{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00185493","sets":["1164:4619:9352:9359"]},"path":["9359"],"owner":"11","recid":"185493","title":["ポイントクラウドを入力とした物体認識と形状補完ネットワークの提案"],"pubdate":{"attribute_name":"公開日","attribute_value":"2018-01-11"},"_buckets":{"deposit":"399f25ee-e1a1-415e-b2b4-5d97637e371b"},"_deposit":{"id":"185493","pid":{"type":"depid","value":"185493","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"ポイントクラウドを入力とした物体認識と形状補完ネットワークの提案","author_link":["412603","412606","412605","412604"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ポイントクラウドを入力とした物体認識と形状補完ネットワークの提案"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"ポスタースポットライト","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2018-01-11","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"青山学院大学／日本電信電話株式会社NTTコミュニケーション科学基礎研究所"},{"subitem_text_value":"青山学院大学"},{"subitem_text_value":"日本電信電話株式会社NTTコミュニケーション科学基礎研究所"},{"subitem_text_value":"日本電信電話株式会社NTTコミュニケーション科学基礎研究所"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Aoyama Gakuin University / NTT Communication Science Laboratories, NTT Corporation","subitem_text_language":"en"},{"subitem_text_value":"Aoyama Gakuin University","subitem_text_language":"en"},{"subitem_text_value":"NTT Communication Science Laboratories, NTT Corporation","subitem_text_language":"en"},{"subitem_text_value":"NTT Communication Science Laboratories, NTT Corporation","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/185493/files/IPSJ-CVIM18210054.pdf","label":"IPSJ-CVIM18210054.pdf"},"date":[{"dateType":"Available","dateValue":"2020-01-11"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CVIM18210054.pdf","filesize":[{"value":"968.8 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":"562d7653-f8d4-4c2a-aafb-47ebf06a7d04","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2018 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"伊東, 聖矢"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"鷲見, 和彦"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"入江, 豪"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"永野, 秀尚"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11131797","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8701","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"本研究では，ポイントクラウドからクラス識別と形状補完を同時に行うニューラルネットワークを提案する．実世界で観測される物体のポイントクラウドは部分的な形状しか得られない場合が多くあり，物体認識と形状補完を行うことは様々なアプリケーションを実現する上で重要である．昨今主流となっている畳み込みネットワークは，その性質上，3 次元データを扱うために入力をボクセルやデプス画像に変換する必要がある．しかし，これらは元の 3 次元情報を離散化したり，2 次元に写像するため，情報欠落が生じるという問題がある．そこで本研究では，ポイントクラウドから大域的特徴と局所的特徴を抽出し，大域的特徴からクラス識別を行うとともに，その大域的特徴と局所的特徴から形状補完を行う．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"4","bibliographic_titles":[{"bibliographic_title":"研究報告コンピュータビジョンとイメージメディア（CVIM）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2018-01-11","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"54","bibliographicVolumeNumber":"2018-CVIM-210"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"updated":"2025-01-20T02:58:17.547993+00:00","created":"2025-01-19T00:52:35.767786+00:00","links":{},"id":185493}