{"id":2003831,"created":"2025-08-25T06:59:07.260466+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:02003831","sets":["1164:3206:1739944645997:1756104364139"]},"path":["1756104364139"],"owner":"80578","recid":"2003831","title":["骨格情報とLLMを用いた個別対応型姿勢評価手法"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2025-09-01"},"_buckets":{"deposit":"2f76fbdb-df67-4f74-a40f-7a19caa2bf85"},"_deposit":{"id":"2003831","pid":{"type":"depid","value":"2003831","revision_id":0},"owners":[80578],"status":"published","created_by":80578},"item_title":"骨格情報とLLMを用いた個別対応型姿勢評価手法","author_link":[],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"骨格情報とLLMを用いた個別対応型姿勢評価手法","subitem_title_language":"ja"},{"subitem_title":"Personalized Posture Evaluation Method Using Skeletal Information and a LLM","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2025-09-01","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"静岡大学"},{"subitem_text_value":"静岡大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Shizuoka University","subitem_text_language":"en"},{"subitem_text_value":"Shizuoka 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/2003831/files/IPSJ-CG25199008.pdf","label":"IPSJ-CG25199008.pdf"},"date":[{"dateType":"Available","dateValue":"2027-09-01"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CG25199008.pdf","filesize":[{"value":"1.7 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":"87825d22-6b75-47cb-97ea-0c45cf194816","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2025 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"桂,陸登"}]},{"creatorNames":[{"creatorName":"岡部,誠"}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Rikuto Katsura","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Makoto Okabe","creatorNameLang":"en"}]}]},"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":"本研究では，ユーザが自身の理想とする姿勢を基準として登録しておき，30分ごとにその時点での姿勢と理想の姿勢を比較することで，姿勢の変化や崩れを検出，指摘するシステムを提案する．システム起動時，Webカメラを起動する．ユーザはまず座った状態で自身の理想の姿勢をとり，Enterキーを押す．すると，MediaPipeによりWebカメラの映像のみからJsonファイル形式で骨格情報が保存される．それから30分後，その時点の姿勢の骨格情報の保存が行われる．そして，保存された骨格情報はChatGPTに送信され，姿勢の評価と改善案の出力が行われる．以降，30分経過する度に，その時点の姿勢と理想の姿勢との比較評価が繰り返される．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In this study, we propose a system that allows the user to register their ideal posture as a reference and, by comparing it with their current posture every 30 minutes, detects and points out changes or deterioration in posture.When the system is launched, the webcam is activated. The user first sits in their ideal posture and presses the Enter key. Then, using MediaPipe, skeletal information is extracted solely from the webcam image and saved in JSON file format. After 30 minutes, the skeletal information of the current posture is recorded again. The saved skeletal data is then sent to ChatGPT, which outputs a posture evaluation and suggestions for improvement. This comparison between the current posture and the ideal posture is repeated at 30-minute intervals thereafter.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","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":"2025-09-01","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"8","bibliographicVolumeNumber":"2025-CG-199"}]},"relation_version_is_last":true,"weko_creator_id":"80578"},"updated":"2025-08-25T06:59:10.811057+00:00","links":{}}