{"id":"https://openalex.org/W2163543587","doi":"https://doi.org/10.1109/tvt.2012.2193910","title":"Recognition of a Driver's Gaze for Vehicle Headlamp Control","display_name":"Recognition of a Driver's Gaze for Vehicle Headlamp Control","publication_year":2012,"publication_date":"2012-04-09","ids":{"openalex":"https://openalex.org/W2163543587","doi":"https://doi.org/10.1109/tvt.2012.2193910","mag":"2163543587"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2012.2193910","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2012.2193910","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","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/A5053644566","display_name":"Jae Hyun Oh","orcid":null},"institutions":[{"id":"https://openalex.org/I57664883","display_name":"Ajou University","ror":"https://ror.org/03tzb2h73","country_code":"KR","type":"education","lineage":["https://openalex.org/I57664883"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Jae Hyun Oh","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Ajou University, Suwon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Ajou University, Suwon, South Korea","institution_ids":["https://openalex.org/I57664883"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084897975","display_name":"Nojun Kwak","orcid":"https://orcid.org/0000-0002-1792-0327"},"institutions":[{"id":"https://openalex.org/I57664883","display_name":"Ajou University","ror":"https://ror.org/03tzb2h73","country_code":"KR","type":"education","lineage":["https://openalex.org/I57664883"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Nojun Kwak","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Ajou University, Suwon, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Ajou University, Suwon, South Korea","institution_ids":["https://openalex.org/I57664883"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I57664883"],"apc_list":null,"apc_paid":null,"fwci":2.9578,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.90669216,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"61","issue":"5","first_page":"2008","last_page":"2017"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9994000196456909,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9864000082015991,"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/T10057","display_name":"Face and Expression Recognition","score":0.9807999730110168,"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":0.8057504296302795},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.6930986046791077},{"id":"https://openalex.org/keywords/gaze","display_name":"Gaze","score":0.6855741739273071},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.6713134050369263},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6256406903266907},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6220805048942566},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6030219793319702},{"id":"https://openalex.org/keywords/headlamp","display_name":"Headlamp","score":0.52852463722229},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43701454997062683},{"id":"https://openalex.org/keywords/rotation","display_name":"Rotation (mathematics)","score":0.4326359033584595},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.42476707696914673},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.19179865717887878}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8057504296302795},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.6930986046791077},{"id":"https://openalex.org/C2779916870","wikidata":"https://www.wikidata.org/wiki/Q14467155","display_name":"Gaze","level":2,"score":0.6855741739273071},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.6713134050369263},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6256406903266907},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6220805048942566},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6030219793319702},{"id":"https://openalex.org/C2777884842","wikidata":"https://www.wikidata.org/wiki/Q869713","display_name":"Headlamp","level":2,"score":0.52852463722229},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43701454997062683},{"id":"https://openalex.org/C74050887","wikidata":"https://www.wikidata.org/wiki/Q848368","display_name":"Rotation (mathematics)","level":2,"score":0.4326359033584595},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.42476707696914673},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.19179865717887878},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","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},{"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":2,"locations":[{"id":"doi:10.1109/tvt.2012.2193910","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2012.2193910","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","raw_type":"journal-article"},{"id":"pmh:oai:s-space.snu.ac.kr:10371/207826","is_oa":false,"landing_page_url":"https://hdl.handle.net/10371/207826","pdf_url":null,"source":{"id":"https://openalex.org/S4306401345","display_name":"Seoul National University Open Repository (Seoul National University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I139264467","host_organization_name":"Seoul National University","host_organization_lineage":["https://openalex.org/I139264467"],"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/10","display_name":"Reduced inequalities","score":0.6800000071525574}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W171524258","https://openalex.org/W1555563476","https://openalex.org/W1587362683","https://openalex.org/W1589443630","https://openalex.org/W1829958643","https://openalex.org/W1886134489","https://openalex.org/W1964475440","https://openalex.org/W1971713783","https://openalex.org/W1990049419","https://openalex.org/W2007492650","https://openalex.org/W2021354104","https://openalex.org/W2052730000","https://openalex.org/W2062989416","https://openalex.org/W2074602185","https://openalex.org/W2097366995","https://openalex.org/W2098693229","https://openalex.org/W2104188055","https://openalex.org/W2104836915","https://openalex.org/W2106418974","https://openalex.org/W2108384452","https://openalex.org/W2111438974","https://openalex.org/W2118460264","https://openalex.org/W2121647436","https://openalex.org/W2130597313","https://openalex.org/W2134262590","https://openalex.org/W2135346934","https://openalex.org/W2139880049","https://openalex.org/W2145859819","https://openalex.org/W2149382413","https://openalex.org/W2153000018","https://openalex.org/W2160759439","https://openalex.org/W2164598857","https://openalex.org/W2170065295","https://openalex.org/W2237125440","https://openalex.org/W2483745592","https://openalex.org/W2739698496","https://openalex.org/W2896366586","https://openalex.org/W3083767870","https://openalex.org/W3144619878","https://openalex.org/W3148981562","https://openalex.org/W6606836890","https://openalex.org/W6633210108","https://openalex.org/W6635414781","https://openalex.org/W6639427110","https://openalex.org/W6674755931","https://openalex.org/W6675607805","https://openalex.org/W6679260439","https://openalex.org/W6682525577"],"related_works":["https://openalex.org/W2384397513","https://openalex.org/W657807921","https://openalex.org/W2381653984","https://openalex.org/W259753140","https://openalex.org/W2156273891","https://openalex.org/W2316040084","https://openalex.org/W840755431","https://openalex.org/W2075836820","https://openalex.org/W2388568947","https://openalex.org/W2009284386"],"abstract_inverted_index":{"In":[0,117,166],"this":[1,72,171],"paper,":[2,172],"we":[3,83],"propose":[4],"a":[5,12,18,58,62,85,173,184,200,210,215],"novel":[6],"method":[7,73,187,198],"for":[8,102,188],"gaze":[9,113,189,202],"recognition":[10,203],"of":[11,17,88,131,176,209],"driver":[13],"coping":[14],"with":[15,135,144],"rotation":[16,207],"driver's":[19,80,112,211],"face.":[20,81],"Frontal":[21],"face":[22,60],"images":[23,28],"and":[24,181],"left":[25,63],"half":[26,46,64],"profile":[27,47,65],"were":[29,107],"separately":[30],"trained":[31],"using":[32],"the":[33,53,79,94,111,118,129,139,148,152,196],"Viola-Jones":[34],"(V-J)":[35],"algorithm":[36],"to":[37,76,93,98,109,124,142,158,168],"produce":[38],"classifiers":[39],"that":[40,127,195],"can":[41,48],"detect":[42,78],"faces.":[43],"The":[44,191],"right":[45],"be":[49],"detected":[50,95],"by":[51],"mirroring":[52],"entire":[54],"image":[55],"when":[56],"neither":[57],"frontal":[59],"nor":[61],"was":[66,74],"detected.":[67],"As":[68],"an":[69],"initial":[70],"step,":[71,121],"used":[75,108,182],"simultaneously":[77],"Then,":[82],"applied":[84],"regressional":[86],"version":[87],"linear":[89],"discriminant":[90],"analysis":[91],"(LDAr)":[92],"facial":[96],"region":[97],"extract":[99],"important":[100],"features":[101,106,126,154],"classification.":[103],"Finally,":[104],"these":[105],"classify":[110],"in":[114,138,147,170,214],"seven":[115],"directions.":[116],"feature":[119,163,185],"extraction":[120,164,186],"LDAr":[122,177],"tries":[123],"find":[125],"maximize":[128],"ratio":[130],"interdistances":[132],"among":[133],"samples":[134],"large":[136],"differences":[137,146],"target":[140,149],"value":[141],"those":[143],"small":[145],"value.":[150],"Therefore,":[151],"resultant":[153],"are":[155],"more":[156],"fitted":[157],"regression":[159],"problems":[160],"than":[161],"conventional":[162],"methods.":[165],"addition":[167],"LDAr,":[169],"2-D":[174],"extension":[175],"is":[178],"also":[179],"developed":[180],"as":[183],"recognition.":[190],"experimental":[192],"results":[193],"show":[194],"proposed":[197],"achieves":[199],"good":[201],"rate":[204],"under":[205],"various":[206],"angles":[208],"head,":[212],"resulting":[213],"reliable":[216],"headlamp":[217],"control":[218],"performance.":[219]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":2}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
