{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00218589","sets":["1164:2735:10865:10962"]},"path":["10962"],"owner":"44499","recid":"218589","title":["A pseudo node based graph convolution network for emotion perception from gait"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-06-20"},"_buckets":{"deposit":"3a6fd591-86cc-4ed4-a9f8-6e699b0715f9"},"_deposit":{"id":"218589","pid":{"type":"depid","value":"218589","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"A pseudo node based graph convolution network for emotion perception from gait","author_link":["568855","568851","568854","568857","568852","568859","568853","568858","568860","568856"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"A pseudo node based graph convolution network for emotion perception from gait"},{"subitem_title":"A pseudo node based graph convolution network for emotion perception from gait","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2022-06-20","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Ritsumeikan University"},{"subitem_text_value":"Ritsumeikan University"},{"subitem_text_value":"Fujita Health University"},{"subitem_text_value":"Zhejiang university"},{"subitem_text_value":"Ritsumeikan University"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Ritsumeikan University","subitem_text_language":"en"},{"subitem_text_value":"Ritsumeikan University","subitem_text_language":"en"},{"subitem_text_value":"Fujita Health University","subitem_text_language":"en"},{"subitem_text_value":"Zhejiang university","subitem_text_language":"en"},{"subitem_text_value":"Ritsumeikan University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"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/218589/files/IPSJ-MPS22138019.pdf","label":"IPSJ-MPS22138019.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MPS22138019.pdf","filesize":[{"value":"2.0 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"17"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"4b497106-e91f-43ec-98ad-5e56d681f9a7","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Institute of Electronics, Information and Communication Engineers This SIG report is only available to those in membership of the SIG."}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Shurong, Chai"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Jiaqing, Liu"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Tomoko, Tateyama"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Lanfen, Lin"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yen-Wei, Chen"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Shurong, Chai","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Jiaqing, Liu","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Tomoko, Tateyama","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Lanfen, Lin","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Yen-Wei, Chen","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN10505667","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":"2188-8833","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"Recently, emotion recognition task has attracted extensive attention in the field of human-computer interaction. With the advancement of Graph Convolutional Networks (GCNs), human gait can be effectively recognized in more complex backgrounds. According to the anatomy of the human body, central torso joints play a key role in GCNs-based human gait recognition systems, instead of the body’s marginal limb joints. As a result, there is a major issue of receptive field imbalance. In this study, we propose a method for perceiving emotions based on the human gait skeleton. We present a novel pseudo node strategy that connects all natural human body joints to alleviate the receptive field imbalance problem. The result of the experiment show that our proposed method outperforms than existing skeleton-based methods.","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Recently, emotion recognition task has attracted extensive attention in the field of human-computer interaction. With the advancement of Graph Convolutional Networks (GCNs), human gait can be effectively recognized in more complex backgrounds. According to the anatomy of the human body, central torso joints play a key role in GCNs-based human gait recognition systems, instead of the body’s marginal limb joints. As a result, there is a major issue of receptive field imbalance. In this study, we propose a method for perceiving emotions based on the human gait skeleton. We present a novel pseudo node strategy that connects all natural human body joints to alleviate the receptive field imbalance problem. The result of the experiment show that our proposed method outperforms than existing skeleton-based methods.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"3","bibliographic_titles":[{"bibliographic_title":"研究報告数理モデル化と問題解決（MPS）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2022-06-20","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"19","bibliographicVolumeNumber":"2022-MPS-138"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":218589,"updated":"2025-01-19T15:07:01.658107+00:00","links":{},"created":"2025-01-19T01:18:56.698511+00:00"}