{"links":{},"id":232665,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00232665","sets":["1164:3980:11478:11514"]},"path":["11514"],"owner":"44499","recid":"232665","title":["環境に適した群衆モデル選択のためのオートエンコーダを用いた環境分類手法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-02-26"},"_buckets":{"deposit":"7f4e6cb3-e8bd-40db-958e-e017886e6ed5"},"_deposit":{"id":"232665","pid":{"type":"depid","value":"232665","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"環境に適した群衆モデル選択のためのオートエンコーダを用いた環境分類手法","author_link":["630435","630436"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"環境に適した群衆モデル選択のためのオートエンコーダを用いた環境分類手法"}]},"item_type_id":"4","publish_date":"2024-02-26","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京女子大学大学院理学研究科"},{"subitem_text_value":"東京女子大学大学院理学研究科"}]},"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/232665/files/IPSJ-ITS24096008.pdf","label":"IPSJ-ITS24096008.pdf"},"date":[{"dateType":"Available","dateValue":"2026-02-26"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-ITS24096008.pdf","filesize":[{"value":"6.6 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":"37"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"60f323d1-50e5-4110-8fc9-06833e608831","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"中澤, 咲"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"加藤, 由花"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11515904","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":"2188-8965","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"自律移動ロボットのナビゲーションでは，移動ポリシーの学習などのために，群衆シミュレーション分野で開発された様々な群衆モデルが用いられる．しかし，群衆の動きは環境に大きく依存し，あらゆる環境に適用できる一つの群衆モデルは存在していない．本稿では，ロボットシミュレーションでの利用を前提に，群衆の動きや地理的形状に関する特徴抽出を行うことで，シミュレーション対象となる時空間を複数カテゴリに分類し，それらのカテゴリごとに適切な群衆モデルを選択する手法を提案する．具体的には，歩行者の移動傾向を可視化した画像データを生成し，オートエンコーダにより特徴抽出を行い，その結果をクラスタリングすることでカテゴリ分類を行う．本稿では，歩行者移動軌跡データセットを用いた評価実験により，視覚的に似ている特徴画像が同じカテゴリに分類されることを示す．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"7","bibliographic_titles":[{"bibliographic_title":"研究報告高度交通システムとスマートコミュニティ（ITS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2024-02-26","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"8","bibliographicVolumeNumber":"2024-ITS-96"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:33:39.804176+00:00","updated":"2025-01-19T10:21:42.189063+00:00"}