{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00229020","sets":["1164:3980:11162:11356"]},"path":["11356"],"owner":"44499","recid":"229020","title":["低解像度サーモカメラを用いた屋内人物位置追跡"],"pubdate":{"attribute_name":"公開日","attribute_value":"2023-11-08"},"_buckets":{"deposit":"799719ca-06ff-42f4-83a6-a30e02ab66f9"},"_deposit":{"id":"229020","pid":{"type":"depid","value":"229020","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"低解像度サーモカメラを用いた屋内人物位置追跡","author_link":["615135","615136","615132","615133","615134"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"低解像度サーモカメラを用いた屋内人物位置追跡"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"映像とヒューマンセンシング","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2023-11-08","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"株式会社NTTドコモ"},{"subitem_text_value":"株式会社NTTドコモ"},{"subitem_text_value":"株式会社NTTドコモ／現在，NTT社会情報研究所"},{"subitem_text_value":"株式会社NTTドコモ"},{"subitem_text_value":"株式会社NTTドコモ"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"NTT DOCOMO, INC.","subitem_text_language":"en"},{"subitem_text_value":"NTT DOCOMO, INC.","subitem_text_language":"en"},{"subitem_text_value":"NTT DOCOMO, INC. / Presently with NTT Social Informatics Laboratories","subitem_text_language":"en"},{"subitem_text_value":"NTT DOCOMO, INC.","subitem_text_language":"en"},{"subitem_text_value":"NTT DOCOMO, INC.","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/229020/files/IPSJ-ITS23095019.pdf","label":"IPSJ-ITS23095019.pdf"},"date":[{"dateType":"Available","dateValue":"2025-11-08"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-ITS23095019.pdf","filesize":[{"value":"697.5 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":"37"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"d5288e3b-c830-4a61-b317-cd410b41be77","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2023 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"関根, 光太郎"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"田中, 宏昌"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"熊川, 瑛至"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"山田, 渉"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"落合, 桂一"}],"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":"IoT 技術の発展により人物の位置情報をトリガーとしたサービスが注目されている．一方で，人物検知におけるセンシング技術には精度とプライバシのトレードオフの問題がある．そこで本研究では，低解像度サーモカメラ動画を用いて，人物が重なる時もそれぞれを区別して追跡する Tracking-by-Detection 手法を提案する．提案手法では，RGB カメラ (960×1280 ピクセル) で平均 0.923 の Multiple Object Tracking Accuracy (MOTA) スコアに対し，RGB カメラの 1/40 の解像度にもかかわらずサーモカメラ (24×32 ピクセル) で平均 0.862 の MOTA スコアを達成した．さらに，サーモカメラ映像をダウンサンプリングし，プライバシ性を向上した時の性能劣化を評価すると，12×16 ピクセルでは 18×24，24×32 ピクセルと比べ IDF1，IDR，IDP スコアがそれぞれ 0.2 以上下がり，明確な性能劣化を確認した．本技術により，低解像度の温度情報のみを用いてプライバシの懸念を抑えつつ人物行動を理解することが期待される．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"4","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":"2023-11-08","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"19","bibliographicVolumeNumber":"2023-ITS-95"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":229020,"updated":"2025-01-19T11:38:15.279179+00:00","links":{},"created":"2025-01-19T01:28:09.238010+00:00"}