{"created":"2023-05-15T09:58:48.436533+00:00","id":2831,"links":{},"metadata":{"_buckets":{"deposit":"1ffc4f1c-8d6d-4a6e-8e9d-5b6737371749"},"_deposit":{"created_by":5,"id":"2831","owner":"5","owners":[5],"pid":{"revision_id":0,"type":"depid","value":"2831"},"status":"published"},"_oai":{"id":"oai:miyazaki-u.repo.nii.ac.jp:00002831","sets":["73","73:36","73:36:330","73:36:330:320"]},"author_link":["14931","14929","6617"],"item_10002_alternative_title_1":{"attribute_name":"その他（別言語等）のタイトル","attribute_value_mlt":[{"subitem_alternative_title":"カイリョウガタ MSEPF ニヨル ガゾウ カラ ノ ブッタイ ツイセキ","subitem_alternative_title_language":"ja-Kana"}]},"item_10002_biblio_info_7":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2010-09-30","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"300","bibliographicPageStart":"293","bibliographicVolumeNumber":"39","bibliographic_titles":[{"bibliographic_title":"宮崎大学工学部紀要","bibliographic_titleLang":"ja"},{"bibliographic_title":"Memoirs of Faculty of Engineering, University of Miyazaki","bibliographic_titleLang":"en"}]}]},"item_10002_description_5":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Recently, many approaches on applying particle filter to visual tracking problem have been proposed. However, it is hard to implement it to the real-time system because it requires a lot of computational and resources in order to achieve higher accuracy. As a method for reduce the computation time, Shan and coworkers proposed combining particle filter and Mean-Shift in order to keep the accuracy with small number of particles. In their approach, the state of each particle moves to the point in the window with the highest likelihood value. It is known that the accuracy of estimation depends on the size of the window, but the larger window size make the computation slower. In this paper, the authors propose a method for exploring the highest likelihood more quickly by means of random sampling. Moreover the authors propose multiple prediction models and new likelihood function that defines likelihood in terms of not only color cue but also motion cue.\nThe effectiveness of the proposed method is evaluated by real image sequence experiments.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_10002_publisher_8":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"宮崎大学工学部","subitem_publisher_language":"ja"},{"subitem_publisher":"Faculty of Engineering, University of Miyazaki","subitem_publisher_language":"en"}]},"item_10002_source_id_11":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA00732558","subitem_source_identifier_type":"NCID"}]},"item_10002_source_id_9":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"05404924","subitem_source_identifier_type":"ISSN"}]},"item_10002_version_type_20":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorAffiliations":[{"affiliationNameIdentifiers":[{"affiliationNameIdentifier":"0000000106573887","affiliationNameIdentifierScheme":"ISNI","affiliationNameIdentifierURI":"https://isni.org/isni/0000000106573887"}],"affiliationNames":[{"affiliationName":"宮崎大学","affiliationNameLang":"ja"},{"affiliationName":"University of Miyazaki","affiliationNameLang":"en"}]}],"creatorNames":[{"creatorName":"横道, 政裕","creatorNameLang":"ja"},{"creatorName":"ヨコミチ, マサヒロ","creatorNameLang":"ja-Kana"},{"creatorName":"Yokomichi, Masahiro","creatorNameLang":"en"}],"familyNames":[{"familyName":"横道","familyNameLang":"ja"},{"familyName":"ヨコミチ","familyNameLang":"ja-Kana"},{"familyName":"Yokomichi","familyNameLang":"en"}],"givenNames":[{"givenName":"政裕","givenNameLang":"ja"},{"givenName":"マサヒロ","givenNameLang":"ja-Kana"},{"givenName":"Masahiro","givenNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"6617","nameIdentifierScheme":"WEKO"},{"nameIdentifier":"30274773","nameIdentifierScheme":"e-Rad_Researcher","nameIdentifierURI":"https://kaken.nii.ac.jp/ja/search/?qm=30274773"}]},{"creatorNames":[{"creatorName":"中釜, 裕希"},{"creatorName":"ナカガマ, ユウキ","creatorNameLang":"ja-Kana"}],"nameIdentifiers":[{"nameIdentifier":"14929","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"Nakagama, Yuki","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"14931","nameIdentifierScheme":"WEKO"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2020-06-21"}],"displaytype":"detail","filename":"engineering39-44.pdf","filesize":[{"value":"1.4 MB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"engineering39-44.pdf","url":"https://miyazaki-u.repo.nii.ac.jp/record/2831/files/engineering39-44.pdf"},"version_id":"90b7720f-9824-4fbc-9fed-f3a5efe97e1e"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Particle filter, Real-time visual tracking, MSEPF","subitem_subject_language":"en","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"departmental bulletin paper","resourceuri":"http://purl.org/coar/resource_type/c_6501"}]},"item_title":"改良型MSEPFによる画像からの物体追跡","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"改良型MSEPFによる画像からの物体追跡","subitem_title_language":"ja"},{"subitem_title":"Visual Tracking by Modified MSEPF","subitem_title_language":"en"}]},"item_type_id":"10002","owner":"5","path":["73","36","330","320"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2011-02-25"},"publish_date":"2011-02-25","publish_status":"0","recid":"2831","relation_version_is_last":true,"title":["改良型MSEPFによる画像からの物体追跡"],"weko_creator_id":"5","weko_shared_id":2},"updated":"2024-12-26T07:19:43.816402+00:00"}