{"id":"https://openalex.org/W2342649219","doi":"https://doi.org/10.1109/taffc.2015.2496320","title":"Partial Matching of Facial Expression Sequence Using Over-Complete Transition Dictionary for Emotion Recognition","display_name":"Partial Matching of Facial Expression Sequence Using Over-Complete Transition Dictionary for Emotion Recognition","publication_year":2015,"publication_date":"2015-10-30","ids":{"openalex":"https://openalex.org/W2342649219","doi":"https://doi.org/10.1109/taffc.2015.2496320","mag":"2342649219"},"language":"en","primary_location":{"id":"doi:10.1109/taffc.2015.2496320","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2015.2496320","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/A5112874884","display_name":"Seung Ho Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Seung Ho Lee","raw_affiliation_strings":["Department of Electrical Engineering, KAIST, Deajeon, Daejeon, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, KAIST, Deajeon, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038798134","display_name":"Yong Man Ro","orcid":"https://orcid.org/0000-0001-5306-6853"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yong Man Ro","raw_affiliation_strings":["Department of Electrical Engineering, KAIST, Deajeon, Daejeon, Republic of Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, KAIST, Deajeon, Daejeon, Republic of Korea","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I157485424"],"apc_list":null,"apc_paid":null,"fwci":1.4694,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.88528582,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"7","issue":"4","first_page":"389","last_page":"408"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9987999796867371,"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":0.9987999796867371,"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":0.9987000226974487,"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/T10901","display_name":"Advanced Data Compression Techniques","score":0.9767000079154968,"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/transition","display_name":"Transition (genetics)","score":0.7597368955612183},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.6935416460037231},{"id":"https://openalex.org/keywords/expression","display_name":"Expression (computer science)","score":0.5816277861595154},{"id":"https://openalex.org/keywords/offset","display_name":"Offset (computer science)","score":0.5319842100143433},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5285761952400208},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5263869762420654},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5164316296577454},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.515428900718689},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5084494352340698},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.4437969923019409},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3494839668273926},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.29621565341949463},{"id":"https://openalex.org/keywords/gene","display_name":"Gene","score":0.14683008193969727},{"id":"https://openalex.org/keywords/biology","display_name":"Biology","score":0.11091303825378418},{"id":"https://openalex.org/keywords/genetics","display_name":"Genetics","score":0.10245475172996521}],"concepts":[{"id":"https://openalex.org/C194232998","wikidata":"https://www.wikidata.org/wiki/Q1606712","display_name":"Transition (genetics)","level":3,"score":0.7597368955612183},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.6935416460037231},{"id":"https://openalex.org/C90559484","wikidata":"https://www.wikidata.org/wiki/Q778379","display_name":"Expression (computer science)","level":2,"score":0.5816277861595154},{"id":"https://openalex.org/C175291020","wikidata":"https://www.wikidata.org/wiki/Q1156822","display_name":"Offset (computer science)","level":2,"score":0.5319842100143433},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5285761952400208},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5263869762420654},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5164316296577454},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.515428900718689},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5084494352340698},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.4437969923019409},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3494839668273926},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.29621565341949463},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.14683008193969727},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.11091303825378418},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.10245475172996521},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"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/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/taffc.2015.2496320","is_oa":false,"landing_page_url":"https://doi.org/10.1109/taffc.2015.2496320","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"},{"id":"pmh:oai:koasas.kaist.ac.kr:10203/219660","is_oa":false,"landing_page_url":"http://hdl.handle.net/10203/219660","pdf_url":null,"source":{"id":"https://openalex.org/S4306402435","display_name":"KAIST Institutional Repository (KAIST)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I157485424","host_organization_name":"Korea Advanced Institute of Science and Technology","host_organization_lineage":["https://openalex.org/I157485424"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.4399999976158142}],"awards":[{"id":"https://openalex.org/G2674080322","display_name":null,"funder_award_id":"B0101-15-0525","funder_id":"https://openalex.org/F4320322030","funder_display_name":"Ministry of Science, ICT and Future Planning"}],"funders":[{"id":"https://openalex.org/F4320322030","display_name":"Ministry of Science, ICT and Future Planning","ror":"https://ror.org/032e49973"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":68,"referenced_works":["https://openalex.org/W1483662103","https://openalex.org/W1574901103","https://openalex.org/W1964762821","https://openalex.org/W1968600824","https://openalex.org/W1978940926","https://openalex.org/W1981918162","https://openalex.org/W1984354005","https://openalex.org/W1986896819","https://openalex.org/W1987231241","https://openalex.org/W1990207480","https://openalex.org/W1990319151","https://openalex.org/W1997425135","https://openalex.org/W2004197686","https://openalex.org/W2012362967","https://openalex.org/W2016163491","https://openalex.org/W2016859189","https://openalex.org/W2021312903","https://openalex.org/W2031802401","https://openalex.org/W2031877935","https://openalex.org/W2035835595","https://openalex.org/W2036250785","https://openalex.org/W2051297709","https://openalex.org/W2053432263","https://openalex.org/W2073609604","https://openalex.org/W2075688085","https://openalex.org/W2077958330","https://openalex.org/W2079712593","https://openalex.org/W2098012923","https://openalex.org/W2101965618","https://openalex.org/W2102544846","https://openalex.org/W2103943262","https://openalex.org/W2106947945","https://openalex.org/W2109002458","https://openalex.org/W2110885456","https://openalex.org/W2115136130","https://openalex.org/W2121684305","https://openalex.org/W2124134481","https://openalex.org/W2125244676","https://openalex.org/W2125399223","https://openalex.org/W2129812935","https://openalex.org/W2133180260","https://openalex.org/W2133820140","https://openalex.org/W2134860945","https://openalex.org/W2138451337","https://openalex.org/W2139916508","https://openalex.org/W2143245774","https://openalex.org/W2143829622","https://openalex.org/W2143899944","https://openalex.org/W2146780613","https://openalex.org/W2154332973","https://openalex.org/W2156503193","https://openalex.org/W2160547390","https://openalex.org/W2161634108","https://openalex.org/W2163808566","https://openalex.org/W2164575144","https://openalex.org/W2173219554","https://openalex.org/W2227797235","https://openalex.org/W2277343944","https://openalex.org/W2532594835","https://openalex.org/W2964199319","https://openalex.org/W2995034616","https://openalex.org/W4205687621","https://openalex.org/W4210993929","https://openalex.org/W4285719527","https://openalex.org/W6663087530","https://openalex.org/W6678770911","https://openalex.org/W6680968271","https://openalex.org/W6694811946"],"related_works":["https://openalex.org/W1972035260","https://openalex.org/W2392243736","https://openalex.org/W86652014","https://openalex.org/W4388308858","https://openalex.org/W2017572878","https://openalex.org/W3022853057","https://openalex.org/W2377728464","https://openalex.org/W2046645015","https://openalex.org/W2328518092","https://openalex.org/W2642127892"],"abstract_inverted_index":{"Facial":[0],"dynamics":[1,12],"contain":[2],"useful":[3],"information":[4],"for":[5],"facial":[6,168],"expression":[7,25,80,96,110,119,132,142,163],"recognition":[8],"(FER).":[9],"However,":[10],"exploiting":[11],"in":[13,41,134,144,194],"FER":[14],"is":[15,18,121,165,184],"challenging.":[16],"This":[17,64,124],"mainly":[19],"due":[20],"to":[21,32,74,157,186],"a":[22,33,67,106,113,130,151,172],"variety":[23],"of":[24,79,108,128,174,188],"transitions.":[26],"For":[27],"example,":[28],"video":[29,58,115,137],"sequences":[30,59],"belonging":[31],"same":[34],"emotion":[35],"class":[36],"may":[37],"have":[38],"different":[39],"characteristics":[40],"transition":[42,45,90,120,133,147,164,189,192],"duration":[43,190],"and/or":[44],"type":[46,193],"(e.g.,":[47],"onset":[48],"versus":[49],"offset).":[50],"The":[51],"temporal":[52,77,159],"mismatches":[53],"between":[54,171],"query":[55,114,136],"and":[56,155,191],"training":[57,84],"could":[60],"degrade":[61],"the":[62,76,83,101,126,135,140,145,158,181],"FER.":[63],"paper":[65],"proposes":[66],"new":[68],"partial":[69,95,109,118,131,141,152,162],"matching":[70,129,153],"framework":[71],"that":[72,180],"aims":[73],"overcome":[75],"mismatch":[78],"transition.":[81],"During":[82,100],"stage,":[85,103],"we":[86,104],"construct":[87],"an":[88],"over-complete":[89,146],"dictionary":[91],"where":[92],"many":[93],"possible":[94],"transitions":[97,111,143],"are":[98],"contained.":[99],"test":[102],"extract":[105],"number":[107],"from":[112],"sequence.":[116],"Each":[117],"analyzed":[122],"individually.":[123],"increases":[125],"possibility":[127],"sequence":[138],"against":[139],"dictionary.":[148],"To":[149],"make":[150],"subject-independent":[154,195],"robust":[156,185],"mismatch,":[160],"each":[161],"defined":[166],"as":[167],"shape":[169],"displacement":[170],"pair":[173],"face":[175],"clusters.":[176],"Experimental":[177],"results":[178],"show":[179],"proposed":[182],"method":[183],"variations":[187],"recognition.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}