{"created":"2025-01-18T23:16:33.957002+00:00","updated":"2025-01-22T06:53:39.376438+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00052181","sets":["1164:4619:4631:4634"]},"path":["4634"],"owner":"1","recid":"52181","title":["全方位視覚センサを用いた方位不変特徴量による自己位置識別"],"pubdate":{"attribute_name":"公開日","attribute_value":"2006-05-18"},"_buckets":{"deposit":"28c477f6-00ff-4e32-9cb3-69ce6fbf230c"},"_deposit":{"id":"52181","pid":{"type":"depid","value":"52181","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"全方位視覚センサを用いた方位不変特徴量による自己位置識別","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"全方位視覚センサを用いた方位不変特徴量による自己位置識別"},{"subitem_title":"Location Identification by Azimuth-Invariant Features from Omnidirectional Images","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2006-05-18","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"大阪大学大学院基礎工学研究科"},{"subitem_text_value":"大阪大学大学院基礎工学研究科"},{"subitem_text_value":"大阪大学大学院基礎工学研究科"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Engineering Science, Osaka University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Engineering Science, Osaka University","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Engineering Science, Osaka 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/52181/files/IPSJ-CVIM06154014.pdf"},"date":[{"dateType":"Available","dateValue":"2008-05-18"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CVIM06154014.pdf","filesize":[{"value":"1.7 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":"20"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"3f1a19e2-fe82-419e-85d1-f99d93df02d1","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2006 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"金, 時均"},{"creatorName":"岩井, 儀雄"},{"creatorName":"谷内田, 正彦"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Tokitada, Kin","creatorNameLang":"en"},{"creatorName":"Yoshio, Iwai","creatorNameLang":"en"},{"creatorName":"Masahiko, Yachida","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":"コンピュータやセンサを身につけてさまざまな作業の支援を行うウェアラブルシステムには、自己位置情報の提供が有益な情報となる。本論文では、ウェアラブルな全方位視覚センサより得られる画像の記憶に基づく自己位置識別手法を提案する。提案手法では、画像上で適当な半径の円周上の画素情報を抽出し、円周方向に積分を行うことで、全方位画像から撮影時の方位に不変な特徴量を抽出する手法を提案する。さらに、抽出した特徴量から部分空間を構成し、部分空間内で最も近接した学習画像を検索することによって自己位置識別を行なう。実際に屋内および屋外環境で撮影された全方位画像を用いて実験を行い、提案手法の有効性を確認した。","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Self-location is very informative for wearable systems. In this paper, we propose a method for identifying user's location from an omnidirectional image by azimuth-invariant features. Azimuth-invariant features are extracted from an omnidirectional image by integrating pixel information circumferentially, and then its location is recognized from the features projected into a sub-space made from learning data. We show the effectiveness of our method by experimental results in real images.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"106","bibliographic_titles":[{"bibliographic_title":"情報処理学会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":"99","bibliographicIssueDates":{"bibliographicIssueDate":"2006-05-18","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"51(2006-CVIM-154)","bibliographicVolumeNumber":"2006"}]},"relation_version_is_last":true,"weko_creator_id":"1"},"id":52181,"links":{}}