{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00087111","sets":["1164:3206:6685:6927"]},"path":["6927"],"owner":"11","recid":"87111","title":["複数人物の移動軌跡データからの環境モデルパラメータの逐次ベイズ推定"],"pubdate":{"attribute_name":"公開日","attribute_value":"2012-11-26"},"_buckets":{"deposit":"b8032012-1a32-43c5-a940-c855736383a8"},"_deposit":{"id":"87111","pid":{"type":"depid","value":"87111","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"複数人物の移動軌跡データからの環境モデルパラメータの逐次ベイズ推定","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"複数人物の移動軌跡データからの環境モデルパラメータの逐次ベイズ推定"},{"subitem_title":"Sequential Bayesian Estimation of Environmental Model Parameters from Moving People Trajectories","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"テーマセッション","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2012-11-26","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"千葉大学大学院融合科学研究科情報科学専攻"},{"subitem_text_value":"千葉大学総合メディア基盤センター"},{"subitem_text_value":"千葉大学アカデミック・リンク・センター"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Chiba University, Graduate School of Advanced Integration Science, Information Science","subitem_text_language":"en"},{"subitem_text_value":"Chiba University, Institute of Media and Information Technology","subitem_text_language":"en"},{"subitem_text_value":"Chiba University, Academic Link Center","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/87111/files/IPSJ-CG12149002.pdf"},"date":[{"dateType":"Available","dateValue":"2014-11-26"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CG12149002.pdf","filesize":[{"value":"293.5 kB"}],"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":"a78d9617-49aa-4013-8844-debc56958380","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2012 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"田代, 祐志"},{"creatorName":"川本, 一彦"},{"creatorName":"岡本, 一志"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yuji, Tashiro","creatorNameLang":"en"},{"creatorName":"Kazuhiko, Kawamoto","creatorNameLang":"en"},{"creatorName":"Kazushi, Okamoto","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"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_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"複数人物移動に現れる誘引や反発などの相互作用を確率的セルオートマトンモデルで表現し，そこに含まれるパラメータを移動軌跡データから推定する手法を提案する．このモデルでは，人物は，空間を格子状に区切った 「セル」 に配置され，セルに埋め込まれた値に基づき確率的に次の移動場所を決定する．その値は，壁や出入口などの静的環境と動的に変化する人物移動軌跡の両者に依存して決定される．本研究では，静的環境を決めるパラメータとして，目的地からの距離によって誘引の強弱を制御するものと，各人物がどの目的地へ向かっているかを指定するラベルを導入し，それを環境モデルパラメータと呼ぶことにする．これらのパラメータは観測できない隠れ変数であるため，一般状態空間モデルの枠組みで推定問題を定式化し，粒子フィルタを用いて数値的に推定する．実験では，公開されている実際の移動軌跡データに対してパラメータを推定し，推定したパラメータによるシミュレーションがどのくらい実際の移動軌跡に近いかを評価した．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"7","bibliographic_titles":[{"bibliographic_title":"研究報告グラフィクスとCAD（CG）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2012-11-26","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"2","bibliographicVolumeNumber":"2012-CG-149"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"id":87111,"updated":"2025-01-21T17:24:12.687431+00:00","links":{},"created":"2025-01-18T23:37:58.267621+00:00"}