{"id":"https://openalex.org/W2314803599","doi":"https://doi.org/10.1109/ccnc.2016.7444761","title":"A smartphone-based driver fatigue detection using fusion of multiple real-time facial features","display_name":"A smartphone-based driver fatigue detection using fusion of multiple real-time facial features","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2314803599","doi":"https://doi.org/10.1109/ccnc.2016.7444761","mag":"2314803599"},"language":"en","primary_location":{"id":"doi:10.1109/ccnc.2016.7444761","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccnc.2016.7444761","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 13th IEEE Annual Consumer Communications & Networking Conference (CCNC)","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/A5100822555","display_name":"Yantao Qiao","orcid":null},"institutions":[{"id":"https://openalex.org/I4210130704","display_name":"University of Michigan\u2013Dearborn","ror":"https://ror.org/035wtm547","country_code":"US","type":"education","lineage":["https://openalex.org/I4210130704"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yantao Qiao","raw_affiliation_strings":["Department of Computer and Information Science, University of Michigan, Dearborn"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, University of Michigan, Dearborn","institution_ids":["https://openalex.org/I4210130704"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078480632","display_name":"Kai Zeng","orcid":"https://orcid.org/0000-0003-3279-0695"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kai Zeng","raw_affiliation_strings":["Department of Electrical and Computer Engineering, George Mason University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, George Mason University","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054881422","display_name":"Lina Xu","orcid":"https://orcid.org/0000-0001-7600-9579"},"institutions":[{"id":"https://openalex.org/I4210156583","display_name":"Laboratoire d'Informatique de Paris-Nord","ror":"https://ror.org/05g1zjw44","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I4210091279","https://openalex.org/I4210156583","https://openalex.org/I4210159245"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Lina Xu","raw_affiliation_strings":["Computer Science Department, Institute of Informatic Technische Universitt, Mnchen"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, Institute of Informatic Technische Universitt, Mnchen","institution_ids":["https://openalex.org/I4210156583"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029346304","display_name":"Xiaoyu Yin","orcid":"https://orcid.org/0000-0002-4631-3251"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]},{"id":"https://openalex.org/I59499333","display_name":"Optica","ror":"https://ror.org/00jypd850","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I59499333"]}],"countries":["CN","US"],"is_corresponding":false,"raw_author_name":"Xiaoyu Yin","raw_affiliation_strings":["Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Shanghai University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Specialty Fiber Optics and Optical Access Networks, Shanghai University","institution_ids":["https://openalex.org/I113940042","https://openalex.org/I59499333"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":46,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"230","last_page":"235"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11373","display_name":"Sleep and Work-Related Fatigue","score":0.9983999729156494,"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":0.9983999729156494,"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/T12222","display_name":"IoT-based Smart Home Systems","score":0.9639000296592712,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10805","display_name":"Vehicle Dynamics and Control Systems","score":0.9584000110626221,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"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":0.7550069093704224},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6321637630462646},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5832411050796509},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5465105772018433},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5009596347808838},{"id":"https://openalex.org/keywords/variance","display_name":"Variance (accounting)","score":0.4529232084751129},{"id":"https://openalex.org/keywords/time-domain","display_name":"Time domain","score":0.4444618821144104},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4293440878391266},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.42589831352233887},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4228455722332001},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.32323741912841797},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.30674904584884644}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7550069093704224},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6321637630462646},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5832411050796509},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5465105772018433},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5009596347808838},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.4529232084751129},{"id":"https://openalex.org/C103824480","wikidata":"https://www.wikidata.org/wiki/Q185889","display_name":"Time domain","level":2,"score":0.4444618821144104},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4293440878391266},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.42589831352233887},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4228455722332001},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32323741912841797},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.30674904584884644},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccnc.2016.7444761","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccnc.2016.7444761","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 13th IEEE Annual Consumer Communications & Networking Conference (CCNC)","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":12,"referenced_works":["https://openalex.org/W1604111755","https://openalex.org/W1990961925","https://openalex.org/W2019363670","https://openalex.org/W2064243014","https://openalex.org/W2100639089","https://openalex.org/W2119799745","https://openalex.org/W2120409505","https://openalex.org/W2135646578","https://openalex.org/W2164598857","https://openalex.org/W2165661909","https://openalex.org/W3097096317","https://openalex.org/W6666422896"],"related_works":["https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W3214791684","https://openalex.org/W2353265673","https://openalex.org/W2152662039","https://openalex.org/W2726747157","https://openalex.org/W2004817612","https://openalex.org/W2336272890","https://openalex.org/W4308999381","https://openalex.org/W3183843611"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,32,96],"fatigue":[4,48,101],"monitoring":[5],"system":[6,51,79],"focuses":[7],"on":[8],"information":[9],"fusion":[10,94],"is":[11],"designed":[12],"and":[13,21,41,58,64,92,99],"implemented":[14],"in":[15,39],"smartphone.":[16],"Eye":[17],"blinking,":[18],"head":[19],"nod":[20],"yawning":[22,68],"are":[23],"detected":[24],"as":[25],"indicators":[26],"of":[27,46,56,77,84],"driver":[28],"fatigue.":[29],"We":[30],"developed":[31],"mathematical":[33],"model":[34],"to":[35],"extract":[36],"the":[37,78,81],"characteristic":[38],"time":[40,54],"frequency":[42],"domain":[43],"using":[44,61],"mean-variance":[45,90],"key":[47],"parameters.":[49],"The":[50,74],"perform":[52],"real":[53],"detection":[55,66],"face":[57],"eye":[59],"blink":[60],"Harr-like":[62],"technique":[63],"mouth":[65],"for":[67],"with":[69,88],"Canny":[70],"Active":[71],"Contour":[72],"Method.":[73],"testing":[75],"result":[76],"demonstrates":[80],"practical":[82],"use":[83],"multiple":[85],"features,":[86],"particularly":[87],"our":[89],"methods,":[91],"their":[93],"enables":[95],"more":[97],"accurate":[98],"authentic":[100],"detection.":[102]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}