{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00175410","sets":["1164:4619:8450:8934"]},"path":["8934"],"owner":"11","recid":"175410","title":["Mixed Features for Face Detection in Thermal Image"],"pubdate":{"attribute_name":"公開日","attribute_value":"2016-11-02"},"_buckets":{"deposit":"c2d95f72-8155-40db-8636-117e830b846a"},"_deposit":{"id":"175410","pid":{"type":"depid","value":"175410","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"Mixed Features for Face Detection in Thermal Image","author_link":["365415","365418","365417","365423","365416","365424","365421","365422","365420","365414","365419","365425"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Mixed Features for Face Detection in Thermal Image"},{"subitem_title":"Mixed Features for Face Detection in Thermal Image","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2016-11-02","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"Kyushu University"},{"subitem_text_value":"Kyushu University"},{"subitem_text_value":"Kyushu University"},{"subitem_text_value":"Kyushu University"},{"subitem_text_value":"Kyushu University"},{"subitem_text_value":"Kyushu University"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Kyushu University","subitem_text_language":"en"},{"subitem_text_value":"Kyushu University","subitem_text_language":"en"},{"subitem_text_value":"Kyushu University","subitem_text_language":"en"},{"subitem_text_value":"Kyushu University","subitem_text_language":"en"},{"subitem_text_value":"Kyushu University","subitem_text_language":"en"},{"subitem_text_value":"Kyushu 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/175410/files/IPSJ-CVIM16204001.pdf","label":"IPSJ-CVIM16204001.pdf"},"date":[{"dateType":"Available","dateValue":"2018-11-02"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-CVIM16204001.pdf","filesize":[{"value":"1.1 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":"20"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"bbcae2b8-4c68-408a-af9d-097c3270a0d1","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2016 by the Information Processing Society of Japan"}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Chao, Ma"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Ngo, Thanh Trung"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hideaki, Uchiyama"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hajime, Nagahara"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Atsushi, Shimada"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Rin-ichiro, Taniguchi"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Chao, Ma","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Ngo, Thanh Trung","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hideaki, Uchiyama","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hajime, Nagahara","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Atsushi, Shimada","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Rin-ichiro, Taniguchi","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11131797","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":"2188-8701","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"An infrared camera is able to capture temperature distribution as an infrared (IR) image. It is a powerful tool in human related applications, such as human face recognition in complex illumination and fever screening in public places relying on facial temperature. Since facial temperature is almost constant, it is easy to find the facial region on an IR image. However, a simple temperature thresholding is not always working for detecting face stably. It is a standard for face detection to use Adaboost with local features such as Haar-like, MB-LPB, and HoG in visible image. However, there are very few research works using these local features in IR domain. In this paper, we propose an AdaBoost based training method to mix these local features for face detection in IR domain. In experiment, we captured a dataset of 20 people including 14 males and 6 females with variations of 10 different distances, 21 poses, and with/without glasses. We showed the proposed mixed features has an advantage over all of the regular local features using leave-one-out cross-validation.","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"An infrared camera is able to capture temperature distribution as an infrared (IR) image. It is a powerful tool in human related applications, such as human face recognition in complex illumination and fever screening in public places relying on facial temperature. Since facial temperature is almost constant, it is easy to find the facial region on an IR image. However, a simple temperature thresholding is not always working for detecting face stably. It is a standard for face detection to use Adaboost with local features such as Haar-like, MB-LPB, and HoG in visible image. However, there are very few research works using these local features in IR domain. In this paper, we propose an AdaBoost based training method to mix these local features for face detection in IR domain. In experiment, we captured a dataset of 20 people including 14 males and 6 females with variations of 10 different distances, 21 poses, and with/without glasses. We showed the proposed mixed features has an advantage over all of the regular local features using leave-one-out cross-validation.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"5","bibliographic_titles":[{"bibliographic_title":"研究報告コンピュータビジョンとイメージメディア（CVIM）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2016-11-02","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2016-CVIM-204"}]},"relation_version_is_last":true,"weko_creator_id":"11"},"id":175410,"updated":"2025-01-20T06:13:38.017007+00:00","links":{},"created":"2025-01-19T00:45:21.169647+00:00"}