{"id":"https://openalex.org/W2909533195","doi":"https://doi.org/10.1109/ipta.2018.8608130","title":"Driver Drowsiness Detection in Facial Images","display_name":"Driver Drowsiness Detection in Facial Images","publication_year":2018,"publication_date":"2018-11-01","ids":{"openalex":"https://openalex.org/W2909533195","doi":"https://doi.org/10.1109/ipta.2018.8608130","mag":"2909533195"},"language":"en","primary_location":{"id":"doi:10.1109/ipta.2018.8608130","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipta.2018.8608130","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Eighth International Conference on Image Processing Theory, Tools and Applications (IPTA)","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/A5081042741","display_name":"Fadi Dornaika","orcid":"https://orcid.org/0000-0001-6581-9680"},"institutions":[{"id":"https://openalex.org/I169108374","display_name":"University of the Basque Country","ror":"https://ror.org/000xsnr85","country_code":"ES","type":"education","lineage":["https://openalex.org/I169108374"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"F. Dornaika","raw_affiliation_strings":["University of the Basque Country (UPV/EHU),San Sebastian,Spain"],"affiliations":[{"raw_affiliation_string":"University of the Basque Country (UPV/EHU),San Sebastian,Spain","institution_ids":["https://openalex.org/I169108374"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034632853","display_name":"J. Reta","orcid":null},"institutions":[{"id":"https://openalex.org/I169108374","display_name":"University of the Basque Country","ror":"https://ror.org/000xsnr85","country_code":"ES","type":"education","lineage":["https://openalex.org/I169108374"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"J. Reta","raw_affiliation_strings":["University of the Basque Country (UPV/EHU),San Sebastian,Spain"],"affiliations":[{"raw_affiliation_string":"University of the Basque Country (UPV/EHU),San Sebastian,Spain","institution_ids":["https://openalex.org/I169108374"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021284069","display_name":"Ignacio Arganda\u2010Carreras","orcid":"https://orcid.org/0000-0003-0229-5722"},"institutions":[{"id":"https://openalex.org/I169108374","display_name":"University of the Basque Country","ror":"https://ror.org/000xsnr85","country_code":"ES","type":"education","lineage":["https://openalex.org/I169108374"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"I. Arganda-Carreras","raw_affiliation_strings":["University of the Basque Country (UPV/EHU),San Sebastian,Spain"],"affiliations":[{"raw_affiliation_string":"University of the Basque Country (UPV/EHU),San Sebastian,Spain","institution_ids":["https://openalex.org/I169108374"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5069092734","display_name":"Abdelmalik Moujahid","orcid":"https://orcid.org/0000-0002-4971-3613"},"institutions":[{"id":"https://openalex.org/I169108374","display_name":"University of the Basque Country","ror":"https://ror.org/000xsnr85","country_code":"ES","type":"education","lineage":["https://openalex.org/I169108374"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"A. Moujahid","raw_affiliation_strings":["University of the Basque Country (UPV/EHU),San Sebastian,Spain"],"affiliations":[{"raw_affiliation_string":"University of the Basque Country (UPV/EHU),San Sebastian,Spain","institution_ids":["https://openalex.org/I169108374"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5081042741"],"corresponding_institution_ids":["https://openalex.org/I169108374"],"apc_list":null,"apc_paid":null,"fwci":1.0243,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.79484196,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"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/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.9998000264167786,"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/T12406","display_name":"IoT and GPS-based Vehicle Safety Systems","score":0.9143999814987183,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12597","display_name":"Fire Detection and Safety Systems","score":0.9108999967575073,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6608940958976746},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6593113541603088},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5832082033157349},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.45995911955833435},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.30660876631736755},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.25264739990234375}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6608940958976746},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6593113541603088},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5832082033157349},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.45995911955833435},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.30660876631736755},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.25264739990234375}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ipta.2018.8608130","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ipta.2018.8608130","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Eighth International Conference on Image Processing Theory, Tools and Applications (IPTA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.5799999833106995}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1582347098","https://openalex.org/W1947481528","https://openalex.org/W1988085776","https://openalex.org/W2002195055","https://openalex.org/W2019304502","https://openalex.org/W2036147779","https://openalex.org/W2069484217","https://openalex.org/W2087681821","https://openalex.org/W2119868897","https://openalex.org/W2125186487","https://openalex.org/W2139838138","https://openalex.org/W2139916508","https://openalex.org/W2272340902","https://openalex.org/W2293060818","https://openalex.org/W2319703701","https://openalex.org/W2398206539","https://openalex.org/W2501623684","https://openalex.org/W2585844547","https://openalex.org/W2604676963","https://openalex.org/W2751088292","https://openalex.org/W2766070201","https://openalex.org/W6677648428","https://openalex.org/W6736000754","https://openalex.org/W6941070018"],"related_works":["https://openalex.org/W2106309274","https://openalex.org/W2003685048","https://openalex.org/W1877382520","https://openalex.org/W2532573070","https://openalex.org/W2607108626","https://openalex.org/W2109429441","https://openalex.org/W2248182120","https://openalex.org/W2061697129","https://openalex.org/W2905622784","https://openalex.org/W2314054190"],"abstract_inverted_index":{"Extracting":[0],"effective":[1],"features":[2,65],"of":[3,53,89,115,118,133,154],"fatigue":[4,27,126],"in":[5,28,38,66,92,124],"images":[6],"and":[7,57,122],"videos":[8],"is":[9,41,73,82],"an":[10],"open":[11],"problem.":[12],"This":[13,109],"paper":[14],"introduces":[15],"a":[16,44,112],"face":[17],"image":[18,37,59],"descriptor":[19,60,72],"that":[20,140],"can":[21],"be":[22],"used":[23],"for":[24],"discriminating":[25],"driver":[26],"static":[29],"frames.":[30],"In":[31],"this":[32],"method,":[33],"first,":[34],"each":[35],"facial":[36],"the":[39,54,70,86,90,93,101,131,134,141,152],"sequence":[40],"represented":[42],"by":[43],"pyramid":[45],"whose":[46],"levels":[47],"are":[48,61],"divided":[49],"into":[50],"non-overlapping":[51],"blocks":[52],"same":[55],"size,":[56],"hybrid":[58],"employed":[62],"to":[63,84],"extract":[64],"all":[67],"blocks.":[68],"Then":[69],"obtained":[71],"filtered":[74],"out":[75],"using":[76],"feature":[77,144],"selection.":[78],"Finally,":[79],"non-linear":[80],"SVM":[81],"applied":[83],"predict":[85],"drowsiness":[87],"state":[88],"subject":[91],"image.":[94],"The":[95],"proposed":[96,135,142],"method":[97],"was":[98],"tested":[99],"on":[100,151],"public":[102],"dataset":[103,110],"NTH":[104],"Drowsy":[105],"Driver":[106],"Detection":[107],"(NTHUDDD).":[108],"includes":[111],"wide":[113],"range":[114],"human":[116],"subjects":[117],"different":[119],"genders,":[120],"poses,":[121],"illuminations":[123],"real-life":[125],"conditions.":[127],"Experimental":[128],"results":[129,138],"show":[130,139],"effectiveness":[132],"method.":[136],"These":[137],"hand-crafted":[143],"compare":[145],"favorably":[146],"with":[147],"several":[148],"approaches":[149],"based":[150],"use":[153],"deep":[155],"Convolutional":[156],"Neural":[157],"Nets.":[158]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}