{"id":"https://openalex.org/W2346638707","doi":"https://doi.org/10.1109/taffc.2016.2563432","title":"Cross-Domain Color Facial Expression Recognition Using Transductive Transfer Subspace Learning","display_name":"Cross-Domain Color Facial Expression Recognition Using Transductive Transfer Subspace Learning","publication_year":2016,"publication_date":"2016-05-05","ids":{"openalex":"https://openalex.org/W2346638707","doi":"https://doi.org/10.1109/taffc.2016.2563432","mag":"2346638707"},"language":"en","primary_location":{"id":"doi:10.1109/taffc.2016.2563432","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2016.2563432","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5029771864","display_name":"Wenming Zheng","orcid":"https://orcid.org/0000-0002-7764-5179"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenming Zheng","raw_affiliation_strings":["Key Laboratory of Child Development and Learning Science (Southeast University), Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, Jiangsu, P.R. China"],"raw_orcid":"https://orcid.org/0000-0002-7764-5179","affiliations":[{"raw_affiliation_string":"Key Laboratory of Child Development and Learning Science (Southeast University), Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, Jiangsu, P.R. China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027316177","display_name":"Yuan Zong","orcid":"https://orcid.org/0000-0002-0839-8792"},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Zong","raw_affiliation_strings":["Key Laboratory of Child Development and Learning Science (Southeast University), Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, Jiangsu, P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Child Development and Learning Science (Southeast University), Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, Jiangsu, P.R. China","institution_ids":["https://openalex.org/I76569877"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060425100","display_name":"Xiaoyan Zhou","orcid":"https://orcid.org/0009-0002-3471-0441"},"institutions":[{"id":"https://openalex.org/I200845125","display_name":"Nanjing University of Information Science and Technology","ror":"https://ror.org/02y0rxk19","country_code":"CN","type":"education","lineage":["https://openalex.org/I200845125"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyan Zhou","raw_affiliation_strings":["school of Electronic and Information Engineering, Nanjing University of Information Science and Engineering Technology, Nanjing, Jiangsu, P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"school of Electronic and Information Engineering, Nanjing University of Information Science and Engineering Technology, Nanjing, Jiangsu, P.R. China","institution_ids":["https://openalex.org/I200845125"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061493075","display_name":"Minghai Xin","orcid":null},"institutions":[{"id":"https://openalex.org/I76569877","display_name":"Southeast University","ror":"https://ror.org/04ct4d772","country_code":"CN","type":"education","lineage":["https://openalex.org/I76569877"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minghai Xin","raw_affiliation_strings":["Key Laboratory of Child Development and Learning Science (Southeast University), Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, Jiangsu, P.R. China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Child Development and Learning Science (Southeast University), Ministry of Education, Research Center for Learning Science, Southeast University, Nanjing, Jiangsu, P.R. China","institution_ids":["https://openalex.org/I76569877"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.1235,"has_fulltext":false,"cited_by_count":86,"citation_normalized_percentile":{"value":0.94697171,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"9","issue":"1","first_page":"21","last_page":"37"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9984999895095825,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9857000112533569,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9581000208854675,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8017871975898743},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7064711451530457},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6993281841278076},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.6279721260070801},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.6173524856567383},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5266684889793396},{"id":"https://openalex.org/keywords/face-hallucination","display_name":"Face hallucination","score":0.509982705116272},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.503781259059906},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5012655258178711},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.4594574272632599},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4545650780200958},{"id":"https://openalex.org/keywords/facial-expression-recognition","display_name":"Facial expression recognition","score":0.44760674238204956},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4467346668243408},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.41947492957115173},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.18831899762153625}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8017871975898743},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7064711451530457},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6993281841278076},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.6279721260070801},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.6173524856567383},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5266684889793396},{"id":"https://openalex.org/C54654163","wikidata":"https://www.wikidata.org/wiki/Q5428359","display_name":"Face hallucination","level":5,"score":0.509982705116272},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.503781259059906},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5012655258178711},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.4594574272632599},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4545650780200958},{"id":"https://openalex.org/C2987714656","wikidata":"https://www.wikidata.org/wiki/Q1185804","display_name":"Facial expression recognition","level":4,"score":0.44760674238204956},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4467346668243408},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.41947492957115173},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.18831899762153625},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/taffc.2016.2563432","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2016.2563432","pdf_url":null,"source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.7400000095367432,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G1757533758","display_name":"\u57fa\u4e8e\u5b50\u7a7a\u95f4\u8fc1\u79fb\u5b66\u4e60\u7684\u8de8\u8bed\u79cd\u8bed\u97f3\u60c5\u611f\u8bc6\u522b\u7814\u7a76","funder_award_id":"61572009","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2344363859","display_name":null,"funder_award_id":"BK20130020","funder_id":"https://openalex.org/F4320322769","funder_display_name":"Natural Science Foundation of Jiangsu Province"},{"id":"https://openalex.org/G3875471163","display_name":"\u57fa\u4e8e\u89c6\u9891\u5206\u6790\u7684\u513f\u7ae5\u884c\u4e3a\u7814\u7a76","funder_award_id":"61231002","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G742410658","display_name":null,"funder_award_id":"(2015CB351704)","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322769","display_name":"Natural Science Foundation of Jiangsu Province","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":47,"referenced_works":["https://openalex.org/W1482409772","https://openalex.org/W1483662103","https://openalex.org/W1513525398","https://openalex.org/W1573257727","https://openalex.org/W1983008863","https://openalex.org/W1991385629","https://openalex.org/W1997201895","https://openalex.org/W2003823024","https://openalex.org/W2008635359","https://openalex.org/W2023486316","https://openalex.org/W2033379850","https://openalex.org/W2057069782","https://openalex.org/W2060488580","https://openalex.org/W2075372532","https://openalex.org/W2080117431","https://openalex.org/W2090213288","https://openalex.org/W2096044434","https://openalex.org/W2100560442","https://openalex.org/W2102419107","https://openalex.org/W2102689555","https://openalex.org/W2103851188","https://openalex.org/W2112483442","https://openalex.org/W2115403315","https://openalex.org/W2137306662","https://openalex.org/W2139212933","https://openalex.org/W2139916508","https://openalex.org/W2140797123","https://openalex.org/W2151103935","https://openalex.org/W2153963799","https://openalex.org/W2157285372","https://openalex.org/W2157762168","https://openalex.org/W2162762921","https://openalex.org/W2165698076","https://openalex.org/W2167718886","https://openalex.org/W2293984055","https://openalex.org/W2575396466","https://openalex.org/W2798766386","https://openalex.org/W2912990735","https://openalex.org/W3022547535","https://openalex.org/W3193477162","https://openalex.org/W4210993929","https://openalex.org/W4244633107","https://openalex.org/W6675410418","https://openalex.org/W6675547039","https://openalex.org/W6676840641","https://openalex.org/W6680591342","https://openalex.org/W6680826164"],"related_works":["https://openalex.org/W4205986151","https://openalex.org/W2355913164","https://openalex.org/W2162992774","https://openalex.org/W1153638794","https://openalex.org/W2168968280","https://openalex.org/W2901126000","https://openalex.org/W2116055069","https://openalex.org/W2356663679","https://openalex.org/W2169777806","https://openalex.org/W3186105911"],"abstract_inverted_index":{"Facial":[0],"expression":[1,39,152,187,198],"recognition":[2,40,146,153,199,228],"across":[3],"domains,":[4],"e.g.,":[5],"training":[6,26],"and":[7,27,83,182],"testing":[8,28],"facial":[9,14,29,38,59,71,92,113,127,141,151,167,175,186,197],"images":[10,128],"come":[11],"from":[12,62,74],"different":[13,22],"poses,":[15],"is":[16,49,65,103],"very":[17],"challenging":[18,36],"due":[19],"to":[20,77,105,143,171,191],"the":[21,85,90,111,123,130,137,145,149,193,202,215,222,232],"marginal":[23],"distributions":[24],"between":[25],"feature":[30,159],"vectors.":[31],"To":[32],"deal":[33],"with":[34,67,164,206,231],"such":[35],"cross-domain":[37],"problem,":[41],"a":[42,57,80,95,118],"novel":[43],"transductive":[44,96],"transfer":[45,97],"subspace":[46,82],"learning":[47],"method":[48,224],"proposed":[50,104,150,203,223],"in":[51,129,214],"this":[52,55,106],"paper.":[53],"In":[54],"method,":[56,154],"labelled":[58],"image":[60,72,114],"set":[61,73],"source":[63],"domain":[64,76,208],"combined":[66],"an":[68],"unlabelled":[69,91],"auxiliary":[70,112],"target":[75,131],"jointly":[78],"learn":[79],"discriminative":[81],"make":[84],"class":[86],"labels":[87],"prediction":[88],"of":[89,125,139,148,201],"images,":[93],"where":[94,155],"regularized":[98],"least-squares":[99],"regression":[100],"(TTRLSR)":[101],"model":[102],"end.":[107],"Then,":[108],"based":[109],"on":[110,180],"set,":[115],"we":[116,134],"train":[117],"SVM":[119],"classifier":[120],"for":[121],"classifying":[122],"expressions":[124],"other":[126],"domain.":[132],"Moreover,":[133],"also":[135,212],"investigate":[136],"use":[138],"color":[140,156,174,185],"features":[142,162],"evaluate":[144,192],"performance":[147,200,229],"scale":[157],"invariant":[158],"transform":[160],"(CSIFT)":[161],"associated":[163],"49":[165],"landmark":[166],"points":[168],"are":[169,189,211],"extracted":[170],"describe":[172],"each":[173],"image.":[176],"Finally,":[177],"extensive":[178],"experiments":[179],"BU-3DFE":[181],"Multi-PIE":[183],"multiview":[184],"databases":[188],"conducted":[190],"cross-database":[194],"&":[195],"cross-view":[196],"method.":[204],"Comparisons":[205],"state-of-the-art":[207,233],"adaption":[209],"methods":[210],"included":[213],"experiments.":[216],"The":[217],"experimental":[218],"results":[219],"demonstrate":[220],"that":[221],"achieves":[225],"much":[226],"better":[227],"compared":[230],"methods.":[234]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":15},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":15},{"year":2019,"cited_by_count":12},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":2}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}