{"updated":"2025-01-19T19:13:20.741436+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00207208","sets":["1164:4061:10116:10349"]},"path":["10349"],"owner":"44499","recid":"207208","title":["フットサル動画分析のためのデータ収集システム"],"pubdate":{"attribute_name":"公開日","attribute_value":"2020-09-22"},"_buckets":{"deposit":"f6c5b3aa-9f74-446f-880e-d41f36d59ee5"},"_deposit":{"id":"207208","pid":{"type":"depid","value":"207208","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"フットサル動画分析のためのデータ収集システム","author_link":["516706","516707","516709","516708"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"フットサル動画分析のためのデータ収集システム"}]},"item_type_id":"4","publish_date":"2020-09-22","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"慶應義塾大学環境情報学部"},{"subitem_text_value":"慶應義塾大学大学院政策・メディア研究科"},{"subitem_text_value":"慶應義塾大学大学院政策・メディア研究科"},{"subitem_text_value":"慶應義塾大学環境情報学部"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Faculty of Environment and Information Studies, Keio University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Media and Governance, Keio University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Media and Governance, Keio University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Environment and Information Studies, Keio 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/207208/files/IPSJ-UBI20067029.pdf","label":"IPSJ-UBI20067029.pdf"},"date":[{"dateType":"Available","dateValue":"2022-09-22"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-UBI20067029.pdf","filesize":[{"value":"1.6 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":"36"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"a032eae4-05c0-4974-b59a-fc6d396fd2df","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2020 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"大村, 昇平"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"谷村, 朋樹"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"大越, 匡"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"中澤, 仁"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11838947","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":"2188-8698","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"データを収集する機器の進化に伴い，スポーツの世界でも多様な分析を行うことが可能になっている．しかし，分析に必要なデバイスは高価であるため，データ収集・分析の恩恵を受けることができるのは一部の人に限られている．この問題を解決するために，多くの人に普及しているスマートフォンで撮影された動画から，データを収集・分析できるシステムを提案する．提案するシステムでは，物体検出の手法を用いて選手とボールを検出し，その検出結果のコート上での位置を使用することでフットサルの試合を分析する．本研究では，システムの個別の技術精度と分析の精度という 2 軸で評価した．システム個別の評価項目は，選手とボールの検出精度，選手の分類の精度，分析の精度の評価項目は支配率の精度とし，実験を行った．選手とボールの検出精度は選手が mAPスコア0.81，ボールは mAP スコア 0.437 となり，選手分類の精度は高い精度を出すことができたが，1 クラス 30 ％と低い精度になった．また，支配率に関しては，目視で判断した場合と大きな差はなかった．精度が低くなったものに関して考察した結果，小さな物体を検出するために更なる研究が求められるとわかった．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告ユビキタスコンピューティングシステム（UBI）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2020-09-22","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"29","bibliographicVolumeNumber":"2020-UBI-67"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:08:57.634840+00:00","id":207208,"links":{}}