{"id":"https://openalex.org/W2996033780","doi":"https://doi.org/10.1109/acii.2019.8925445","title":"A Deep Framework for Facial Emotion Recognition using Light Field Images","display_name":"A Deep Framework for Facial Emotion Recognition using Light Field Images","publication_year":2019,"publication_date":"2019-09-01","ids":{"openalex":"https://openalex.org/W2996033780","doi":"https://doi.org/10.1109/acii.2019.8925445","mag":"2996033780"},"language":"en","primary_location":{"id":"doi:10.1109/acii.2019.8925445","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acii.2019.8925445","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII)","raw_type":"proceedings-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/A5088311682","display_name":"Alireza Sepas\u2010Moghaddam","orcid":"https://orcid.org/0000-0002-4881-5386"},"institutions":[{"id":"https://openalex.org/I204722609","display_name":"Queen's University","ror":"https://ror.org/02y72wh86","country_code":"CA","type":"education","lineage":["https://openalex.org/I204722609"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Alireza Sepas-Moghaddam","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Queen's University, Kingston, Ontario, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Queen's University, Kingston, Ontario, Canada","institution_ids":["https://openalex.org/I204722609"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039812985","display_name":"Ali Etemad","orcid":"https://orcid.org/0000-0001-7128-0220"},"institutions":[{"id":"https://openalex.org/I204722609","display_name":"Queen's University","ror":"https://ror.org/02y72wh86","country_code":"CA","type":"education","lineage":["https://openalex.org/I204722609"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ali Etemad","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Queen's University, Kingston, Ontario, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Queen's University, Kingston, Ontario, Canada","institution_ids":["https://openalex.org/I204722609"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019322980","display_name":"Paulo Lobato Correia","orcid":"https://orcid.org/0000-0001-6525-9572"},"institutions":[{"id":"https://openalex.org/I4210120471","display_name":"Instituto de Telecomunica\u00e7\u00f5es","ror":"https://ror.org/02ht4fk33","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I4210120471"]},{"id":"https://openalex.org/I141596103","display_name":"University of Lisbon","ror":"https://ror.org/01c27hj86","country_code":"PT","type":"education","lineage":["https://openalex.org/I141596103"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Paulo Lobato Correia","raw_affiliation_strings":["Instituto de Telecomunicacoes, Instituto Superior Tecnico, Universidade de Lisboa, Lisbon, Portugal"],"affiliations":[{"raw_affiliation_string":"Instituto de Telecomunicacoes, Instituto Superior Tecnico, Universidade de Lisboa, Lisbon, Portugal","institution_ids":["https://openalex.org/I4210120471","https://openalex.org/I141596103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044708805","display_name":"Fernando Pereira","orcid":"https://orcid.org/0000-0001-6100-947X"},"institutions":[{"id":"https://openalex.org/I4210120471","display_name":"Instituto de Telecomunica\u00e7\u00f5es","ror":"https://ror.org/02ht4fk33","country_code":"PT","type":"nonprofit","lineage":["https://openalex.org/I4210120471"]},{"id":"https://openalex.org/I141596103","display_name":"University of Lisbon","ror":"https://ror.org/01c27hj86","country_code":"PT","type":"education","lineage":["https://openalex.org/I141596103"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Fernando Pereira","raw_affiliation_strings":["Instituto de Telecomunicacoes, Instituto Superior Tecnico, Universidade de Lisboa, Lisbon, Portugal"],"affiliations":[{"raw_affiliation_string":"Instituto de Telecomunicacoes, Instituto Superior Tecnico, Universidade de Lisboa, Lisbon, Portugal","institution_ids":["https://openalex.org/I4210120471","https://openalex.org/I141596103"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5088311682"],"corresponding_institution_ids":["https://openalex.org/I204722609"],"apc_list":null,"apc_paid":null,"fwci":1.3159,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.84865426,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"10","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.996399998664856,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.996399998664856,"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/T11666","display_name":"Color Science and Applications","score":0.9914000034332275,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11019","display_name":"Image Enhancement Techniques","score":0.9876000285148621,"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":0.7895714044570923},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7532235383987427},{"id":"https://openalex.org/keywords/softmax-function","display_name":"Softmax function","score":0.7225195169448853},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6729320883750916},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5801144242286682},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5547295808792114},{"id":"https://openalex.org/keywords/light-field","display_name":"Light field","score":0.5309566855430603},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.5102534294128418},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.49439430236816406},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.42588526010513306},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.41042324900627136},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.07358196377754211}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7895714044570923},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7532235383987427},{"id":"https://openalex.org/C188441871","wikidata":"https://www.wikidata.org/wiki/Q7554146","display_name":"Softmax function","level":3,"score":0.7225195169448853},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6729320883750916},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5801144242286682},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5547295808792114},{"id":"https://openalex.org/C48983235","wikidata":"https://www.wikidata.org/wiki/Q593161","display_name":"Light field","level":2,"score":0.5309566855430603},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.5102534294128418},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.49439430236816406},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.42588526010513306},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.41042324900627136},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.07358196377754211},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/acii.2019.8925445","is_oa":false,"landing_page_url":"https://doi.org/10.1109/acii.2019.8925445","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 8th International Conference on Affective Computing and Intelligent Interaction (ACII)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W1598796236","https://openalex.org/W1686810756","https://openalex.org/W1965947362","https://openalex.org/W2049862374","https://openalex.org/W2063366997","https://openalex.org/W2064675550","https://openalex.org/W2073942619","https://openalex.org/W2096171208","https://openalex.org/W2104175489","https://openalex.org/W2137313943","https://openalex.org/W2141200867","https://openalex.org/W2142813212","https://openalex.org/W2150293569","https://openalex.org/W2158198839","https://openalex.org/W2164623278","https://openalex.org/W2195207531","https://openalex.org/W2243226955","https://openalex.org/W2244142460","https://openalex.org/W2251198138","https://openalex.org/W2253728219","https://openalex.org/W2292885564","https://openalex.org/W2345305417","https://openalex.org/W2414501075","https://openalex.org/W2441198140","https://openalex.org/W2516472199","https://openalex.org/W2519280274","https://openalex.org/W2613569861","https://openalex.org/W2756315940","https://openalex.org/W2767415038","https://openalex.org/W2782072221","https://openalex.org/W2792324968","https://openalex.org/W2792396704","https://openalex.org/W2799041689","https://openalex.org/W2883099249","https://openalex.org/W2885653416","https://openalex.org/W2891096297","https://openalex.org/W2894766532","https://openalex.org/W2894805842","https://openalex.org/W2895006884","https://openalex.org/W2902603854","https://openalex.org/W2905628412","https://openalex.org/W2962835968","https://openalex.org/W2963252191","https://openalex.org/W2963602021","https://openalex.org/W3123581847","https://openalex.org/W4289744912","https://openalex.org/W4298857891","https://openalex.org/W6675875113","https://openalex.org/W6680152570","https://openalex.org/W6700903540","https://openalex.org/W6727000516","https://openalex.org/W6754752091","https://openalex.org/W6754945939","https://openalex.org/W6755023374","https://openalex.org/W6789313404"],"related_works":["https://openalex.org/W3107204728","https://openalex.org/W4287591324","https://openalex.org/W3108503355","https://openalex.org/W3090555870","https://openalex.org/W4226420367","https://openalex.org/W2962876041","https://openalex.org/W3022820045","https://openalex.org/W2801655600","https://openalex.org/W2899027234","https://openalex.org/W3120400911"],"abstract_inverted_index":{"Light":[0],"field":[1,177],"cameras":[2,46],"capture":[3],"the":[4,33,53,57,77,101,134,150,160,174],"intensity":[5],"of":[6,17,32,59,136,168],"light":[7,176],"rays":[8],"coming":[9],"from":[10,35],"multiple":[11],"directions,":[12],"thus":[13],"allowing":[14],"a":[15,83,89],"set":[16,167],"2D":[18],"images,":[19,23,117],"named":[20],"sub-aperture":[21],"(SA)":[22],"to":[24,30,74,129,158],"be":[25],"rendered.":[26],"These":[27],"images":[28],"correspond":[29],"observations":[31],"scene":[34],"slightly":[36],"different":[37],"angles.":[38],"The":[39,96,124,144,184],"rich":[40],"spatio-angular":[41,66,104],"information":[42],"obtained":[43,148],"using":[44,82,180],"these":[45],"is":[47,69,72],"exploited":[48],"in":[49,56],"this":[50],"paper,":[51],"for":[52,118,149],"first":[54],"time,":[55],"context":[58],"facial":[60],"emotion":[61,162,189],"recognition.":[62],"A":[63,165],"deep":[64,103],"learning":[65,138],"fusion":[67,105],"framework":[68,186],"adopted":[70,102,185],"which":[71,119],"able":[73],"model":[75],"both":[76],"intra-view/spatial":[78],"and":[79,88,112,140,152],"inter-view/angular":[80],"information,":[81],"VGG-16":[84],"convolutional":[85],"neural":[86],"network":[87],"long":[90],"short-term":[91],"memory":[92],"(LSTM)":[93],"recurrent":[94],"network.":[95],"proposed":[97],"solution,":[98],"based":[99],"on":[100,173],"framework,":[106],"creates":[107],"two":[108,130,181],"view":[109],"sequences,":[110],"horizontal":[111,139,151],"vertical,":[113],"with":[114,133,194],"selected":[115],"SA":[116],"VGG-Face":[120],"descriptions":[121,126],"are":[122,127,155],"extracted.":[123],"resulting":[125],"fed":[128],"LSTM":[131],"networks,":[132],"aim":[135],"independently":[137],"vertical":[141,153],"classification":[142],"models.":[143],"softmax":[145],"classifier":[146],"scores":[147],"descriptors":[154],"then":[156],"fused":[157],"obtain":[159],"final":[161],"recognition":[163,190],"labels.":[164],"comprehensive":[166],"experiments":[169],"has":[170],"been":[171],"conducted":[172],"IST-EURECOM":[175],"face":[178],"database":[179],"assessment":[182],"protocols.":[183],"achieves":[187],"superior":[188],"performance":[191],"when":[192],"compared":[193],"state-of-the-art":[195],"benchmarking":[196],"methods.":[197]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
