{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00235892","sets":["6504:11678:11689"]},"path":["11689"],"owner":"44499","recid":"235892","title":["欠損状態下における動き生成技術を用いた骨格データの補間手法に関する検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-03-01"},"_buckets":{"deposit":"7fe93120-0734-4b6c-910b-580b9c254b18"},"_deposit":{"id":"235892","pid":{"type":"depid","value":"235892","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"欠損状態下における動き生成技術を用いた骨格データの補間手法に関する検討","author_link":["644649","644647","644650","644646","644645","644648"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"欠損状態下における動き生成技術を用いた骨格データの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":"2024-03-01","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":"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/235892/files/IPSJ-Z86-6C-03.pdf","label":"IPSJ-Z86-6C-03.pdf"},"date":[{"dateType":"Available","dateValue":"2024-07-03"}],"format":"application/pdf","filename":"IPSJ-Z86-6C-03.pdf","filesize":[{"value":"248.2 kB"}],"mimetype":"application/pdf","accessrole":"open_date","version_id":"424bb198-9d9b-4d65-b86f-fb5e32940164","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 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":"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，画像処理および深層学習の発展に伴い，様々なアルゴリズムが開発され，各領域で活躍している．この中でも，動作認識手法は，作業動作の内容や体調状態などの情報を推定可能な技術として，建設現場の安全管理システムの開発に使用されている．しかしながら，作業環境の状況やカメラの撮影角度によって，体の部位が物体に遮蔽され，身体情報の検出および骨格データに基づいたモデルの推定が必ずしも良好に行われない場合がある．本稿では，動き生成技術を用いた骨格データの補間手法を提案した．実験結果から，欠損状態下における14種類の動作の認識精度改善に有用であり，Top-1は平均3.8%，Top-5は平均1.5%向上することが示された．","subitem_description_type":"Other"}]},"item_22_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"92","bibliographic_titles":[{"bibliographic_title":"第86回全国大会講演論文集"}],"bibliographicPageStart":"91","bibliographicIssueDates":{"bibliographicIssueDate":"2024-03-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2024"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":235892,"updated":"2025-01-19T09:28:38.641870+00:00","links":{},"created":"2025-01-19T01:37:38.442949+00:00"}