{"created":"2021-03-01T06:29:24.312093+00:00","id":21710,"links":{},"metadata":{"_buckets":{"deposit":"c403eb2e-595a-4aad-92c4-05156ad3c600"},"_deposit":{"id":"21710","owners":[],"pid":{"revision_id":0,"type":"depid","value":"21710"},"status":"published"},"_oai":{"id":"oai:nagoya.repo.nii.ac.jp:00021710","sets":["312:313:314"]},"author_link":["64427","64428","64429","64430","64431","64432","64433","64434","64435","64436"],"item_10_alternative_title_19":{"attribute_name":"その他のタイトル","attribute_value_mlt":[{"subitem_alternative_title":"A Study on Spatio-Temporal CoHOG Features for Recognition of Generic Objects in Video","subitem_alternative_title_language":"en"}]},"item_10_biblio_info_6":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2011-12-18","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"353","bibliographicPageEnd":"6","bibliographicPageStart":"1","bibliographicVolumeNumber":"111","bibliographic_titles":[{"bibliographic_title":"電子情報通信学会技術研究報告. PRMU, パターン認識・メディア理解","bibliographic_titleLang":"ja"}]}]},"item_10_description_4":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Web上の大量の動画像を効率よく検索するための重要な要素技術の一つとして,動画像に映っている物体を認識する技術が挙げられる.従来,静止画像を対象とした一般物体認識は盛んに研究が行われてきたが,動画像を対象とした一般物体認識の研究はほとんど行われていない.動画像を対象とした一般物体認識では,動画像中の様々なフレームから得られる形状特徴と動き特徴の双方を効果的に利用することが重要となる.本報告では,歩行者検出などで高い性能を持つCoHOG (Co-occurrence Histograms of Oriented Gradients)を時間方向に拡張した時空間CoHOG特徴を提案する.時空間CoHOG特徴は,動画像中の局所領域での時空間勾配方向の共起ヒストグラムである.認識には,BoF (Bag of Features)表現とカーネルSVMを用いる.実験では,Web上から収集した10カテゴリ,計1,000本の動画像を用い,オプティカルフロー特徴およびSIFT特徴と比較することにより,時空間CoHOG特徴の有効性を確認した.","subitem_description_language":"ja","subitem_description_type":"Abstract"},{"subitem_description":"Recognizing objects in videos is one of the important technologies to search a large amount of videos efficiently on the Web. Recently, generic object recognition has been actively studied for still images, but almost not for videos. As for the generic object recognition in a video, it is important to use both the shape features and the motion features obtained from multiple frames in the video efficiently. In this paper, we propose spatio-temporal CoHOG (Co-occurrence Histograms of Oriented Gradients) features. This is an extension of CoHOG features that provide a high performance for pedestrian detection and others. The spatio-temporal CoHOG features are co-occurrence histograms of oriented spatio-temporal gradients in local regions in a video. In the recognition, a BoF (Bag of Features) representation and a kernel SVM are employed. We conducted an experiment on 1,000 videos including 10 categories collected from the Web. The experimental results showed the effectiveness of the spatio-temporal CoHOG features compared with conventional optical flow features and SIFT features.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_10_description_5":{"attribute_name":"内容記述","attribute_value_mlt":[{"subitem_description":"IEICE Technical Report;PRMU2011-124","subitem_description_language":"en","subitem_description_type":"Other"}]},"item_10_identifier_60":{"attribute_name":"URI","attribute_value_mlt":[{"subitem_identifier_type":"URI","subitem_identifier_uri":"http://ci.nii.ac.jp/naid/110009467016/"},{"subitem_identifier_type":"HDL","subitem_identifier_uri":"http://hdl.handle.net/2237/23859"}]},"item_10_publisher_32":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"一般社団法人電子情報通信学会","subitem_publisher_language":"ja"}]},"item_10_relation_40":{"attribute_name":"シリーズ","attribute_value_mlt":[{"subitem_relation_name":[{"subitem_relation_name_text":"IEICE Technical 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Shogo","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"64432","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"DEGUCHI, Daisuke","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"64433","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"TAKAHASHI, Tomokazu","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"64434","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"IDE, Ichiro","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"64435","nameIdentifierScheme":"WEKO"}]},{"creatorNames":[{"creatorName":"MURASE, Hiroshi","creatorNameLang":"en"}],"nameIdentifiers":[{"nameIdentifier":"64436","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":"2018-02-21"}],"displaytype":"detail","filename":"110009467016.pdf","filesize":[{"value":"1.3 MB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"110009467016.pdf","objectType":"fulltext","url":"https://nagoya.repo.nii.ac.jp/record/21710/files/110009467016.pdf"},"version_id":"74c23a9b-412e-4386-84e9-b24c876b808f"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"一般物体認識","subitem_subject_scheme":"Other"},{"subitem_subject":"動画像","subitem_subject_scheme":"Other"},{"subitem_subject":"時空間CoHOG特徴","subitem_subject_scheme":"Other"},{"subitem_subject":"BoF表現","subitem_subject_scheme":"Other"},{"subitem_subject":"Generic object recognition","subitem_subject_scheme":"Other"},{"subitem_subject":"Video","subitem_subject_scheme":"Other"},{"subitem_subject":"Spatio-temporal CoHOG features","subitem_subject_scheme":"Other"},{"subitem_subject":"BoF 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