{"id":"https://openalex.org/W4387878196","doi":"https://doi.org/10.3233/faia230662","title":"Full-Range Yaw Prediction: A Multi-View Approach for 3D Head Model Pose Estimation Using Convolutional Neural Networks","display_name":"Full-Range Yaw Prediction: A Multi-View Approach for 3D Head Model Pose Estimation Using Convolutional Neural Networks","publication_year":2023,"publication_date":"2023-10-19","ids":{"openalex":"https://openalex.org/W4387878196","doi":"https://doi.org/10.3233/faia230662"},"language":"en","primary_location":{"id":"doi:10.3233/faia230662","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia230662","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA230662","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"type":"book-chapter","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA230662","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092253465","display_name":"\u00c1lvaro Heredia-Lid\u00f3n","orcid":"https://orcid.org/0000-0001-6325-8744"},"institutions":[{"id":"https://openalex.org/I5593406","display_name":"Universitat Ramon Llull","ror":"https://ror.org/04p9k2z50","country_code":"ES","type":"education","lineage":["https://openalex.org/I5593406"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"\u00c1lvaro Heredia-Lid\u00f3n","raw_affiliation_strings":["HER \u2013 Human-Environment Research Group, La Salle \u2013 Universitat Ramon Llull, Barcelona, Spain"],"raw_orcid":"https://orcid.org/0000-0001-6325-8744","affiliations":[{"raw_affiliation_string":"HER \u2013 Human-Environment Research Group, La Salle \u2013 Universitat Ramon Llull, Barcelona, Spain","institution_ids":["https://openalex.org/I5593406"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030740506","display_name":"Neus Mart\u00ednez\u2010Abad\u00edas","orcid":"https://orcid.org/0000-0003-3061-2123"},"institutions":[{"id":"https://openalex.org/I71999127","display_name":"Universitat de Barcelona","ror":"https://ror.org/021018s57","country_code":"ES","type":"education","lineage":["https://openalex.org/I71999127"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Neus Mart\u00ednez-Abad\u00edas","raw_affiliation_strings":["Departament de Biologia Evolutiva, Ecologia i Ci\u00e8ncies Ambientals (BEECA), Facultat de Biologia, Universitat de Barcelona (UB), Barcelona, Spain"],"raw_orcid":"https://orcid.org/0000-0003-3061-2123","affiliations":[{"raw_affiliation_string":"Departament de Biologia Evolutiva, Ecologia i Ci\u00e8ncies Ambientals (BEECA), Facultat de Biologia, Universitat de Barcelona (UB), Barcelona, Spain","institution_ids":["https://openalex.org/I71999127"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039293393","display_name":"Xavier Sevillano","orcid":"https://orcid.org/0000-0002-6209-3033"},"institutions":[{"id":"https://openalex.org/I5593406","display_name":"Universitat Ramon Llull","ror":"https://ror.org/04p9k2z50","country_code":"ES","type":"education","lineage":["https://openalex.org/I5593406"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Xavier Sevillano","raw_affiliation_strings":["HER \u2013 Human-Environment Research Group, La Salle \u2013 Universitat Ramon Llull, Barcelona, Spain"],"raw_orcid":"https://orcid.org/0000-0002-6209-3033","affiliations":[{"raw_affiliation_string":"HER \u2013 Human-Environment Research Group, La Salle \u2013 Universitat Ramon Llull, Barcelona, Spain","institution_ids":["https://openalex.org/I5593406"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5092253465"],"corresponding_institution_ids":["https://openalex.org/I5593406"],"apc_list":null,"apc_paid":null,"fwci":0.3942,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.67913268,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9965000152587891,"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":0.9965000152587891,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9185000061988831,"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/pose","display_name":"Pose","score":0.861996054649353},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8127591013908386},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7611441016197205},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.7203680872917175},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6896937489509583},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.668070375919342},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.598656415939331},{"id":"https://openalex.org/keywords/head","display_name":"Head (geology)","score":0.5658866167068481},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.508372962474823},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.4658285975456238},{"id":"https://openalex.org/keywords/euler-angles","display_name":"Euler angles","score":0.43931248784065247},{"id":"https://openalex.org/keywords/rotation","display_name":"Rotation (mathematics)","score":0.43372029066085815},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.42529308795928955},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3628746271133423},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09878301620483398},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.07108458876609802}],"concepts":[{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.861996054649353},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8127591013908386},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7611441016197205},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.7203680872917175},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6896937489509583},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.668070375919342},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.598656415939331},{"id":"https://openalex.org/C2780312720","wikidata":"https://www.wikidata.org/wiki/Q5689100","display_name":"Head (geology)","level":2,"score":0.5658866167068481},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.508372962474823},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.4658285975456238},{"id":"https://openalex.org/C146160929","wikidata":"https://www.wikidata.org/wiki/Q751290","display_name":"Euler angles","level":2,"score":0.43931248784065247},{"id":"https://openalex.org/C74050887","wikidata":"https://www.wikidata.org/wiki/Q848368","display_name":"Rotation (mathematics)","level":2,"score":0.43372029066085815},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.42529308795928955},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3628746271133423},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09878301620483398},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07108458876609802},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C114793014","wikidata":"https://www.wikidata.org/wiki/Q52109","display_name":"Geomorphology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3233/faia230662","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia230662","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA230662","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},{"id":"pmh:oai:dau.url.edu:20.500.14342/5502","is_oa":true,"landing_page_url":"http://hdl.handle.net/20.500.14342/5502","pdf_url":"https://dau.url.edu/bitstream/20.500.14342/5502/1/FAIA-375-FAIA230662.pdf","source":{"id":"https://openalex.org/S7407055114","display_name":"DAU - Digital Archive of URL","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.3233/faia230662","is_oa":true,"landing_page_url":"https://doi.org/10.3233/faia230662","pdf_url":"https://ebooks.iospress.nl/pdf/doi/10.3233/FAIA230662","source":{"id":"https://openalex.org/S4210201731","display_name":"Frontiers in artificial intelligence and applications","issn_l":"0922-6389","issn":["0922-6389","1879-8314"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Frontiers in Artificial Intelligence and Applications","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3815383569","display_name":null,"funder_award_id":"2021 SGR00706","funder_id":"https://openalex.org/F4320334830","funder_display_name":"Ag\u00e8ncia de Gesti\u00f3 d'Ajuts Universitaris i de Recerca"}],"funders":[{"id":"https://openalex.org/F4320321505","display_name":"Generalitat de Catalunya","ror":"https://ror.org/01bg62x04"},{"id":"https://openalex.org/F4320334830","display_name":"Ag\u00e8ncia de Gesti\u00f3 d'Ajuts Universitaris i de Recerca","ror":"https://ror.org/01n4pqe45"},{"id":"https://openalex.org/F4320338080","display_name":"European Social Fund","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4387878196.pdf"},"referenced_works_count":13,"referenced_works":["https://openalex.org/W1607753512","https://openalex.org/W2047875689","https://openalex.org/W2163605009","https://openalex.org/W2194775991","https://openalex.org/W2521769738","https://openalex.org/W2618530766","https://openalex.org/W3014882614","https://openalex.org/W3028400540","https://openalex.org/W3034798648","https://openalex.org/W4212907698","https://openalex.org/W4242746942","https://openalex.org/W4308233968","https://openalex.org/W4381887204"],"related_works":["https://openalex.org/W4253893311","https://openalex.org/W2798721181","https://openalex.org/W3201205132","https://openalex.org/W4287600488","https://openalex.org/W4312694060","https://openalex.org/W4281696776","https://openalex.org/W4318148659","https://openalex.org/W4387967917","https://openalex.org/W4299867837","https://openalex.org/W2951583186"],"abstract_inverted_index":{"Head":[0],"pose":[1,35,53,83,105,124,156],"estimation,":[2],"a":[3,14,37,95,100,128,144],"crucial":[4],"task":[5,153],"in":[6,17,32,67],"computer":[7],"vision,":[8],"involves":[9,120],"determining":[10],"the":[11,43,46,63,82,108,122,152,165,170,182],"orientation":[12],"of":[13,81,110,154,161,172],"person\u2019s":[15],"head":[16,34,44,104,115,137,155],"3D":[18,114,123,136,187],"space":[19],"through":[20],"yaw,":[21],"pitch,":[22],"and":[23,177,186],"roll":[24],"angles.":[25],"While":[26],"recent":[27],"techniques":[28],"present":[29],"excellent":[30],"results":[31],"estimating":[33],"from":[36,55,74],"single":[38],"2D":[39,130],"RGB":[40],"image":[41,131],"when":[42,62],"faces":[45],"camera":[47],"directly,":[48],"few":[49],"methods":[50],"exist":[51],"for":[52,86,102],"estimation":[54,80,106,125,157],"arbitrary":[56],"viewpoints.":[57],"This":[58],"problem":[59,126,133],"is":[60,66,84],"emphasised":[61],"input":[64],"data":[65],"3D,":[68],"such":[69],"as":[70,139],"heads":[71],"reconstructed":[72],"models":[73,138,180],"magnetic":[75],"resonances,":[76],"where":[77],"an":[78],"accurate":[79],"necessary":[85],"diagnostic":[87],"purposes.":[88],"To":[89],"overcome":[90],"these":[91],"limitations,":[92],"we":[93,150,175],"make":[94],"first":[96],"step":[97],"by":[98,134],"proposing":[99],"method":[101],"fine-grained":[103],"across":[107],"full-range":[109],"yaw":[111,167],"angles":[112],"using":[113],"synthetic":[116],"models.":[117],"Our":[118],"approach":[119],"transforming":[121],"into":[127],"multi-class":[129],"classification":[132],"representing":[135],"multi-view":[140],"projection":[141],"images.":[142],"Leveraging":[143],"fine-tuned":[145],"ResNet50":[146],"convolutional":[147],"neural":[148],"network,":[149],"tackle":[151],"with":[158,181],"fine":[159],"granularity":[160],"5\u00b0,":[162],"effectively":[163],"discretizing":[164],"360\u00b0":[166],"orientations.":[168],"For":[169],"evaluation":[171],"our":[173,179],"proposal,":[174],"train":[176],"test":[178],"publicly":[183],"available":[184],"FaceScape":[185],"BIWI":[188],"datasets":[189],"obtaining":[190],"promising":[191],"results.":[192]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-02-03T23:48:18.283914","created_date":"2025-10-10T00:00:00"}