{"id":"https://openalex.org/W4210353742","doi":"https://doi.org/10.1109/tmm.2022.3144893","title":"Accurate Head Pose Estimation Using Image Rectification and a Lightweight Convolutional Neural Network","display_name":"Accurate Head Pose Estimation Using Image Rectification and a Lightweight Convolutional Neural Network","publication_year":2022,"publication_date":"2022-01-25","ids":{"openalex":"https://openalex.org/W4210353742","doi":"https://doi.org/10.1109/tmm.2022.3144893"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2022.3144893","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2022.3144893","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","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/A5100708804","display_name":"Xiao Li","orcid":"https://orcid.org/0000-0002-9606-5292"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiao Li","raw_affiliation_strings":["School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-9606-5292","affiliations":[{"raw_affiliation_string":"School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100366134","display_name":"Dong Zhang","orcid":"https://orcid.org/0000-0003-0825-3400"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dong Zhang","raw_affiliation_strings":["School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0003-0825-3400","affiliations":[{"raw_affiliation_string":"School of Electronics and Information Technology, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100351449","display_name":"Ming Li","orcid":"https://orcid.org/0000-0002-6406-1983"},"institutions":[{"id":"https://openalex.org/I4210159968","display_name":"Duke Kunshan University","ror":"https://ror.org/04sr5ys16","country_code":"CN","type":"education","lineage":["https://openalex.org/I170897317","https://openalex.org/I37461747","https://openalex.org/I4210159968"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming Li","raw_affiliation_strings":["Duke Kunshan University, Kunshan, China"],"raw_orcid":"https://orcid.org/0000-0002-6406-1983","affiliations":[{"raw_affiliation_string":"Duke Kunshan University, Kunshan, China","institution_ids":["https://openalex.org/I4210159968"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065513075","display_name":"Dah-Jye Lee","orcid":"https://orcid.org/0000-0003-1752-8146"},"institutions":[{"id":"https://openalex.org/I100005738","display_name":"Brigham Young University","ror":"https://ror.org/047rhhm47","country_code":"US","type":"education","lineage":["https://openalex.org/I100005738"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dah-Jye Lee","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Brigham Young University, Provo, UT, USA"],"raw_orcid":"https://orcid.org/0000-0003-1752-8146","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Brigham Young University, Provo, UT, USA","institution_ids":["https://openalex.org/I100005738"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.2337,"has_fulltext":false,"cited_by_count":24,"citation_normalized_percentile":{"value":0.88975158,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"25","issue":null,"first_page":"2239","last_page":"2251"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9998999834060669,"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":0.9998999834060669,"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":0.991100013256073,"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/T12301","display_name":"Facial Nerve Paralysis Treatment and Research","score":0.9732999801635742,"subfield":{"id":"https://openalex.org/subfields/2728","display_name":"Neurology"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8559541702270508},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.8402920961380005},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8306941986083984},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7885174751281738},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6917131543159485},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.6579914093017578},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.6214960217475891},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.6021950244903564},{"id":"https://openalex.org/keywords/image-rectification","display_name":"Image rectification","score":0.587303876876831},{"id":"https://openalex.org/keywords/rectification","display_name":"Rectification","score":0.49595364928245544},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.44978344440460205},{"id":"https://openalex.org/keywords/human-head","display_name":"Human head","score":0.44831517338752747},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.4357945919036865},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.4226393699645996},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3849620521068573},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.37052738666534424}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8559541702270508},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.8402920961380005},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8306941986083984},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7885174751281738},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6917131543159485},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.6579914093017578},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.6214960217475891},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.6021950244903564},{"id":"https://openalex.org/C171614847","wikidata":"https://www.wikidata.org/wiki/Q1262415","display_name":"Image rectification","level":4,"score":0.587303876876831},{"id":"https://openalex.org/C50942859","wikidata":"https://www.wikidata.org/wiki/Q4967193","display_name":"Rectification","level":3,"score":0.49595364928245544},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.44978344440460205},{"id":"https://openalex.org/C2780549717","wikidata":"https://www.wikidata.org/wiki/Q3409626","display_name":"Human head","level":3,"score":0.44831517338752747},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.4357945919036865},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.4226393699645996},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3849620521068573},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.37052738666534424},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"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/C125287762","wikidata":"https://www.wikidata.org/wiki/Q1758948","display_name":"Absorption (acoustics)","level":2,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2022.3144893","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2022.3144893","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"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 Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1270229601","display_name":null,"funder_award_id":"62171207","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G1545573750","display_name":null,"funder_award_id":"62173353","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":61,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1527240141","https://openalex.org/W1643185111","https://openalex.org/W1825120740","https://openalex.org/W1896788142","https://openalex.org/W1925384340","https://openalex.org/W1963599662","https://openalex.org/W1995694455","https://openalex.org/W2012885984","https://openalex.org/W2047508432","https://openalex.org/W2047875689","https://openalex.org/W2058961190","https://openalex.org/W2087681821","https://openalex.org/W2088028039","https://openalex.org/W2114763125","https://openalex.org/W2122782540","https://openalex.org/W2129210471","https://openalex.org/W2131213359","https://openalex.org/W2136000821","https://openalex.org/W2141047752","https://openalex.org/W2142727917","https://openalex.org/W2144578817","https://openalex.org/W2149382413","https://openalex.org/W2153094732","https://openalex.org/W2157285372","https://openalex.org/W2215711223","https://openalex.org/W2234480906","https://openalex.org/W2345283274","https://openalex.org/W2531409750","https://openalex.org/W2540768567","https://openalex.org/W2548780814","https://openalex.org/W2621061298","https://openalex.org/W2736648018","https://openalex.org/W2737047298","https://openalex.org/W2737644856","https://openalex.org/W2798553619","https://openalex.org/W2921699956","https://openalex.org/W2923153064","https://openalex.org/W2949662773","https://openalex.org/W2951863938","https://openalex.org/W2957744218","https://openalex.org/W2962766044","https://openalex.org/W2963163009","https://openalex.org/W2963349720","https://openalex.org/W2963644257","https://openalex.org/W2963861381","https://openalex.org/W2964014798","https://openalex.org/W2964171387","https://openalex.org/W2982083293","https://openalex.org/W3015671815","https://openalex.org/W3034552680","https://openalex.org/W3104792420","https://openalex.org/W3156669901","https://openalex.org/W3175906877","https://openalex.org/W4297775537","https://openalex.org/W6631190155","https://openalex.org/W6631618440","https://openalex.org/W6662335928","https://openalex.org/W6677531174","https://openalex.org/W6737664043","https://openalex.org/W6762563763"],"related_works":["https://openalex.org/W2372715484","https://openalex.org/W2755641224","https://openalex.org/W2375893148","https://openalex.org/W139502281","https://openalex.org/W2392564394","https://openalex.org/W2069867538","https://openalex.org/W2036165812","https://openalex.org/W4253893311","https://openalex.org/W3089306886","https://openalex.org/W2005372642"],"abstract_inverted_index":{"Head":[0],"pose":[1,24,38,87,148,157,176,201],"estimation":[2,25,39,158,202],"is":[3,115,128,134,164],"an":[4],"important":[5],"step":[6],"for":[7],"many":[8],"human-computer":[9],"interaction":[10],"applications":[11,28],"such":[12],"as":[13,33,142,172],"face":[14,31,53,113,140,162],"detection,":[15],"facial":[16,19],"recognition,":[17],"and":[18,76,102,190,214],"expression":[20],"classification.":[21],"Accurate":[22],"head":[23,37,86,147,156,175,200],"benefits":[26],"these":[27],"that":[29,64,127,184],"require":[30],"images":[32],"the":[34,46,56,70,93,96,100,103,107,110,138,143,153,155,160,168,173,185,191,197],"input.":[35],"Most":[36],"methods":[40],"suffer":[41],"from":[42],"perspective":[43,74,122],"distortion":[44,75],"because":[45],"users":[47],"do":[48],"not":[49],"always":[50],"align":[51],"their":[52],"perfectly":[54],"with":[55,205],"camera.":[57],"This":[58],"paper":[59],"presents":[60],"a":[61,77],"new":[62],"approach":[63,209],"uses":[65],"image":[66,114,141,187],"rectification":[67,188],"to":[68,82,136,145,167],"reduce":[69],"negative":[71],"effect":[72],"of":[73,99,106,109,152,159,199],"lightweight":[78,125,194],"convolutional":[79],"neural":[80],"network":[81,126,195],"obtain":[83],"highly":[84],"accurate":[85],"estimations.":[88],"The":[89,112,150],"proposed":[90,186],"method":[91,189],"calculates":[92],"angle":[94,120],"between":[95],"optical":[97],"axis":[98],"camera":[101,169],"projection":[104],"vector":[105],"center":[108],"face.":[111],"rectified":[116,139,161],"using":[117],"this":[118],"estimated":[119],"through":[121],"transformation.":[123],"A":[124],"only":[129],"0.88":[130],"MB":[131],"in":[132],"size":[133],"designed":[135,193],"take":[137],"input":[144],"perform":[146],"estimation.":[149,177],"output":[151],"network,":[154],"image,":[163],"transformed":[165],"back":[166],"coordinate":[170],"system":[171],"final":[174],"Experiments":[178],"on":[179],"public":[180],"benchmark":[181],"datasets":[182],"show":[183],"newly":[192],"improve":[196],"accuracy":[198,213],"remarkably.":[203],"Compared":[204],"state-of-the-art":[206],"methods,":[207],"our":[208],"achieves":[210],"both":[211],"higher":[212],"faster":[215],"processing":[216],"speed.":[217]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
