{"_buckets": {"deposit": "1f281045-6909-4df1-a3e5-d754e29a567c"}, "_deposit": {"id": "13065", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "13065"}, "status": "published"}, "_oai": {"id": "oai:nagoya.repo.nii.ac.jp:00013065", "sets": ["314"]}, "author_link": ["41098", "41099", "41100", "41101"], "item_10_biblio_info_6": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2008-04-01", "bibliographicIssueDateType": "Issued"}, "bibliographicIssueNumber": "4", "bibliographicPageEnd": "1100", "bibliographicPageStart": "1091", "bibliographicVolumeNumber": "E91-D", "bibliographic_titles": [{"bibliographic_title": "IEICE transactions on information and systems", "bibliographic_titleLang": "en"}]}]}, "item_10_description_4": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "We propose the construction of an appearance manifold with embedded view-dependent covariance matrix to recognize 3D objects which are influenced by geometric distortions and quality degradation effects. The appearance manifold is used to capture the pose variability, while the covariance matrix is used to learn the distribution of samples for gaining noise-invariance. However, since the appearance of an object in the captured image is different for every different pose, the covariance matrix value is also different for every pose position. Therefore, it is important to embed view-dependent covariance matrices in the manifold of an object. We propose two models of constructing an appearance manifold with view-dependent covariance matrix, called the View-dependent Covariance matrix by training-Point Interpolation (VCPI) and View-dependent Covariance matrix by Eigenvector Interpolation (VCEI) methods. Here, the embedded view-dependent covariance matrix of the VCPI method is obtained by interpolating every training-points from one pose to other training-points in a consecutive pose. Meanwhile, in the VCEI method, the embedded view-dependent covariance matrix is obtained by interpolating only the eigenvectors and eigenvalues without considering the correspondences of each training image. As it embeds the covariance matrix in manifold, our view-dependent covariance matrix methods are robust to any pose changes and are also noise invariant. Our main goal is to construct a robust and efficient manifold with embedded view-dependent covariance matrix for recognizing objects from images which are influenced with various degradation effects.", "subitem_description_language": "en", "subitem_description_type": "Abstract"}]}, "item_10_identifier_60": {"attribute_name": "URI", "attribute_value_mlt": [{"subitem_identifier_type": "URI", "subitem_identifier_uri": "http://www.ieice.org/jpn/trans_online/index.html"}, {"subitem_identifier_type": "HDL", "subitem_identifier_uri": "http://hdl.handle.net/2237/14959"}]}, "item_10_publisher_32": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "Institute of Electronics, Information and Communication Engineers", "subitem_publisher_language": "en"}]}, "item_10_relation_43": {"attribute_name": "関連情報", "attribute_value_mlt": [{"subitem_relation_type": "isVersionOf", "subitem_relation_type_id": {"subitem_relation_type_id_text": "http://www.ieice.org/jpn/trans_online/index.html", "subitem_relation_type_select": "URI"}}]}, "item_10_rights_12": {"attribute_name": "権利", "attribute_value_mlt": [{"subitem_rights": "Copyright (C) 2008 IEICE", "subitem_rights_language": "en"}]}, "item_10_select_15": {"attribute_name": "著者版フラグ", "attribute_value_mlt": [{"subitem_select_item": "publisher"}]}, "item_10_source_id_7": {"attribute_name": "ISSN", "attribute_value_mlt": [{"subitem_source_identifier": "0916-8532", "subitem_source_identifier_type": "PISSN"}]}, "item_1615787544753": {"attribute_name": "出版タイプ", "attribute_value_mlt": [{"subitem_version_resource": "http://purl.org/coar/version/c_970fb48d4fbd8a85", "subitem_version_type": "VoR"}]}, "item_access_right": {"attribute_name": "アクセス権", "attribute_value_mlt": [{"subitem_access_right": "open access", "subitem_access_right_uri": "http://purl.org/coar/access_right/c_abf2"}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "Lina", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "41098", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "TAKAHASHI, Tomokazu", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "41099", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "IDE, Ichiro", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "41100", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "MURASE, Hiroshi", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "41101", "nameIdentifierScheme": "WEKO"}]}]}, "item_files": {"attribute_name": "ファイル情報", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_date", "date": [{"dateType": "Available", "dateValue": "2018-02-20"}], "displaytype": "detail", "download_preview_message": "", "file_order": 0, "filename": "355.pdf", "filesize": [{"value": "1.1 MB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_note", "mimetype": "application/pdf", "size": 1100000.0, "url": {"label": "355.pdf", "objectType": "fulltext", "url": "https://nagoya.repo.nii.ac.jp/record/13065/files/355.pdf"}, "version_id": "e681c8a4-eca9-4467-8830-278a1ec9cbf4"}]}, "item_keyword": {"attribute_name": "キーワード", "attribute_value_mlt": [{"subitem_subject": "3D object recognition", "subitem_subject_scheme": "Other"}, {"subitem_subject": "appearance manifold", "subitem_subject_scheme": "Other"}, {"subitem_subject": "view-dependent covariance matrix", "subitem_subject_scheme": "Other"}, {"subitem_subject": "eigenvector interpolation", "subitem_subject_scheme": "Other"}, {"subitem_subject": "eigenvalue interpolation", "subitem_subject_scheme": "Other"}, {"subitem_subject": "eigenspace", "subitem_subject_scheme": "Other"}]}, "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": "Construction of Appearance Manifold with Embedded View-Dependent Covariance Matrix for 3D Object Recognition", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "Construction of Appearance Manifold with Embedded View-Dependent Covariance Matrix for 3D Object Recognition", "subitem_title_language": "en"}]}, "item_type_id": "10", "owner": "1", "path": ["314"], "permalink_uri": "http://hdl.handle.net/2237/14959", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2011-06-28"}, "publish_date": "2011-06-28", "publish_status": "0", "recid": "13065", "relation": {}, "relation_version_is_last": true, "title": ["Construction of Appearance Manifold with Embedded View-Dependent Covariance Matrix for 3D Object Recognition"], "weko_shared_id": -1}