{"id":"https://openalex.org/W2885963772","doi":"https://doi.org/10.1109/tip.2018.2856373","title":"Spontaneous Expression Recognition Using Universal Attribute Model","display_name":"Spontaneous Expression Recognition Using Universal Attribute Model","publication_year":2018,"publication_date":"2018-07-16","ids":{"openalex":"https://openalex.org/W2885963772","doi":"https://doi.org/10.1109/tip.2018.2856373","mag":"2885963772","pmid":"https://pubmed.ncbi.nlm.nih.gov/30010578"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2018.2856373","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2018.2856373","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5026751171","display_name":"Nazil Perveen","orcid":"https://orcid.org/0000-0001-8522-7068"},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Nazil Perveen","raw_affiliation_strings":["Visual Learning and Intelligence Group, IIT Hyderabad, Hyderabad, India"],"affiliations":[{"raw_affiliation_string":"Visual Learning and Intelligence Group, IIT Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I65181880"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060306211","display_name":"Debaditya Roy","orcid":"https://orcid.org/0000-0002-8779-1241"},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Debaditya Roy","raw_affiliation_strings":["Visual Learning and Intelligence Group, IIT Hyderabad, Hyderabad, India"],"affiliations":[{"raw_affiliation_string":"Visual Learning and Intelligence Group, IIT Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I65181880"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012566120","display_name":"C. Krishna Mohan","orcid":"https://orcid.org/0000-0002-7316-0836"},"institutions":[{"id":"https://openalex.org/I65181880","display_name":"Indian Institute of Technology Hyderabad","ror":"https://ror.org/01j4v3x97","country_code":"IN","type":"education","lineage":["https://openalex.org/I65181880"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Chalavadi Krishna Mohan","raw_affiliation_strings":["Visual Learning and Intelligence Group, IIT Hyderabad, Hyderabad, India"],"affiliations":[{"raw_affiliation_string":"Visual Learning and Intelligence Group, IIT Hyderabad, Hyderabad, India","institution_ids":["https://openalex.org/I65181880"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5026751171"],"corresponding_institution_ids":["https://openalex.org/I65181880"],"apc_list":null,"apc_paid":null,"fwci":1.4624,"has_fulltext":false,"cited_by_count":82,"citation_normalized_percentile":{"value":0.8688315,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"27","issue":"11","first_page":"5575","last_page":"5584"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9988999962806702,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9988999962806702,"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":0.9980000257492065,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.994700014591217,"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/expression","display_name":"Expression (computer science)","score":0.8069099187850952},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7160619497299194},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.652409017086029},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6427850723266602},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6231916546821594},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5697036981582642},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5333853363990784},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.520982563495636},{"id":"https://openalex.org/keywords/facial-expression-recognition","display_name":"Facial expression recognition","score":0.4171631932258606},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.15763184428215027}],"concepts":[{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.8069099187850952},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7160619497299194},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.652409017086029},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6427850723266602},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6231916546821594},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5697036981582642},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5333853363990784},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.520982563495636},{"id":"https://openalex.org/C2987714656","wikidata":"https://www.wikidata.org/wiki/Q1185804","display_name":"Facial expression recognition","level":4,"score":0.4171631932258606},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.15763184428215027},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2018.2856373","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2018.2856373","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"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 Image Processing","raw_type":"journal-article"},{"id":"pmid:30010578","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/30010578","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.75,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":67,"referenced_works":["https://openalex.org/W170472577","https://openalex.org/W914561379","https://openalex.org/W1486156117","https://openalex.org/W1522734439","https://openalex.org/W1589137271","https://openalex.org/W1609907549","https://openalex.org/W1776647345","https://openalex.org/W1981918162","https://openalex.org/W1993868489","https://openalex.org/W2003686830","https://openalex.org/W2005733474","https://openalex.org/W2008933718","https://openalex.org/W2023486316","https://openalex.org/W2024868105","https://openalex.org/W2028016407","https://openalex.org/W2035343574","https://openalex.org/W2051297709","https://openalex.org/W2065379720","https://openalex.org/W2071680276","https://openalex.org/W2073395356","https://openalex.org/W2073534683","https://openalex.org/W2081835714","https://openalex.org/W2085283108","https://openalex.org/W2092946680","https://openalex.org/W2101866605","https://openalex.org/W2103943262","https://openalex.org/W2105101328","https://openalex.org/W2108333036","https://openalex.org/W2117645142","https://openalex.org/W2121415728","https://openalex.org/W2121627225","https://openalex.org/W2121812409","https://openalex.org/W2128955009","https://openalex.org/W2132555391","https://openalex.org/W2134860945","https://openalex.org/W2137306662","https://openalex.org/W2139916508","https://openalex.org/W2142194269","https://openalex.org/W2150769028","https://openalex.org/W2152725477","https://openalex.org/W2156503193","https://openalex.org/W2158198839","https://openalex.org/W2159668072","https://openalex.org/W2165283290","https://openalex.org/W2169798735","https://openalex.org/W2173219554","https://openalex.org/W2197748410","https://openalex.org/W2205937646","https://openalex.org/W2245421092","https://openalex.org/W2247869531","https://openalex.org/W2293804193","https://openalex.org/W2296223520","https://openalex.org/W2345305417","https://openalex.org/W2396445702","https://openalex.org/W2526853616","https://openalex.org/W2542323081","https://openalex.org/W2584131488","https://openalex.org/W2588300744","https://openalex.org/W2612508648","https://openalex.org/W2767488767","https://openalex.org/W2783866469","https://openalex.org/W2952633803","https://openalex.org/W4290443075","https://openalex.org/W6670991099","https://openalex.org/W6673980726","https://openalex.org/W6680591342","https://openalex.org/W6696798686"],"related_works":["https://openalex.org/W2642127892","https://openalex.org/W4205986151","https://openalex.org/W2355913164","https://openalex.org/W1153638794","https://openalex.org/W2168968280","https://openalex.org/W2116055069","https://openalex.org/W2162992774","https://openalex.org/W2952602176","https://openalex.org/W4323520705","https://openalex.org/W2356663679"],"abstract_inverted_index":{"Spontaneous":[0],"expression":[1,17,42,53,120,144,174,186,222],"recognition":[2,18,43],"refers":[3],"to":[4,32,70,89,153,217],"recognizing":[5],"non-posed":[6],"human":[7],"expressions.":[8,183],"In":[9],"literature,":[10],"most":[11],"of":[12,51,74,82,114,141,176],"the":[13,49,72,80,101,115,128,139,146],"existing":[14],"approaches":[15],"for":[16,40,48,118,172],"mainly":[19],"rely":[20],"on":[21,209],"manual":[22],"annotations":[23],"by":[24,107],"experts,":[25],"which":[26],"is":[27,68,105,148],"both":[28],"time-consuming":[29],"and":[30,166,190],"difficult":[31],"obtain.":[33],"Hence,":[34],"we":[35,192,203],"propose":[36],"an":[37],"unsupervised":[38],"framework":[39],"spontaneous":[41,182,185],"that":[44,86,142,169,194,206],"preserves":[45],"discriminative":[46],"information":[47],"videos":[50],"each":[52,119,173],"without":[54],"using":[55,108,150],"annotations.":[56],"Initially,":[57],"a":[58,91,96,109,111,132,155,210],"large":[59],"Gaussian":[60],"mixture":[61],"model":[62,66],"called":[63,100],"universal":[64],"attribute":[65],"(UAM)":[67],"trained":[69,208],"learn":[71],"attributes":[73,125,140],"various":[75,83],"expressions":[76,129,219],"implicitly.":[77],"Attributes":[78],"are":[79,87,170],"movements":[81],"facial":[84,93],"muscles":[85],"combined":[88],"form":[90],"particular":[92,143],"expression.":[94],"Then":[95],"concatenated":[97],"mean":[98],"vector":[99],"super":[102],"expression-vector":[103,195],"(SEV)":[104],"formed":[106],"maximum":[110],"posteriori":[112],"adaptation":[113],"UAM":[116,207],"means":[117],"clip.":[121],"This":[122,158],"SEV":[123,147],"contains":[124],"from":[126],"all":[127],"resulting":[130],"in":[131,181,220],"high":[133,177],"dimensional":[134],"representation.":[135],"To":[136],"retain":[137],"only":[138],"clip,":[145],"decomposed":[149],"factor":[151],"analysis":[152],"produce":[154],"low-dimensional":[156],"expression-vector.":[157],"procedure":[159],"does":[160],"not":[161],"require":[162],"any":[163],"class":[164],"labels":[165],"produces":[167],"expression-vectors":[168],"distinct":[171],"irrespective":[175],"inter-actor":[178],"variability":[179],"present":[180],"On":[184],"datasets":[187],"like":[188],"BP4D":[189],"AFEW,":[191],"demonstrate":[193],"achieves":[196],"better":[197],"performance":[198],"than":[199],"state-of-the-art":[200],"techniques.":[201],"Further,":[202],"also":[204],"show":[205],"constrained":[211],"dataset":[212],"can":[213],"be":[214],"effectively":[215],"used":[216],"recognize":[218],"unconstrained":[221],"videos.":[223]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":29},{"year":2023,"cited_by_count":18},{"year":2022,"cited_by_count":19},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}