{"id":214244,"updated":"2025-01-19T16:51:00.755334+00:00","links":{},"created":"2025-01-19T01:15:04.206261+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00214244","sets":["1164:3865:10488:10731"]},"path":["10731"],"owner":"44499","recid":"214244","title":["日常的な家電操作による人物識別のためのマウス操作による検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-11-30"},"_buckets":{"deposit":"5de95ffa-d925-41fb-bdea-c48735e615e6"},"_deposit":{"id":"214244","pid":{"type":"depid","value":"214244","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"日常的な家電操作による人物識別のためのマウス操作による検討","author_link":["549220","549223","549221","549222","549224","549218","549217","549219"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"日常的な家電操作による人物識別のためのマウス操作による検討"},{"subitem_title":"Examination by Mouse Operation for Person Identification by Routine Home Appliance Operation","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"WiPショットガンセッション","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2021-11-30","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"公立はこだて未来大学"},{"subitem_text_value":"公立はこだて未来大学"},{"subitem_text_value":"公立はこだて未来大学"},{"subitem_text_value":"京都橘大学"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Future University Hakodate","subitem_text_language":"en"},{"subitem_text_value":"Future University Hakodate","subitem_text_language":"en"},{"subitem_text_value":"Future University Hakodate","subitem_text_language":"en"},{"subitem_text_value":"Kyoto Tachibana 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/214244/files/IPSJ-MBL21101021.pdf","label":"IPSJ-MBL21101021.pdf"},"date":[{"dateType":"Available","dateValue":"2023-11-30"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MBL21101021.pdf","filesize":[{"value":"3.0 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":"35"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"b01ebe3f-2a0f-47bd-b7f9-643f9456d78e","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"須田, 恭平"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"石田, 繁巳"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"稲村, 浩"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"中村, 嘉隆"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Kyohei, Suda","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Shigemi, Ishida","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hiroshi, Inamura","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yoshitaka, Nakamura","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11851388","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":"2188-8817","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"共同生活を行う中で，複数人で共用する家電が多く存在する．このような家電では自分以外の人が使うたびに設定が変更されるため，使うたびに再設定を行う必要がある．本研究では，「家電の操作」という日常的な動作をセンシングすることで人物を識別し，適切な設定を自動的に行う仕組みの実現を目指す．家電を操作する際の「入力デバイスを動かす」「ボタンを押す」などの操作には個人差が生じることが予想されるため，このような操作をセンシングし，個人差が現れる特徴量を抽出して機械学習により操作を行った人物を識別する．本稿では，家電の操作の一例として「PC をスリープから復帰させる際のマウス操作」において人物識別を行った結果を報告する．使用する特徴量を人物識別精度に基づいて取捨選択することで人物識別に有用な特徴量の検討を行った結果，マウスカーソルの移動距離や操作に要した時間などの特徴量を用いることで，4 人の人物を EER=2.5%，12 人の人物を EER=10.0% で識別できた．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"There are many home appliances shared by multiple people when living together. For such home appliances, we need to switch each person's configuration on every use. We are developing an automatic home appliance configuration system that automatically restores users' configuration by recognizing a user based on the user's home appliance control operations. We assume that home appliance control operations, such as moving an input device and pushing a button, include slightly different movements depending on users. The automatic configuration system extracts features describing users' differences from sensing data derived while the user is operating a home appliance and estimates the user by a supervised learning algorithm. As a first step toward the automatic configuration system, this paper presents a user identification method based on a user's computer-mouse operation when resuming from the sleep state. As a result of examining the features useful for person identification by selecting the features to be used based on the person identification accuracy, EER=2.5% for 4 people and EER=10.0% for 12 people. As the feature amount, the feature amount such as the moving distance of the mouse cursor and the time required for the operation was used.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"6","bibliographic_titles":[{"bibliographic_title":"研究報告モバイルコンピューティングと新社会システム（MBL）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2021-11-30","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"21","bibliographicVolumeNumber":"2021-MBL-101"}]},"relation_version_is_last":true,"weko_creator_id":"44499"}}