{"id":"https://openalex.org/W3089766630","doi":"https://doi.org/10.1109/ijcnn48605.2020.9207542","title":"Emotion Detection using Periocular Region: A Cross-Dataset Study","display_name":"Emotion Detection using Periocular Region: A Cross-Dataset Study","publication_year":2020,"publication_date":"2020-07-01","ids":{"openalex":"https://openalex.org/W3089766630","doi":"https://doi.org/10.1109/ijcnn48605.2020.9207542","mag":"3089766630"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn48605.2020.9207542","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9207542","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5112355795","display_name":"Narsi Reddy","orcid":null},"institutions":[{"id":"https://openalex.org/I75421653","display_name":"University of Missouri\u2013Kansas City","ror":"https://ror.org/01w0d5g70","country_code":"US","type":"education","lineage":["https://openalex.org/I75421653"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Narsi Reddy","raw_affiliation_strings":["Dept. of Computer Science and Electrical Engineering, University of Missouri, Kansas City, MO, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science and Electrical Engineering, University of Missouri, Kansas City, MO, USA","institution_ids":["https://openalex.org/I75421653"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103133910","display_name":"Reza Derakhshani","orcid":"https://orcid.org/0000-0002-2351-1730"},"institutions":[{"id":"https://openalex.org/I75421653","display_name":"University of Missouri\u2013Kansas City","ror":"https://ror.org/01w0d5g70","country_code":"US","type":"education","lineage":["https://openalex.org/I75421653"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Reza Derakhshani","raw_affiliation_strings":["Dept. of Computer Science and Electrical Engineering, University of Missouri, Kansas City, MO, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Computer Science and Electrical Engineering, University of Missouri, Kansas City, MO, USA","institution_ids":["https://openalex.org/I75421653"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I75421653"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9959999918937683,"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/T11448","display_name":"Face recognition and analysis","score":0.9959999918937683,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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":0.9922000169754028,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7812700271606445},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7790004014968872},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.7741696834564209},{"id":"https://openalex.org/keywords/histogram-of-oriented-gradients","display_name":"Histogram of oriented gradients","score":0.6717690229415894},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5810607671737671},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.5489892363548279},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5484758019447327},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.5097405314445496},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5072469115257263},{"id":"https://openalex.org/keywords/demographics","display_name":"Demographics","score":0.5036057829856873},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.501624345779419},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4874906539916992},{"id":"https://openalex.org/keywords/cross-validation","display_name":"Cross-validation","score":0.4538787603378296},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.44616737961769104},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.43062594532966614},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1311379075050354}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7812700271606445},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7790004014968872},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.7741696834564209},{"id":"https://openalex.org/C17426736","wikidata":"https://www.wikidata.org/wiki/Q419918","display_name":"Histogram of oriented gradients","level":4,"score":0.6717690229415894},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5810607671737671},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5489892363548279},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5484758019447327},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.5097405314445496},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5072469115257263},{"id":"https://openalex.org/C2780084366","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demographics","level":2,"score":0.5036057829856873},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.501624345779419},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4874906539916992},{"id":"https://openalex.org/C27181475","wikidata":"https://www.wikidata.org/wiki/Q541014","display_name":"Cross-validation","level":2,"score":0.4538787603378296},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.44616737961769104},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.43062594532966614},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1311379075050354},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn48605.2020.9207542","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn48605.2020.9207542","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Joint Conference on Neural Networks (IJCNN)","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":33,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1654036628","https://openalex.org/W1964981411","https://openalex.org/W1965947362","https://openalex.org/W1979189411","https://openalex.org/W2003238582","https://openalex.org/W2004197686","https://openalex.org/W2103943262","https://openalex.org/W2106115875","https://openalex.org/W2115252128","https://openalex.org/W2117539524","https://openalex.org/W2186574009","https://openalex.org/W2244142460","https://openalex.org/W2377824622","https://openalex.org/W2590378553","https://openalex.org/W2788728386","https://openalex.org/W2799041689","https://openalex.org/W2891399311","https://openalex.org/W2896157115","https://openalex.org/W2896245383","https://openalex.org/W2904483377","https://openalex.org/W2911366667","https://openalex.org/W2945479660","https://openalex.org/W2963163009","https://openalex.org/W2964121744","https://openalex.org/W3124675547","https://openalex.org/W4288602157","https://openalex.org/W4403242122","https://openalex.org/W6631190155","https://openalex.org/W6677618333","https://openalex.org/W6750843368","https://openalex.org/W6755154942","https://openalex.org/W6758799208"],"related_works":["https://openalex.org/W816105089","https://openalex.org/W3201126466","https://openalex.org/W912456583","https://openalex.org/W4282827391","https://openalex.org/W4318240167","https://openalex.org/W4386828785","https://openalex.org/W1527929073","https://openalex.org/W3165580226","https://openalex.org/W2509272512","https://openalex.org/W2123478443"],"abstract_inverted_index":{"Many":[0],"computer":[1],"vision":[2],"methods":[3],"have":[4],"been":[5],"proposed":[6],"for":[7,56,115,179],"the":[8,23,31,45,66,112,124,144,158],"affective":[9],"assessment":[10,59,184],"using":[11,60,87,95,185],"facial":[12,119,170],"expressions":[13,120,171],"from":[14],"full-face":[15],"images.":[16],"In":[17,40],"many":[18],"use":[19],"cases,":[20],"however,":[21],"only":[22,137,186],"ocular":[24,57],"region":[25],"may":[26],"be":[27],"available":[28],"due":[29],"to":[30,130,174],"application":[32],"of":[33,47,97,146,167],"masks,":[34],"clothing":[35],"items,":[36],"or":[37],"privacy":[38],"issues.":[39],"this":[41,180],"paper,":[42],"we":[43,64],"show":[44,131,156],"utility":[46],"a":[48,82,91],"robust":[49],"and":[50,71,121,176],"yet":[51],"light":[52],"deep":[53,84,159],"learning":[54,85,160],"model":[55,67,161],"affect":[58],"cross-dataset":[61,139,182],"evaluation,":[62],"where":[63],"train":[65],"on":[68,74,111,123],"one":[69],"dataset":[70,76,114],"perform":[72],"testing":[73],"another":[75],"with":[77,90,102,117],"different":[78],"demographics.":[79],"We":[80],"compare":[81],"MobileNet-V2":[83],"model,":[86],"transfer":[88],"learning,":[89],"more":[92,125],"traditional":[93],"method":[94],"histogram":[96],"oriented":[98],"gradients":[99],"(HOG)":[100],"features":[101],"support":[103],"vector":[104],"machine":[105],"(SVM)":[106],"classifier.":[107],"Experiments":[108],"were":[109],"conducted":[110],"FACES":[113],"training":[116],"six":[118],"tested":[122],"diverse":[126],"Chicago":[127],"faces":[128],"dataset(CFD)":[129],"how":[132],"evaluated":[133],"models":[134],"generalize":[135],"not":[136,149],"in":[138,143],"evaluation":[140],"but":[141],"also":[142],"presence":[145],"new":[147],"ethnicities":[148],"present":[150],"during":[151],"training.":[152],"The":[153],"experimental":[154],"results":[155],"that":[157],"can":[162],"provide":[163],"an":[164],"average":[165],"accuracy":[166],"76.77%":[168],"overall":[169],"when":[172],"compared":[173],"HOG":[175],"SVM's":[177],"62.47%":[178],"challenging":[181],"emotion":[183],"eye":[187],"regions.":[188]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
