{"id":"https://openalex.org/W3160792241","doi":"https://doi.org/10.1109/tits.2021.3075350","title":"Temporal Head Pose Estimation From Point Cloud in Naturalistic Driving Conditions","display_name":"Temporal Head Pose Estimation From Point Cloud in Naturalistic Driving Conditions","publication_year":2021,"publication_date":"2021-05-06","ids":{"openalex":"https://openalex.org/W3160792241","doi":"https://doi.org/10.1109/tits.2021.3075350","mag":"3160792241"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2021.3075350","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tits.2021.3075350","pdf_url":"https://ieeexplore.ieee.org/ielx7/6979/9826234/09425023.pdf","source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://ieeexplore.ieee.org/ielx7/6979/9826234/09425023.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006591088","display_name":"Tiancheng Hu","orcid":"https://orcid.org/0009-0006-7354-1088"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tiancheng Hu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The University of Texas at Dallas, Dallas, TX, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The University of Texas at Dallas, Dallas, TX, USA","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101918839","display_name":"Sumit Jha","orcid":"https://orcid.org/0000-0001-6402-494X"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sumit Jha","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The University of Texas at Dallas, Dallas, TX, USA"],"raw_orcid":"https://orcid.org/0000-0001-6402-494X","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The University of Texas at Dallas, Dallas, TX, USA","institution_ids":["https://openalex.org/I162577319"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040793194","display_name":"Carlos Busso","orcid":"https://orcid.org/0000-0002-4075-4072"},"institutions":[{"id":"https://openalex.org/I162577319","display_name":"The University of Texas at Dallas","ror":"https://ror.org/049emcs32","country_code":"US","type":"education","lineage":["https://openalex.org/I162577319"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Carlos Busso","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The University of Texas at Dallas, Dallas, TX, USA"],"raw_orcid":"https://orcid.org/0000-0002-4075-4072","affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The University of Texas at Dallas, Dallas, TX, USA","institution_ids":["https://openalex.org/I162577319"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I162577319"],"apc_list":null,"apc_paid":null,"fwci":1.5443,"has_fulltext":true,"cited_by_count":23,"citation_normalized_percentile":{"value":0.82967257,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":93,"max":98},"biblio":{"volume":"23","issue":"7","first_page":"8063","last_page":"8076"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9993000030517578,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9993000030517578,"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/T11448","display_name":"Face recognition and analysis","score":0.9980999827384949,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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":0.7496455311775208},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7441149950027466},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6980507373809814},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6154955625534058},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.6019350290298462},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5196598768234253},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.512806236743927},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.46641314029693604},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4655972421169281},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4462069571018219},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36271345615386963}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7496455311775208},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7441149950027466},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6980507373809814},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6154955625534058},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.6019350290298462},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5196598768234253},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.512806236743927},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.46641314029693604},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4655972421169281},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4462069571018219},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36271345615386963},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","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":1,"locations":[{"id":"doi:10.1109/tits.2021.3075350","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tits.2021.3075350","pdf_url":"https://ieeexplore.ieee.org/ielx7/6979/9826234/09425023.pdf","source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1109/tits.2021.3075350","is_oa":true,"landing_page_url":"https://doi.org/10.1109/tits.2021.3075350","pdf_url":"https://ieeexplore.ieee.org/ielx7/6979/9826234/09425023.pdf","source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"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 Intelligent Transportation Systems","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.6399999856948853}],"awards":[{"id":"https://openalex.org/G5875809265","display_name":null,"funder_award_id":"2810.014","funder_id":"https://openalex.org/F4320306087","funder_display_name":"Semiconductor Research Corporation"}],"funders":[{"id":"https://openalex.org/F4320306087","display_name":"Semiconductor Research Corporation","ror":"https://ror.org/047z4n946"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3160792241.pdf","grobid_xml":"https://content.openalex.org/works/W3160792241.grobid-xml"},"referenced_works_count":65,"referenced_works":["https://openalex.org/W18611558","https://openalex.org/W19135718","https://openalex.org/W198235305","https://openalex.org/W1567532702","https://openalex.org/W1960395571","https://openalex.org/W1964232317","https://openalex.org/W1974744233","https://openalex.org/W1987654648","https://openalex.org/W2029544449","https://openalex.org/W2047875689","https://openalex.org/W2064675550","https://openalex.org/W2083638830","https://openalex.org/W2088028039","https://openalex.org/W2092432777","https://openalex.org/W2094577405","https://openalex.org/W2100138391","https://openalex.org/W2139014568","https://openalex.org/W2145708690","https://openalex.org/W2150585588","https://openalex.org/W2151802865","https://openalex.org/W2156322464","https://openalex.org/W2158047270","https://openalex.org/W2164598857","https://openalex.org/W2194775991","https://openalex.org/W2215711223","https://openalex.org/W2237250383","https://openalex.org/W2277498883","https://openalex.org/W2281572045","https://openalex.org/W2295870746","https://openalex.org/W2305684127","https://openalex.org/W2508429489","https://openalex.org/W2560609797","https://openalex.org/W2562996209","https://openalex.org/W2593748903","https://openalex.org/W2735189551","https://openalex.org/W2737146145","https://openalex.org/W2738989550","https://openalex.org/W2741922652","https://openalex.org/W2769581371","https://openalex.org/W2790510723","https://openalex.org/W2791777119","https://openalex.org/W2793296744","https://openalex.org/W2806125796","https://openalex.org/W2807126412","https://openalex.org/W2885905848","https://openalex.org/W2896423298","https://openalex.org/W2904325242","https://openalex.org/W2921536280","https://openalex.org/W2949924544","https://openalex.org/W2953303875","https://openalex.org/W2963644257","https://openalex.org/W2963794138","https://openalex.org/W2963919999","https://openalex.org/W2964014798","https://openalex.org/W2970106338","https://openalex.org/W2979750740","https://openalex.org/W3000681136","https://openalex.org/W3089840912","https://openalex.org/W3113416056","https://openalex.org/W3118281159","https://openalex.org/W3118941076","https://openalex.org/W4246495810","https://openalex.org/W6739778489","https://openalex.org/W6770086194","https://openalex.org/W6787791458"],"related_works":["https://openalex.org/W2822883015","https://openalex.org/W2295870746","https://openalex.org/W1461621550","https://openalex.org/W2970216048","https://openalex.org/W4290774832","https://openalex.org/W4293067784","https://openalex.org/W3102636071","https://openalex.org/W2997897143","https://openalex.org/W2020350089","https://openalex.org/W3206828132"],"abstract_inverted_index":{"Head":[0,96],"pose":[1,23,61,119],"estimation":[2,14,62,120],"is":[3,63],"an":[4],"important":[5,102],"problem":[6,66],"as":[7,12],"it":[8],"facilitates":[9],"tasks":[10],"such":[11],"gaze":[13],"and":[15,35,76,177,187],"attention":[16],"modeling.":[17],"In":[18],"the":[19,28,68,136,141,160,203,206],"automotive":[20],"context,":[21],"head":[22,60,78,118],"provides":[24,193],"crucial":[25],"information":[26,192],"about":[27],"driver\u2019s":[29],"mental":[30],"state,":[31],"including":[32],"drowsiness,":[33],"distraction":[34],"attention.":[36],"It":[37],"can":[38,88],"also":[39,201],"be":[40,89],"used":[41],"for":[42,117],"interaction":[43],"with":[44,101],"in-vehicle":[45],"infotainment":[46],"systems.":[47],"While":[48],"computer":[49],"vision":[50],"algorithms":[51,172],"using":[52,93,173,180],"RGB":[53,181],"cameras":[54],"are":[55,81,99,146],"reliable":[56],"in":[57,67,83,198,202],"controlled":[58],"environments,":[59],"a":[64,84,111],"challenging":[65],"car":[69],"due":[70],"to":[71,170],"sudden":[72],"illumination":[73],"changes,":[74],"occlusions":[75],"large":[77,194],"rotations":[79],"that":[80,189],"common":[82],"vehicle.":[85],"These":[86],"issues":[87],"partially":[90],"alleviated":[91],"by":[92],"depth":[94],"cameras.":[95],"rotation":[97],"trajectories":[98],"continuous":[100],"temporal":[103,113,191],"dependencies.":[104],"Our":[105],"study":[106],"leverages":[107],"this":[108,157],"observation,":[109],"proposing":[110],"novel":[112],"deep":[114],"learning":[115],"model":[116,158],"from":[121,131],"point":[122,132,174],"cloud.":[123],"The":[124,143],"approach":[125],"extracts":[126],"discriminative":[127],"feature":[128],"representation":[129],"directly":[130],"cloud":[133,175],"data,":[134,176],"leveraging":[135],"3D":[137],"spatial":[138],"structure":[139],"of":[140,205],"face.":[142],"frame-based":[144],"representations":[145],"then":[147],"combined":[148],"withbidirectional":[149],"long":[150],"short":[151],"term":[152],"memory(BLSTM)":[153],"layers.":[154],"We":[155,183],"train":[156],"on":[159],"newly":[161],"collectedmultimodal":[162],"driver":[163],"monitoring(MDM)":[164],"dataset,":[165],"achieving":[166],"better":[167],"results":[168],"compared":[169],"non-temporal":[171],"state-of-the-art":[178],"models":[179],"images.":[182],"further":[184],"show":[185],"quantitatively":[186],"qualitatively":[188],"incorporating":[190],"improvements":[195],"not":[196],"only":[197],"accuracy,":[199],"but":[200],"smoothness":[204],"predictions.":[207]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":2}],"updated_date":"2026-07-29T09:40:50.615796","created_date":"2025-10-10T00:00:00"}