{"_buckets": {"deposit": "c07dc320-47db-457d-877e-20560b595bf6"}, "_deposit": {"id": "12158", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "12158"}, "status": "published"}, "_oai": {"id": "oai:nagoya.repo.nii.ac.jp:00012158", "sets": ["314"]}, "author_link": ["38560", "38561", "38562", "38563", "38564", "38565", "38566", "38567"], "item_10_alternative_title_19": {"attribute_name": "その他のタイトル", "attribute_value_mlt": [{"subitem_alternative_title": "A Multimodal Constellation Model for Generic Object Recognition", "subitem_alternative_title_language": "en"}]}, "item_10_biblio_info_6": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2009-08-01", "bibliographicIssueDateType": "Issued"}, "bibliographicIssueNumber": "8", "bibliographicPageEnd": "1114", "bibliographicPageStart": "1104", "bibliographicVolumeNumber": "J92-D", "bibliographic_titles": [{"bibliographic_title": "電子情報通信学会論文誌", "bibliographic_titleLang": "ja"}]}]}, "item_10_description_4": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "画像の撮影条件や対象とする物体の種類を制限せずに物体の属するカテゴリーを認識する一般物体認識は,現在注目されている物体認識の研究分野の一つである.この分野で現在主流になりつつある手法としてBag of Features(BoF)を用いた手法と,星座モデルがある.星座モデルにはいくつかの利点があるが,欠点として,本質的にユニモーダル(単峰性)なモデルであるため,カテゴリー中の物体が見た目の大きく異なる複数の種類に分かれる場合には記述精度が低くなるということがある.本論文では,この欠点を解決する\"マルチモーダル星座モデル\"を提案する.マルチモーダル化により物体のそれぞれの種類の見た目を個別に記述できるようになり,記述精度が向上する.実験ではユニモーダルなモデル及びBoFを用いた手法に比べ識別性能が高いことを確認した.", "subitem_description_language": "ja", "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/2237/14037"}, {"subitem_identifier_type": "URI", "subitem_identifier_uri": "http://www.ieice.org/jpn/trans_online/index.html"}]}, "item_10_publisher_32": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "電子情報通信学会", "subitem_publisher_language": "ja"}]}, 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