{"id":"https://openalex.org/W3129025339","doi":"https://doi.org/10.1145/3440054.3440058","title":"Driver's Gaze Zone Estimation Method: A Four-channel Convolutional Neural Network Model","display_name":"Driver's Gaze Zone Estimation Method: A Four-channel Convolutional Neural Network Model","publication_year":2020,"publication_date":"2020-12-03","ids":{"openalex":"https://openalex.org/W3129025339","doi":"https://doi.org/10.1145/3440054.3440058","mag":"3129025339"},"language":"en","primary_location":{"id":"doi:10.1145/3440054.3440058","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3440054.3440058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 2nd International Conference on Big-data Service and Intelligent Computation","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/A5002797727","display_name":"Yingji Zhang","orcid":"https://orcid.org/0000-0003-1499-3309"},"institutions":[{"id":"https://openalex.org/I34949971","display_name":"University of Jinan","ror":"https://ror.org/02mjz6f26","country_code":"CN","type":"education","lineage":["https://openalex.org/I34949971"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yingji Zhang","raw_affiliation_strings":["the University of Jinan, China"],"affiliations":[{"raw_affiliation_string":"the University of Jinan, China","institution_ids":["https://openalex.org/I34949971"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054830929","display_name":"Xiaohui Yang","orcid":"https://orcid.org/0000-0001-9677-979X"},"institutions":[{"id":"https://openalex.org/I34949971","display_name":"University of Jinan","ror":"https://ror.org/02mjz6f26","country_code":"CN","type":"education","lineage":["https://openalex.org/I34949971"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaohui Yang","raw_affiliation_strings":["University of Jinan, China"],"affiliations":[{"raw_affiliation_string":"University of Jinan, China","institution_ids":["https://openalex.org/I34949971"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064486012","display_name":"Zhe Ma","orcid":"https://orcid.org/0009-0003-0202-3863"},"institutions":[{"id":"https://openalex.org/I34949971","display_name":"University of Jinan","ror":"https://ror.org/02mjz6f26","country_code":"CN","type":"education","lineage":["https://openalex.org/I34949971"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhe Ma","raw_affiliation_strings":["the University of Jinan"],"affiliations":[{"raw_affiliation_string":"the University of Jinan","institution_ids":["https://openalex.org/I34949971"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5002797727"],"corresponding_institution_ids":["https://openalex.org/I34949971"],"apc_list":null,"apc_paid":null,"fwci":0.5896,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.69489592,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"20","last_page":"24"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11707","display_name":"Gaze Tracking and Assistive Technology","score":1.0,"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":1.0,"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/T10250","display_name":"Glaucoma and retinal disorders","score":0.9559999704360962,"subfield":{"id":"https://openalex.org/subfields/2731","display_name":"Ophthalmology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9506999850273132,"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/gaze","display_name":"Gaze","score":0.9414330124855042},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8738195300102234},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7963287830352783},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6748855113983154},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.6422057151794434},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6197048425674438},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.46511274576187134},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.4499850273132324},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3845439553260803},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.06265294551849365}],"concepts":[{"id":"https://openalex.org/C2779916870","wikidata":"https://www.wikidata.org/wiki/Q14467155","display_name":"Gaze","level":2,"score":0.9414330124855042},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8738195300102234},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7963287830352783},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6748855113983154},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.6422057151794434},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6197048425674438},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.46511274576187134},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.4499850273132324},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3845439553260803},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.06265294551849365},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3440054.3440058","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3440054.3440058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2020 2nd International Conference on Big-data Service and Intelligent Computation","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1750883736","https://openalex.org/W2006803106","https://openalex.org/W2103978011","https://openalex.org/W2116208238","https://openalex.org/W2153264364","https://openalex.org/W2155217597","https://openalex.org/W2279098554","https://openalex.org/W2468114283","https://openalex.org/W2778268008","https://openalex.org/W2786726857","https://openalex.org/W2793506100","https://openalex.org/W2794597837","https://openalex.org/W2962835718","https://openalex.org/W2963525576","https://openalex.org/W3177525997","https://openalex.org/W4362597614"],"related_works":["https://openalex.org/W1880689012","https://openalex.org/W3014378845","https://openalex.org/W4240909707","https://openalex.org/W2059546927","https://openalex.org/W3207760378","https://openalex.org/W4386072035","https://openalex.org/W1986970529","https://openalex.org/W2161294397","https://openalex.org/W2012644758","https://openalex.org/W2047559669"],"abstract_inverted_index":{"Driver's":[0],"gaze":[1,14,42,57,101],"has":[2],"become":[3],"an":[4],"important":[5],"indicator":[6],"to":[7,54,98],"analysis":[8],"driving":[9,29],"state.":[10],"By":[11],"estimating":[12],"the":[13,32,56,60,63,66,69,72,75,78,83,87,91,100,113,118],"zone":[15],"of":[16,59,68,86,93,120],"drivers,":[17],"we":[18,38,104],"can":[19],"further":[20],"judge":[21],"their":[22,28],"fatigue":[23],"state":[24],"and":[25,77,112],"even":[26],"predict":[27],"intention":[30],"in":[31],"next":[33],"step.":[34],"In":[35,62],"this":[36],"paper,":[37],"propose":[39],"a":[40],"four-channel":[41],"estimation":[43],"model":[44],"based":[45],"on":[46],"Convolutional":[47],"Neural":[48],"Network":[49],"(CNN),":[50],"which":[51],"is":[52,123],"used":[53,81],"estimate":[55,99],"zones":[58],"driver.":[61],"proposed":[64],"method,":[65],"images":[67],"right":[70],"eye,":[71,74],"left":[73],"face,":[76],"head":[79],"are":[80,96],"as":[82],"input":[84],"data":[85],"multi-channel":[88],"CNN.":[89],"Then,":[90],"features":[92],"different":[94],"channels":[95],"fused":[97],"zone.":[102],"Finally,":[103],"compared":[105],"our":[106,121],"method":[107,122],"with":[108],"several":[109],"existing":[110],"methods,":[111],"experimental":[114],"results":[115],"show":[116],"that":[117],"accuracy":[119],"96%.":[124]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
