{"links":{},"id":53409,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00053409","sets":["1164:4619:4721:4725"]},"path":["4725"],"owner":"1","recid":"53409","title":["幾何学的計算の統計解析：I．基礎理論"],"pubdate":{"attribute_name":"公開日","attribute_value":"1992-03-27"},"_buckets":{"deposit":"d1caa1b0-e55e-4d27-bfa7-cd316d7f8550"},"_deposit":{"id":"53409","pid":{"type":"depid","value":"53409","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"幾何学的計算の統計解析：I．基礎理論","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"幾何学的計算の統計解析：I．基礎理論"},{"subitem_title":"Statistical Analysis of Geometric Computation : Part 1. Fundamental Theory","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"1992-03-27","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"群馬大学工学部情報工学科"},{"subitem_text_value":"群馬大学工学部情報工学科"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Department of Computer Science Gunma University","subitem_text_language":"en"},{"subitem_text_value":"Department of Computer Science Gunma 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/53409/files/IPSJ-CVIM91077001.pdf"},"date":[{"dateType":"Available","dateValue":"1994-03-27"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CVIM91077001.pdf","filesize":[{"value":"1.1 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":"50519068-ceb5-4a82-94f2-54b48e792a0e","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 1992 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"浦沢, 康ニ"},{"creatorName":"金谷健一"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Kouji, Urasawa","creatorNameLang":"en"},{"creatorName":"Kenichi, Kanatani","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":"本論文では、コンピュータビジョンの基礎となる画像データの幾何学的計算の誤差の統計的挙動を一般的に定式化する。まず「Nベクトル」の「共分散行列」により画像のノイズを統計的にモデル化し、直線の交点や2点を通る直線のNベクトルの共分散行列を計算する。これを用いて交点の推定や直線あてはめのための最小二乗法の「最適重み」を導出し、最適推定値の共分散行列を計算する。また、これらの計算には「統計的偏差」が存在することも指摘する。最後に「不偏推定値」の計算方法を示す。","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"This paper studies statistical behaviors of errors involved in fundamental geometric computations for computer vision. We first present a statistical model of image noise in terms of the \"covariance matrix\" of the \"N-Vector\". Using this model, we compute the covariance matrices of N-vectors of lines and their intersections. Then, we determine the \"optimal weights\" for the least-squares optimization for intersection estimation and line fitting, and compute the covariance matrix of the resulting optimal estimate. We also point out that \"statistical biases\" exist in such computations, and present schemes of computing \"unbiased estimates\".","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","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":"1","bibliographicIssueDates":{"bibliographicIssueDate":"1992-03-27","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"29(1991-CVIM-077)","bibliographicVolumeNumber":"1992"}]},"relation_version_is_last":true,"weko_creator_id":"1"},"created":"2025-01-18T23:17:30.959569+00:00","updated":"2025-01-22T06:20:07.246968+00:00"}