{"_buckets": {"deposit": "0e11f63d-fa9d-4349-82ad-2cd8bf12f3ed"}, "_deposit": {"id": "21702", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "21702"}, "status": "published"}, "_oai": {"id": "oai:nagoya.repo.nii.ac.jp:00021702", "sets": ["314"]}, "author_link": ["64329", "64330", "64331", "64332", "64333", "64334"], "item_10_alternative_title_19": {"attribute_name": "その他のタイトル", "attribute_value_mlt": [{"subitem_alternative_title": "Human Re-identification by Non-linear Distance Metric Learning", "subitem_alternative_title_language": "en"}]}, "item_10_biblio_info_6": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2011-05-12", "bibliographicIssueDateType": "Issued"}, "bibliographicIssueNumber": "48", "bibliographicPageEnd": "146", "bibliographicPageStart": "139", "bibliographicVolumeNumber": "111", "bibliographic_titles": [{"bibliographic_title": "電子情報通信学会技術研究報告. PRMU, パターン認識・メディア理解", "bibliographic_titleLang": "ja"}]}]}, "item_10_description_4": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "人物監視において,特定の人物を追跡し続けるためには,一台の監視カメラの視野は限られていることから,複数の監視カメラを用いる必要がある.一方,カメラの台数が増加しても完全に死角のない領域を広範囲に渡って構築することは困難であることも多い.このために,視野を共有しないカメラ間で人物照合を行い,追跡することが提案されてきた.従来手法においては,人物の服装の色が短時間には変化しないことを前提とした服装の色ヒストグラムによる照合が最も一般的である.しかしながら,複数の視野を共有しないカメラにおいては,各カメラの色校正法や,監視対象の人物の体の向きや姿勢,照明条件が異なるので,そうした影響を受けた色ヒストグラムを用いて単純に照合すると精度低下するおそれがある.このため提案手法では,ヒストグラム間の距離指標を高次元非線形空間で学習し,カメラによる違いの影響をうけにくい照合を目指す.提案手法の有効性は実験により示される.", "subitem_description_language": "ja", "subitem_description_type": "Abstract"}, {"subitem_description": "To do tracking of a specific person, since a field of view in a camera is limited, the use of multiple surveillance cameras is essential. On the other hand, even if the number of these cameras is increased, in many practical scenarios it is difficult to cover a large area without any blind spot. Therefore, human tracking across cameras with non-overlapping field of views have been studied. In previous work, clothing color matching is the most popular method, assuming that clothing colors are not changed in short time. However, matching with histograms via different color calibrations affects adversely accuracy. Therefore in this paper we propose to use distance metric learning with nonlinear kernels to do robust matching in spite of camera differences. The effectiveness of the proposed method is proved through experimental studies.", "subitem_description_language": "en", "subitem_description_type": "Abstract"}]}, "item_10_description_5": {"attribute_name": "内容記述", "attribute_value_mlt": [{"subitem_description": "IEICE Technical Report;IE2011-33, PRMU2011-25, MI2011-25", "subitem_description_language": "en", "subitem_description_type": "Other"}]}, "item_10_identifier_60": {"attribute_name": "URI", "attribute_value_mlt": [{"subitem_identifier_type": "URI", "subitem_identifier_uri": "http://ci.nii.ac.jp/naid/110008726277/"}, {"subitem_identifier_type": "HDL", "subitem_identifier_uri": "http://hdl.handle.net/2237/23852"}]}, "item_10_publisher_32": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "一般社団法人電子情報通信学会", "subitem_publisher_language": "ja"}]}, "item_10_relation_40": {"attribute_name": "シリーズ", "attribute_value_mlt": [{"subitem_relation_name": [{"subitem_relation_name_text": "IEICE Technical Report;IE2011-33, 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"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": "井尻, 善久", "creatorNameLang": "ja"}], "nameIdentifiers": [{"nameIdentifier": "64329", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "労, 世竑", "creatorNameLang": "ja"}], "nameIdentifiers": [{"nameIdentifier": "64330", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "村瀬, 洋", "creatorNameLang": "ja"}], "nameIdentifiers": [{"nameIdentifier": "64331", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "IJIRI, Yoshihisa", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "64332", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "LAO, Shihong", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "64333", 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