{"_buckets": {"deposit": "2c112d3e-99cc-43f9-8c48-7061b7e487b4"}, "_deposit": {"id": "8504", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "8504"}, "status": "published"}, "_oai": {"id": "oai:nagoya.repo.nii.ac.jp:00008504", "sets": ["322"]}, "author_link": ["23825", "23826", "23827", "23828", "23829", "23830"], "item_10_biblio_info_6": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2001-01", "bibliographicIssueDateType": "Issued"}, "bibliographicIssueNumber": "1", "bibliographicPageEnd": "15", "bibliographicPageStart": "1", "bibliographicVolumeNumber": "42", "bibliographic_titles": [{"bibliographic_title": "情報処理学会論文誌", "bibliographic_titleLang": "ja"}]}]}, "item_10_description_4": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "自動車追跡システムのロバスト性向上の主な障害として, 移動する物体(自動車)の影がある.精度の高い物体モデルを用いたとしても, 追跡プロセスは影によって混乱される.本論文では, 背景・物体領域と同様, 影もモデル化することが可能な, HMMに基づく領域分離手法を提案する.他の多くの確率的背景モデルと異なり, 本モデルにおいては学習データとして特定のものを選択する必要はない.複数のカテゴリ(背景, 物体, 影)を含む映像シーケンスから自動的にこれらのカテゴリ率を学習することが可能だからである.各カテゴリに関する時間的持続性を利用するだけではなく, 輝度値と空間的情報に基づくSobel値を観測シンボルとして用いることによって, カテゴリ間の曖昧性を減少させる.本手法は, ローレベルの追跡プロセスとして, または動画像による輪郭追跡システムのコンポーネントとして使われるのに適する.実際に高速道路を撮影した映像シーケンスに対して本手法を適用した結果, 各画像において, 背景, 移動物体, および移動物体の影の3種類をリアルタイムで高精度に分離できた. ", "subitem_description_language": "ja", "subitem_description_type": "Abstract"}, {"subitem_description": "The main obstacle to the robustness of car tracking is large shadows of vehicles. Even with a good foreground model, the tracking process is liable to be disrupted by the shadows. This paper proposes an HMM-based foreground-background segmentation method which is capable of modeling shadow as well as foreground and background regions. Unlike many other probabilistic background models, it is not necessary to select the training data since the distributions for different regions can be learnt from an ordinary video sequence. The ambiguity among different regions(categories)is reduced by not only using the temporal continuity constraint for each category, but using jointly intensity and Sobel values, which measure the homogeneity of a region in space, as the observation symbols. This method itself functions a low level tracker. It can be also used as a low level process for an active contour based car tracker. Results on real-world motorway sequences show that using the proposed method, it is possible to accurately segment the image into background, cars and the shadow of cars in real time.", "subitem_description_language": "en", "subitem_description_type": "Abstract"}]}, "item_10_identifier_60": {"attribute_name": "URI", "attribute_value_mlt": [{"subitem_identifier_type": "HDL", "subitem_identifier_uri": "http://hdl.handle.net/2237/10251"}]}, "item_10_publisher_32": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "情報処理学会", "subitem_publisher_language": "ja"}]}, "item_10_rights_12": {"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。 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. All Rights Reserved, Copyright (C) Information Processing Society of Japan. Comments are welcome. Mail to address: 　editj\u003cat\u003eipsj.or.jp, please.", "subitem_rights_language": "ja"}]}, "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": "03875806", "subitem_source_identifier_type": "PISSN"}]}, "item_10_text_14": {"attribute_name": "フォーマット", "attribute_value_mlt": [{"subitem_text_value": "application/pdf"}]}, "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": "加藤, ジェーン", "creatorNameLang": "ja"}], "nameIdentifiers": [{"nameIdentifier": "23825", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "KATO, Jien", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "23826", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "渡邉, 豊英", "creatorNameLang": "ja"}], "nameIdentifiers": [{"nameIdentifier": "23827", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "WATANABE, Toyohide", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "23828", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "米田, 政明", "creatorNameLang": "ja"}], "nameIdentifiers": [{"nameIdentifier": "23829", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "YONEDA, Masaaki", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "23830", "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": "2018-02-19"}], "displaytype": "detail", "download_preview_message": "", "file_order": 0, "filename": "ipsjj_42_1_1.pdf", "filesize": [{"value": "1.6 MB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_note", "mimetype": "application/pdf", "size": 1600000.0, "url": {"label": "ipsjj_42_1_1.pdf", "objectType": "fulltext", "url": "https://nagoya.repo.nii.ac.jp/record/8504/files/ipsjj_42_1_1.pdf"}, "version_id": "2b43cd6b-6b22-4b4a-b247-11cd26963c31"}]}, "item_language": {"attribute_name": "言語", "attribute_value_mlt": [{"subitem_language": "jpn"}]}, "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": "HMMに基づく交通監視映像の背景・物体・影の分離手法", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "HMMに基づく交通監視映像の背景・物体・影の分離手法", "subitem_title_language": "ja"}]}, "item_type_id": "10", "owner": "1", "path": ["322"], "permalink_uri": "http://hdl.handle.net/2237/10251", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2008-07-16"}, "publish_date": "2008-07-16", "publish_status": "0", "recid": "8504", "relation": {}, "relation_version_is_last": true, "title": ["HMMに基づく交通監視映像の背景・物体・影の分離手法"], "weko_shared_id": -1}