人工知能と認知科学","subitem_subject_scheme":"Other"}]},"item_type_id":"22","publish_date":"2023-02-16","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_22_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"秋田大"},{"subitem_text_value":"秋田大"},{"subitem_text_value":"秋田大"},{"subitem_text_value":"秋田大"},{"subitem_text_value":"エイデイケイ富士システム"},{"subitem_text_value":"エイデイケイ富士システム"},{"subitem_text_value":"エイデイケイ富士システム"}]},"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/229838/files/IPSJ-Z85-6C-05.pdf","label":"IPSJ-Z85-6C-05.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-17"}],"format":"application/pdf","filename":"IPSJ-Z85-6C-05.pdf","filesize":[{"value":"382.9 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"ec395ca4-eb2a-4830-8aeb-d514c7e5d5e1","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_22_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"雲, 河晨"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"中村, 悦郎"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"景山, 陽一"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"石沢, 千佳子"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"加藤, 伸彦"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"五十嵐, 健"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"川本, 健"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_22_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00349328","subitem_source_identifier_type":"NCID"}]},"item_22_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年，労働現場では労働者の高年齢化が進行しており，従事者の安全管理を行うことが必要不可欠である．本研究では，安全管理システムの構築を目的とし，危険行動予測手法の構築を行う．すでに，人物の動画像から抽出した骨格特徴点を利用し，動作予測技術が開発されているが，作業内容や環境状況など複雑な状況により骨格点の取得と補間が必ずしも良好に行われない場合において，動作認識精度のばらつきが発生する課題がある．本稿では，時系列的骨格データを対象として，Generative Adversarial Network (GAN)を用い，複数な行動パターンと視点に基づく部分欠損した骨格点の位置情報を補間する手法および提案手法の有用性の評価に関して検討を行った．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"74","bibliographic_titles":[{"bibliographic_title":"第85回全国大会講演論文集"}],"bibliographicPageStart":"73","bibliographicIssueDates":{"bibliographicIssueDate":"2023-02-16","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2023"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":229838,"links":{}}