{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00094861","sets":["1164:4619:6988:7247"]},"path":["7247"],"owner":"11","recid":"94861","title":["Tracklet特徴量とMean-Shiftクラスタリングによる歩行者流量推定方式の提案"],"pubdate":{"attribute_name":"公開日","attribute_value":"2013-08-26"},"_buckets":{"deposit":"a1208f12-538c-41f4-85cf-52badcb18325"},"_deposit":{"id":"94861","pid":{"type":"depid","value":"94861","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"Tracklet特徴量とMean-Shiftクラスタリングによる歩行者流量推定方式の提案","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Tracklet特徴量とMean-Shiftクラスタリングによる歩行者流量推定方式の提案"},{"subitem_title":"Pedestrian Flow Estimation using Tracklet and Mean-Shift Clustering","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2013-08-26","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"(株)日立製作所中央研究所"},{"subitem_text_value":"(株)日立製作所中央研究所"},{"subitem_text_value":"(株)日立製作所中央研究所"},{"subitem_text_value":"(株)日立製作所中央研究所"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Hitachi Ltd., Central Research Laboratory","subitem_text_language":"en"},{"subitem_text_value":"Hitachi Ltd., Central Research Laboratory","subitem_text_language":"en"},{"subitem_text_value":"Hitachi Ltd., Central Research Laboratory","subitem_text_language":"en"},{"subitem_text_value":"Hitachi Ltd., Central Research Laboratory","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/94861/files/IPSJ-CVIM13188020.pdf"},"date":[{"dateType":"Available","dateValue":"2015-08-26"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CVIM13188020.pdf","filesize":[{"value":"819.1 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":"20"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"f6b57052-627d-412f-a404-0dbe35b91a50","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2013 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"米司, 健一"},{"creatorName":"吉永, 智明"},{"creatorName":"松原, 大輔"},{"creatorName":"額賀, 信尾"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Kenichi, Yoneji","creatorNameLang":"en"},{"creatorName":"Tomoaki, Yoshinaga","creatorNameLang":"en"},{"creatorName":"Daisuke, Matsubara","creatorNameLang":"en"},{"creatorName":"Nobuo, Nukaga","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11131797","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":"監視カメラの映像から歩行者の流量を推定する技術に関し，低演算量でロバストな推定結果が得られる方式を提案する．従来の流量推定方式では，画像中から人の流量をロバストに検出するために，HOG 等の演算量の多い特徴量を用いる必要があった．これに対し提案方式では，演算量の少ない Tracklet 特徴量を， Mean-Shift クラスタリングを用いて歩行者毎の動き情報に変換して解析することで，低演算量かつロバストな流量推定が可能となった．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"We developed a method of pedestrian flow estimation for surveillance camera system. Previous methods like HOG descriptor need high computational cost for accurate estimation. In this paper, we present a robust method for pedestrian flow estimation of which computational cost is low. Our method uses Mean-Shift clustering to divide tracklets into each pedestrian's information, and it achieves both accurate estimation and low computational cost.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"7","bibliographic_titles":[{"bibliographic_title":"研究報告コンピュータビジョンとイメージメディア（CVIM）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2013-08-26","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"20","bibliographicVolumeNumber":"2013-CVIM-188"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"id":94861,"updated":"2025-01-21T14:19:47.401177+00:00","links":{},"created":"2025-01-18T23:42:04.641987+00:00"}