{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00240301","sets":["6164:6165:6640:11802"]},"path":["11802"],"owner":"44499","recid":"240301","title":["文脈に基づくネットワークカメラ映像の変化点抽出および説明手法の提案"],"pubdate":{"attribute_name":"公開日","attribute_value":"2024-06-19"},"_buckets":{"deposit":"48c85d39-794c-481b-913c-381500e7b37a"},"_deposit":{"id":"240301","pid":{"type":"depid","value":"240301","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"文脈に基づくネットワークカメラ映像の変化点抽出および説明手法の提案","author_link":["659005","659007","659010","659006","659009","659008"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"文脈に基づくネットワークカメラ映像の変化点抽出および説明手法の提案"},{"subitem_title":"Change Point Extraction and Explanation Method for Network Camera Footage Based on Context","subitem_title_language":"en"}]},"item_type_id":"18","publish_date":"2024-06-19","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_18_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"株式会社NTTドコモ／慶應義塾大学"},{"subitem_text_value":"株式会社NTTドコモ"},{"subitem_text_value":"株式会社NTTドコモ"},{"subitem_text_value":"株式会社NTTドコモ"},{"subitem_text_value":"株式会社NTTドコモ"},{"subitem_text_value":"慶應義塾大学"}]},"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/240301/files/IPSJ-DICOMO2024177.pdf","label":"IPSJ-DICOMO2024177.pdf"},"date":[{"dateType":"Available","dateValue":"2026-06-19"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DICOMO2024177.pdf","filesize":[{"value":"2.6 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"e62e8001-b11f-4510-812a-968106ff959a","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2024 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"北出, 卓也"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"山谷, 佳祐"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"春山, 知生"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"中村, 匠"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"安川, 真平"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"今井, 倫太"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_18_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"ネットワークカメラの普及により，遠隔地の映像をリアルタイムに確認可能となっている．特に自動運転車両における遠隔監視は一人のオペレータが複数映像を監視することで省人化が可能となるため，映像監視自動化システムの重要性が増しており，システムとしてはオペレータが特に確認すべきシーンを抽出し，オペレータが短時間に理解可能な情報として提示できることが求められている．これまでもネットワークカメラ映像に映る人物の行動を分析する手法が研究されてきたが，それぞれの行動に対して認識モデルの開発が必要であった．そこで本研究では「人の動きがある」シーンのみを抽出しVLMで汎用的に分析し，その結果を使用してシーンを短文で説明する手法を提案する．VLMを説明した文章の文脈変化が大きな部位がシーンの大きな変化となり得るという考え方で，オペレータが確認すべきシーンを絞り込む．この手法により，自動運転バスを想定した映像から重要なシーンを抽出し，文章での説明ができること，そして実用上の課題を確認した．","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"1310","bibliographic_titles":[{"bibliographic_title":"マルチメディア，分散，協調とモバイルシンポジウム2024論文集"}],"bibliographicPageStart":"1304","bibliographicIssueDates":{"bibliographicIssueDate":"2024-06-19","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2024"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":240301,"updated":"2025-01-19T08:01:19.406644+00:00","links":{},"created":"2025-01-19T01:44:24.914831+00:00"}