{"created":"2023-06-19T11:40:04.927202+00:00","id":8377,"links":{},"metadata":{"_buckets":{"deposit":"77d66803-7855-4086-b478-8ecdd007de32"},"_deposit":{"created_by":15,"id":"8377","owners":[15],"pid":{"revision_id":0,"type":"depid","value":"8377"},"status":"published"},"_oai":{"id":"oai:mie-u.repo.nii.ac.jp:00008377","sets":["366:638:639"]},"author_link":[],"item_10001_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2007-08-27","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"87","bibliographicPageEnd":"144","bibliographicPageStart":"139","bibliographicVolumeNumber":"2007","bibliographic_titles":[{"bibliographic_title":"情報処理学会研究報告. CVIM, [コンピュータビジョンとイメージメディア]"}]}]},"item_10001_description_19":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_description":"application/pdf","subitem_description_type":"Other"}]},"item_10001_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"We propose an automatic frontal face recognition method using gradient features. Our proposed method consists of three main stages : 1) face detection, 2) detection of tight bounding box of face using the result of facial feature extraction and 3) face recognition. In each stage, we use the gradient of image instead of pixel values. Face recognition experiments based on CSU Face identification Evaluation scheme using FERET database suggests that the gradient features has better performance than conventional pixel-based face recognition.","subitem_description_type":"Abstract"},{"subitem_description":"特徴量に画像の濃度こう配を用いた正面顔自動認識手法を提案する。提案手法は主に以下の3つの処理からなる.(1)画像探索に基づく顔検出,(2)検出された顔領域内の顔部品検出に基づく顔外擦枠の検出,(3)顔外接枠内の顔に対する見え方に基づく顔認識.それぞれの処理においては,画像濃度値のかわりに濃度値のこう配を特徴量として用いる.FERETデータベースに含まれる正面顔画像を用いた.CSU Face Identification Evaluationに従った実験の結果,濃度こう配特徴は,従来の画像特徴よりも低次元の特徴量で高い認識性能を持つことが分かった.","subitem_description_type":"Abstract"}]},"item_10001_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会"}]},"item_10001_rights_15":{"attribute_name":"権利","attribute_value_mlt":[{"subitem_rights":"ここに掲載した著作物の利用に関する注意 本著作物の著作権は（社）情報処理学会に帰属します。本著作物は著作権者である情報処理学会の許可のもとに掲載するものです。ご利用に当たっては「著作権法」ならびに「情報処理学会倫理綱領」に従うことをお願いいたします。"},{"subitem_rights":"Notice for the use of this material The copyright of this material is retained by the Information Processing Society of Japan (IPSJ). This material is published on this web site with the agreement of the author (s) and the IPSJ. Please be complied with Copyright Law of Japan and the Code of Ethics of the IPSJ if any users wish to reproduce, make derivative work, distribute or make available to the public any part or whole thereof.\nAll Rights Reserved, Copyright (C) Information Processing Society of Japan.\nComments are welcome. Mail to address , please."}]},"item_10001_source_id_11":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11131797","subitem_source_identifier_type":"NCID"}]},"item_10001_source_id_9":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"0919-6072","subitem_source_identifier_type":"PISSN"}]},"item_10001_subject_21":{"attribute_name":"日本十進分類法","attribute_value_mlt":[{"subitem_subject":"007","subitem_subject_scheme":"NDC"}]},"item_10001_text_25":{"attribute_name":"その他のタイトル","attribute_value_mlt":[{"subitem_text_value":"濃度こう配特徴を用いた全自動正面顔認識(テーマ関連セッション3)"}]},"item_10001_text_70":{"attribute_name":"資源タイプ（三重大）","attribute_value_mlt":[{"subitem_text_value":"Journal Article / 学術雑誌論文"}]},"item_10001_version_type_20":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Ohyma, Wataru","creatorNameLang":"en"},{"creatorName":"大山, 航","creatorNameLang":"ja"}]},{"creatorNames":[{"creatorName":"Wakabayashi, Tetsushi","creatorNameLang":"en"},{"creatorName":"若林, 哲史","creatorNameLang":"ja"}]},{"creatorNames":[{"creatorName":"Kimura, Fumitaka","creatorNameLang":"en"}],"familyNames":[{"familyName":"木村, 文隆","familyNameLang":"ja"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2017-02-18"}],"displaytype":"detail","filename":"40A12202.pdf","filesize":[{"value":"581.3 kB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"40A12202.pdf","url":"https://mie-u.repo.nii.ac.jp/record/8377/files/40A12202.pdf"},"version_id":"8104cda5-1ab8-4873-9850-d03fe4f25953"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"journal article","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"Automatic frontal face recognition using gradient features","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Automatic frontal face recognition using gradient features","subitem_title_language":"en"}]},"item_type_id":"10001","owner":"15","path":["639"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2010-05-21"},"publish_date":"2010-05-21","publish_status":"0","recid":"8377","relation_version_is_last":true,"title":["Automatic frontal face recognition using gradient features"],"weko_creator_id":"15","weko_shared_id":-1},"updated":"2023-10-16T02:34:18.584426+00:00"}