{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00215967","sets":["1164:6390:10768:10769"]},"path":["10769"],"owner":"44499","recid":"215967","title":["植物生育記録の自動化に向けたKeypoint検出の検討"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-01-13"},"_buckets":{"deposit":"03bf567c-a507-472c-aee5-6c85f5e9658a"},"_deposit":{"id":"215967","pid":{"type":"depid","value":"215967","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"植物生育記録の自動化に向けたKeypoint検出の検討","author_link":["556745","556747","556749","556744","556743","556746","556748"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"植物生育記録の自動化に向けたKeypoint検出の検討"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"情報技術と社会","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2022-01-13","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"静岡大学情報学部"},{"subitem_text_value":"（株）Plant 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彰"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"峰野, 博史"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12628327","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":"2188-8604","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"栽培と育種の両面において，作物の生育状態を把握するための定期的な生育調査が重要である．定期的な生育調査では，植物の成長速度，植物のストレス状態を定量化することで現在の植物の状態を想像することができる．また，植物の状態を定量化した過去データを参照できるようになれば，現在行うべき農作業の判断に役立ち，より品質の高い作物を栽培に繋がる．しかし，節間の伸長の計測や花数のカウントといった植物の生育調査は，手作業で行うにはとても手間のかかる作業である．近年の農業従事者の高齢化，新規就農者の減少による労働力不足もあり，より重要度の高い収穫・出荷といった農作業に追われ，手間のかかる定期的な生育調査は十分実施できているとは言えない．本研究では，様々な理想的な生育調査の中でも「長さ」を測る項目に着目し，Keypoint 検出を用いて自動的に距離測定を行う技術の確立を目指す．まずはモデル植物として一般的であるトマトの長段ハウス栽培を対象とし，ハウス内の栽培ベッド間を自走する吊り下げ型ロボットで撮影された動画に対し，Keypoint 検出によって茎や枝の節を見つける手法を検証した．Keypoint 検出によって画像中から特徴点を見つけられるため，植物ならではの特徴点の結びつきを定義することで，植物の茎や枝の節間距離の自動推定を実現する．植物に対する茎や枝の節といった Keypoint を定義し基礎評価を実施した結果，植物の画像中から茎や枝の節部分の検出を高精度に実現できる可能性を確認した．今後，植物ならではの Keypoint 検出精度向上に向けた検討を深め，距離推定の検証を進めていく．","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告コンシューマ・デバイス＆システム（CDS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2022-01-13","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"52","bibliographicVolumeNumber":"2022-CDS-33"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":215967,"updated":"2025-01-19T15:58:37.032999+00:00","links":{},"created":"2025-01-19T01:16:42.042738+00:00"}