{"id":"https://openalex.org/W4392411865","doi":"https://doi.org/10.1109/ijcb57857.2023.10448641","title":"W2H-Net: Fast Prediction of Waist-to-Hip Ratio from Single Partial Dressed Body Scans in Arbitrary Postures via Deep Learning","display_name":"W2H-Net: Fast Prediction of Waist-to-Hip Ratio from Single Partial Dressed Body Scans in Arbitrary Postures via Deep Learning","publication_year":2023,"publication_date":"2023-09-25","ids":{"openalex":"https://openalex.org/W4392411865","doi":"https://doi.org/10.1109/ijcb57857.2023.10448641"},"language":"en","primary_location":{"id":"doi:10.1109/ijcb57857.2023.10448641","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcb57857.2023.10448641","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Joint Conference on Biometrics (IJCB)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://pure.coventry.ac.uk/ws/files/82420239/Hu2024AAM.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5005164531","display_name":"Ran Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I13469542","display_name":"Vrije Universiteit Brussel","ror":"https://ror.org/006e5kg04","country_code":"BE","type":"education","lineage":["https://openalex.org/I13469542"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"Ran Zhao","raw_affiliation_strings":["Vrije Universiteit Brussel,ETRO,Brussels,Belgium","ETRO, Vrije Universiteit Brussel, Brussels, Belgium"],"affiliations":[{"raw_affiliation_string":"Vrije Universiteit Brussel,ETRO,Brussels,Belgium","institution_ids":["https://openalex.org/I13469542"]},{"raw_affiliation_string":"ETRO, Vrije Universiteit Brussel, Brussels, Belgium","institution_ids":["https://openalex.org/I13469542"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048844398","display_name":"Xinxin Dai","orcid":"https://orcid.org/0000-0002-3682-1391"},"institutions":[{"id":"https://openalex.org/I13469542","display_name":"Vrije Universiteit Brussel","ror":"https://ror.org/006e5kg04","country_code":"BE","type":"education","lineage":["https://openalex.org/I13469542"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Xinxin Dai","raw_affiliation_strings":["Vrije Universiteit Brussel,ETRO,Brussels,Belgium","ETRO, Vrije Universiteit Brussel, Brussels, Belgium"],"affiliations":[{"raw_affiliation_string":"Vrije Universiteit Brussel,ETRO,Brussels,Belgium","institution_ids":["https://openalex.org/I13469542"]},{"raw_affiliation_string":"ETRO, Vrije Universiteit Brussel, Brussels, Belgium","institution_ids":["https://openalex.org/I13469542"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090214843","display_name":"Pengpeng Hu","orcid":"https://orcid.org/0000-0002-2547-1517"},"institutions":[{"id":"https://openalex.org/I73417466","display_name":"Coventry University","ror":"https://ror.org/01tgmhj36","country_code":"GB","type":"education","lineage":["https://openalex.org/I73417466"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Pengpeng Hu","raw_affiliation_strings":["Coventry University,Computational Science and Mathematical Modelling,Coventry,UK","Computational Science and Mathematical Modelling, Coventry University, Coventry, UK"],"affiliations":[{"raw_affiliation_string":"Coventry University,Computational Science and Mathematical Modelling,Coventry,UK","institution_ids":["https://openalex.org/I73417466"]},{"raw_affiliation_string":"Computational Science and Mathematical Modelling, Coventry University, Coventry, UK","institution_ids":["https://openalex.org/I73417466"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5088598176","display_name":"Adrian Munteanu","orcid":"https://orcid.org/0000-0001-7290-0428"},"institutions":[{"id":"https://openalex.org/I13469542","display_name":"Vrije Universiteit Brussel","ror":"https://ror.org/006e5kg04","country_code":"BE","type":"education","lineage":["https://openalex.org/I13469542"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Adrian Munteanu","raw_affiliation_strings":["Vrije Universiteit Brussel,ETRO,Brussels,Belgium","ETRO, Vrije Universiteit Brussel, Brussels, Belgium"],"affiliations":[{"raw_affiliation_string":"Vrije Universiteit Brussel,ETRO,Brussels,Belgium","institution_ids":["https://openalex.org/I13469542"]},{"raw_affiliation_string":"ETRO, Vrije Universiteit Brussel, Brussels, Belgium","institution_ids":["https://openalex.org/I13469542"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5005164531"],"corresponding_institution_ids":["https://openalex.org/I13469542"],"apc_list":null,"apc_paid":null,"fwci":0.4227,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.58931766,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9940999746322632,"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"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9940999746322632,"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"}},{"id":"https://openalex.org/T10114","display_name":"Balance, Gait, and Falls Prevention","score":0.9797000288963318,"subfield":{"id":"https://openalex.org/subfields/3612","display_name":"Physical Therapy, Sports Therapy and Rehabilitation"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9735999703407288,"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/computer-science","display_name":"Computer science","score":0.6173892021179199},{"id":"https://openalex.org/keywords/waist","display_name":"Waist","score":0.5807059407234192},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5227587223052979},{"id":"https://openalex.org/keywords/net","display_name":"Net (polyhedron)","score":0.4148778021335602},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4086528420448303},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.19213464856147766},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.10979035496711731},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.10676825046539307}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6173892021179199},{"id":"https://openalex.org/C2776193436","wikidata":"https://www.wikidata.org/wiki/Q236232","display_name":"Waist","level":3,"score":0.5807059407234192},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5227587223052979},{"id":"https://openalex.org/C14166107","wikidata":"https://www.wikidata.org/wiki/Q253829","display_name":"Net (polyhedron)","level":2,"score":0.4148778021335602},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4086528420448303},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.19213464856147766},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.10979035496711731},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.10676825046539307},{"id":"https://openalex.org/C511355011","wikidata":"https://www.wikidata.org/wiki/Q12174","display_name":"Obesity","level":2,"score":0.0},{"id":"https://openalex.org/C126322002","wikidata":"https://www.wikidata.org/wiki/Q11180","display_name":"Internal medicine","level":1,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.1109/ijcb57857.2023.10448641","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcb57857.2023.10448641","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE International Joint Conference on Biometrics (IJCB)","raw_type":"proceedings-article"},{"id":"pmh:oai:pure.atira.dk:publications/c0c5fc0c-9f69-4f09-bb98-b07781554e14","is_oa":false,"landing_page_url":"https://research.manchester.ac.uk/en/publications/c0c5fc0c-9f69-4f09-bb98-b07781554e14","pdf_url":null,"source":{"id":"https://openalex.org/S4306400662","display_name":"Research Explorer (The University of Manchester)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I28407311","host_organization_name":"University of Manchester","host_organization_lineage":["https://openalex.org/I28407311"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Zhao, R, Munteanu, A, Hu, P & Dai, X 2023, W2H-Net: Fast Prediction of Waist-to-Hip Ratio from Single Partial Dressed Body Scans in Arbitrary Postures via Deep Learning. in IEEE International Joint Conference on Biometrics (IJCB 2023). https://doi.org/10.1109/IJCB57857.2023.10448641","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:pure.atira.dk:publications/d24dcd6e-d6a8-4509-83c4-d8152733f5fc","is_oa":true,"landing_page_url":"https://pureportal.coventry.ac.uk/en/publications/w2hnet-fast-prediction-of-waisttohip-ratio-from-single-partial-dressed-body-scans-in-arbitrary-postures-via-deep-learning(d24dcd6e-d6a8-4509-83c4-d8152733f5fc).html","pdf_url":"https://pure.coventry.ac.uk/ws/files/82420239/Hu2024AAM.pdf","source":{"id":"https://openalex.org/S4306402411","display_name":"Pure (Coventry University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I73417466","host_organization_name":"Coventry University","host_organization_lineage":["https://openalex.org/I73417466"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Zhao, R, Dai, X, Hu, P & Munteanu, A 2024, W2H-Net : Fast Prediction of Waist-to-Hip Ratio from Single Partial Dressed Body Scans in Arbitrary Postures via Deep Learning. in 2023 IEEE International Joint Conference on Biometrics, IJCB 2023. 2023 IEEE International Joint Conference on Biometrics, IJCB 2023, IEEE, IEEE International Joint Conference on Biometrics , Ljubljana, Slovenia, 25/09/23. https://doi.org/10.1109/IJCB57857.2023.10448641","raw_type":"contributionToPeriodical"},{"id":"pmh:oai:pure.atira.dk:openaire/d24dcd6e-d6a8-4509-83c4-d8152733f5fc","is_oa":true,"landing_page_url":"https://pureportal.coventry.ac.uk/en/publications/d24dcd6e-d6a8-4509-83c4-d8152733f5fc","pdf_url":null,"source":{"id":"https://openalex.org/S4306402411","display_name":"Pure (Coventry University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I73417466","host_organization_name":"Coventry University","host_organization_lineage":["https://openalex.org/I73417466"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Zhao, R, Dai, X, Hu, P & Munteanu, A 2024, W2H-Net : Fast Prediction of Waist-to-Hip Ratio from Single Partial Dressed Body Scans in Arbitrary Postures via Deep Learning. in 2023 IEEE International Joint Conference on Biometrics, IJCB 2023. 2023 IEEE International Joint Conference on Biometrics, IJCB 2023, IEEE, IEEE International Joint Conference on Biometrics , Ljubljana, Slovenia, 25/09/23. https://doi.org/10.1109/IJCB57857.2023.10448641","raw_type":"contributionToPeriodical"},{"id":"pmh:oai:vubissmart:VUBISSMART:2000:171377","is_oa":false,"landing_page_url":"https://biblio.vub.ac.be/vubir/w2hnet-fast-prediction-of-waisttohip-ratio-from-single-partial-dressed-body-scans-in-arbitrary-postures-via-deep-learning(7d477963-ca06-4381-95da-f7461def7ab5).html","pdf_url":null,"source":{"id":"https://openalex.org/S4306402573","display_name":"VUBIR (Vrije Universiteit Brussel)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I13469542","host_organization_name":"Vrije Universiteit Brussel","host_organization_lineage":["https://openalex.org/I13469542"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},{"id":"pmh:oai:vubissmart:VUBISSMART:2000:187588","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306402573","display_name":"VUBIR (Vrije Universiteit Brussel)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I13469542","host_organization_name":"Vrije Universiteit Brussel","host_organization_lineage":["https://openalex.org/I13469542"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:pure.atira.dk:publications/d24dcd6e-d6a8-4509-83c4-d8152733f5fc","is_oa":true,"landing_page_url":"https://pureportal.coventry.ac.uk/en/publications/w2hnet-fast-prediction-of-waisttohip-ratio-from-single-partial-dressed-body-scans-in-arbitrary-postures-via-deep-learning(d24dcd6e-d6a8-4509-83c4-d8152733f5fc).html","pdf_url":"https://pure.coventry.ac.uk/ws/files/82420239/Hu2024AAM.pdf","source":{"id":"https://openalex.org/S4306402411","display_name":"Pure (Coventry University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I73417466","host_organization_name":"Coventry University","host_organization_lineage":["https://openalex.org/I73417466"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Zhao, R, Dai, X, Hu, P & Munteanu, A 2024, W2H-Net : Fast Prediction of Waist-to-Hip Ratio from Single Partial Dressed Body Scans in Arbitrary Postures via Deep Learning. in 2023 IEEE International Joint Conference on Biometrics, IJCB 2023. 2023 IEEE International Joint Conference on Biometrics, IJCB 2023, IEEE, IEEE International Joint Conference on Biometrics , Ljubljana, Slovenia, 25/09/23. https://doi.org/10.1109/IJCB57857.2023.10448641","raw_type":"contributionToPeriodical"},"sustainable_development_goals":[{"score":0.6800000071525574,"id":"https://metadata.un.org/sdg/5","display_name":"Gender equality"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4392411865.pdf","grobid_xml":"https://content.openalex.org/works/W4392411865.grobid-xml"},"referenced_works_count":28,"referenced_works":["https://openalex.org/W126840538","https://openalex.org/W1522301498","https://openalex.org/W1967554269","https://openalex.org/W1977954308","https://openalex.org/W1979595233","https://openalex.org/W2134326473","https://openalex.org/W2169014193","https://openalex.org/W2534079481","https://openalex.org/W2593522046","https://openalex.org/W2883758202","https://openalex.org/W2886499109","https://openalex.org/W2894052262","https://openalex.org/W2952831099","https://openalex.org/W3049667295","https://openalex.org/W3101022589","https://openalex.org/W3169990849","https://openalex.org/W3195658191","https://openalex.org/W3206431030","https://openalex.org/W4205841096","https://openalex.org/W4221002448","https://openalex.org/W4245383502","https://openalex.org/W4311786169","https://openalex.org/W4321022107","https://openalex.org/W4322577112","https://openalex.org/W4361224121","https://openalex.org/W4367557492","https://openalex.org/W4382047121","https://openalex.org/W6631190155"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"The":[0,22],"Waist-to-Hip":[1],"Ratio":[2],"(WHR)":[3],"is":[4,116],"an":[5],"important":[6],"indicator":[7],"for":[8,25,187],"health":[9,189],"risk":[10],"prediction,":[11],"body":[12,15,111,147],"fat":[13],"distribution,":[14],"shape":[16],"analysis,":[17],"and":[18,40,53,79,99,176],"physical":[19],"fitness":[20],"analysis.":[21],"conventional":[23],"approach":[24],"obtaining":[26],"the":[27,38,56,60,70,76,82,126,131,140,200,203],"WHR":[28,63,141,182],"entails":[29],"manual":[30],"measurement,":[31],"which":[32,115,184],"necessitates":[33],"experienced":[34],"anthropometrists":[35],"to":[36,69,103,125,138,159,179],"measure":[37],"waist":[39],"hip":[41],"circumferences":[42],"of":[43,128,202],"a":[44,50,154,173],"subject":[45],"wearing":[46],"tight":[47],"clothing":[48],"in":[49,95,149],"predetermined":[51],"posture,":[52],"subsequently":[54],"calculate":[55],"ratio":[57],"based":[58],"on":[59,166],"acquired":[61],"measurements.":[62],"errors":[64],"may":[65],"be":[66],"accumulated":[67],"due":[68],"anthropometrist\u2019s":[71],"subjectivity,":[72],"as":[73,75,113],"well":[74],"person\u2019s":[77],"pose":[78],"attire":[80],"during":[81],"measurement":[83,101],"process.":[84],"Non-contact":[85],"anthropometric":[86],"measurements":[87],"using":[88],"3D":[89],"scanning":[90],"technology":[91],"have":[92],"shown":[93],"promise":[94],"providing":[96],"higher":[97],"accuracy":[98,162],"faster":[100],"compared":[102],"traditional":[104],"methods.":[105],"However,":[106],"they":[107],"require":[108,169],"complete":[109],"undressed":[110],"scans":[112,148],"input,":[114],"not":[117],"always":[118],"available.":[119],"In":[120],"this":[121],"paper,":[122],"we":[123],"proposed,":[124],"best":[127],"our":[129],"knowledge,":[130],"first":[132],"deep":[133],"learning-based":[134],"algorithm,":[135],"dubbed":[136],"W2H-Net,":[137],"predict":[139],"directly":[142],"from":[143],"single":[144],"partial":[145],"dressed":[146],"arbitrary":[150],"postures.":[151],"W2H-Net":[152,171],"introduces":[153],"novel":[155],"framework":[156],"called":[157],"Focus-Net":[158],"improve":[160],"learning":[161],"by":[163],"selectively":[164],"focusing":[165],"parts":[167],"that":[168],"attention.":[170],"provides":[172],"flexible,":[174],"cost-effective,":[175],"privacy-preserving":[177],"way":[178],"obtain":[180],"accurate":[181],"measurements,":[183],"are":[185],"crucial":[186],"predicting":[188],"risks":[190],"associated":[191],"with":[192],"central":[193],"obesity.":[194],"Extensive":[195],"experimental":[196],"results":[197],"can":[198],"demonstrate":[199],"superiority":[201],"proposed":[204],"method.":[205]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
