{"links":{},"id":52146,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00052146","sets":["1164:4619:4631:4633"]},"path":["4633"],"owner":"1","recid":"52146","title":["顔らしさ分布を利用した顔検出手法"],"pubdate":{"attribute_name":"公開日","attribute_value":"2006-09-08"},"_buckets":{"deposit":"ab64126e-05c7-4a50-8252-96b4dcea5e8e"},"_deposit":{"id":"52146","pid":{"type":"depid","value":"52146","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"顔らしさ分布を利用した顔検出手法","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"顔らしさ分布を利用した顔検出手法"},{"subitem_title":"Face Detection Algorithm using Face Likelihood Distribution","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2006-09-08","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京工業大学大学院理工学研究科"},{"subitem_text_value":"東京工業大学大学院理工学研究科"},{"subitem_text_value":"東京工業大学大学院理工学研究科"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Science and Engineering,Tokyo Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Science and Engineering,Tokyo Institute of Technology","subitem_text_language":"en"},{"subitem_text_value":"Graduate School of Science and Engineering,Tokyo Institute of Technology","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/52146/files/IPSJ-CVIM06155011.pdf"},"date":[{"dateType":"Available","dateValue":"2008-09-08"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CVIM06155011.pdf","filesize":[{"value":"1.5 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":"c87e3188-5cd9-41b0-af06-4c2b1a9af8d2","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":"高塚, 皓正"},{"creatorName":"田中, 正行"},{"creatorName":"奥富, 正敏"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Hiromasa, Takatsuka","creatorNameLang":"en"},{"creatorName":"Masayuki, Tanaka","creatorNameLang":"en"},{"creatorName":"Masatoshi, Okutomi","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":"顔検出はコンピュータビジョンにおいて，近年注目されている技術の一つであり，様々な研究が行なわれている従来の顔検出に関する研究の多くは，切り取られたサブウィンドウが顔かどうかを判別する識別器を改良することを主な目的としている．この識別器は顔検出を行なう際の?プロセスとして重要であるしかし，これらの識別器は各サプウィンドウに対して，独立に顔または非顔を判定するため，識別器の出力(顔らしさ)の高い非顔画像を誤検出してしまうことがよくある．本報告では，顔と非顔における顔らしさ分布の違いに着目し，この違いを陽に利用した新しい顔検出の枠組みについて提案する．提案手法では，顔らしさ分布を生成し，統合処理により顔と非顔の違いを強調することで，従来手法で誤検出していた非顔を正しく分類することが可能になる．実験では，テストデータセットと実画像を用いて，提案手法の有効性を確認したその結果，それぞれ20％と１０％の検出率の向上が見られた．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Face detection is a useful technique in computer vision. Many face detectors have been developed in the literature. Almost all approaches for face detection focus on the face detectors which classify a given subwindow into face or non-face. However, in face detection process, since the detectors also evaluate the scanned sub-windows independently, non-faces with high face likelihood are often misdetected. In this paper, we propose a novel face detection algorithm which explicitly uses difference of face likelihood distribution between faces and non-faces. The proposed algorithm can correctly classify the non-faces misdetected by the existing algorithm. The face likelihood distribution is generated and integrated to emphasize the difference between faces and nonfaces. Experiments with pre-scanned data set and real-world images show that the proposed algorithm improves the detection rate approximately by 20% and 10%, respectively.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"80","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":"73","bibliographicIssueDates":{"bibliographicIssueDate":"2006-09-08","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"93(2006-CVIM-155)","bibliographicVolumeNumber":"2006"}]},"relation_version_is_last":true,"weko_creator_id":"1"},"created":"2025-01-18T23:16:32.299446+00:00","updated":"2025-01-22T06:54:35.383394+00:00"}