{"links":{},"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00017988","sets":["934:1085:1096:1098"]},"path":["1098"],"owner":"1","recid":"17988","title":["目領域の切り出しの不定性を考慮した低解像度画像からの視線方向推定"],"pubdate":{"attribute_name":"公開日","attribute_value":"2006-07-15"},"_buckets":{"deposit":"672110f4-fc10-4055-9a99-dd19e892d15d"},"_deposit":{"id":"17988","pid":{"type":"depid","value":"17988","revision_id":0},"owners":[1],"status":"published","created_by":1},"item_title":"目領域の切り出しの不定性を考慮した低解像度画像からの視線方向推定","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"目領域の切り出しの不定性を考慮した低解像度画像からの視線方向推定"},{"subitem_title":"Gaze Estimation from Low Resolution Images Insensitive to Segmentation Error","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"人を観る","subitem_subject_scheme":"Other"}]},"item_type_id":"3","publish_date":"2006-07-15","item_3_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"東京大学生産技術研究所"},{"subitem_text_value":"東京大学生産技術研究所"},{"subitem_text_value":"東京大学生産技術研究所"}]},"item_3_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Institue of Industrial Science, The University of Tokyo","subitem_text_language":"en"},{"subitem_text_value":"Institue of Industrial Science, The University of Tokyo","subitem_text_language":"en"},{"subitem_text_value":"Institue of Industrial Science, The University of Tokyo","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/17988/files/IPSJ-TCVIM4710018.pdf"},"date":[{"dateType":"Available","dateValue":"2008-07-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-TCVIM4710018.pdf","filesize":[{"value":"359.5 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":"8db0f2b8-834f-4da8-9da6-2d15ffc48bd8","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2006 by the Information Processing Society of Japan"}]},"item_3_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"小野, 泰弘"},{"creatorName":"岡部, 孝弘"},{"creatorName":"佐藤洋一"}],"nameIdentifiers":[{}]}]},"item_3_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Yasuhiro, Ono","creatorNameLang":"en"},{"creatorName":"Takahiro, Okabe","creatorNameLang":"en"},{"creatorName":"Yoichi, Sato","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_3_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11560603","subitem_source_identifier_type":"NCID"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_6501","resourcetype":"journal article"}]},"item_3_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1882-7810","subitem_source_identifier_type":"ISSN"}]},"item_3_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"本論文では，見えに基づく手法の枠組みで低解像度の目画像から視線方向を推定する手法を提案する．低解像度画像の入力を前提とすることで，被計測者をカメラの近傍に拘束しないという利点がある一方，目の領域を安定に切り出すのが困難になるという欠点が存在する．そこで提案手法では，様々な切り出しの目画像の学習パターンに対して，通常のSVD（Singular Value Decomposition）を複数のモードを取り扱えるように拡張したNモードSVDを適用することにより，目領域の切り出しの不定性に対処する．このNモードSVDを用いることにより，視線方向の変動のモードと切り出しの変動のモードを注意深く分離し，視線方向の変動を反映する特徴量を抽出する．実画像を用いた評価実験を行うことにより，提案手法がモードの分離を行わない従来のPCA（Principal Component Analysis）および，クラスごとに基底を準備する部分空間法よりも優れていることを確認した．","subitem_description_type":"Other"}]},"item_3_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"We propose an appearance-based method for estimating gaze directions from low resolution images. In estimation of gaze directions from low resolution images, there exist inevitable errors in segmentation of eye regions. To improve the accuracy of gaze estimation, two key ideas are introduced in our method: using a set of training images of eye regions with artificially added segmentation error, and using N-mode SVD (Singular Value Decomposition) in order to separate image variation due to gaze directions from that due to segmentation errors. By using N-mode SVD, the feature vectors of the gaze direction can be extracted. In this paper, we describe the details of our proposed method and report experimental results demonstrating the advantage of our method over the conventional PCA (Principal Component Analysis)-based method and the subspace method in which a subspace is constructed for each class.","subitem_description_type":"Other"}]},"item_3_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"184","bibliographic_titles":[{"bibliographic_title":"情報処理学会論文誌コンピュータビジョンとイメージメディア（CVIM）"}],"bibliographicPageStart":"173","bibliographicIssueDates":{"bibliographicIssueDate":"2006-07-15","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"SIG10(CVIM15)","bibliographicVolumeNumber":"47"}]},"relation_version_is_last":true,"weko_creator_id":"1"},"updated":"2025-01-22T23:02:34.656863+00:00","created":"2025-01-18T22:50:50.485851+00:00","id":17988}