{"id":"https://openalex.org/W3195658191","doi":"https://doi.org/10.1109/tim.2021.3106126","title":"Deep Learning-Based Automated Extraction of Anthropometric Measurements From a Single 3-D Scan","display_name":"Deep Learning-Based Automated Extraction of Anthropometric Measurements From a Single 3-D Scan","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3195658191","doi":"https://doi.org/10.1109/tim.2021.3106126","mag":"3195658191"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2021.3106126","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2021.3106126","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","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/A5028609470","display_name":"Nastaran Nourbakhsh Kaashki","orcid":"https://orcid.org/0000-0001-8317-4994"},"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":"Nastaran Nourbakhsh Kaashki","raw_affiliation_strings":["Department of Electronics and Informatics,Vrije Universiteit Brussel, Brussels, Belgium"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Informatics,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/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":"Pengpeng Hu","raw_affiliation_strings":["Department of Electronics and Informatics,Vrije Universiteit Brussel, Brussels, Belgium. (e-mail: phu@etrovub.be)"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Informatics,Vrije Universiteit Brussel, Brussels, Belgium. (e-mail: phu@etrovub.be)","institution_ids":["https://openalex.org/I13469542"]}]},{"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":["Department of Electronics and Informatics,Vrije Universiteit Brussel, Brussels, Belgium"],"affiliations":[{"raw_affiliation_string":"Department of Electronics and Informatics,Vrije Universiteit Brussel, Brussels, Belgium","institution_ids":["https://openalex.org/I13469542"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5028609470"],"corresponding_institution_ids":["https://openalex.org/I13469542"],"apc_list":null,"apc_paid":null,"fwci":3.5575,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.93589459,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"70","issue":null,"first_page":"1","last_page":"14"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9994999766349792,"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":0.9994999766349792,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9825999736785889,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9749000072479248,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7893368005752563},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7458404302597046},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6179382801055908},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5213392972946167},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5211403369903564},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5027503967285156},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49866271018981934},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.48714062571525574},{"id":"https://openalex.org/keywords/scanner","display_name":"Scanner","score":0.46394893527030945},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.15780127048492432}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7893368005752563},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7458404302597046},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6179382801055908},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5213392972946167},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5211403369903564},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5027503967285156},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49866271018981934},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.48714062571525574},{"id":"https://openalex.org/C2779751349","wikidata":"https://www.wikidata.org/wiki/Q1474480","display_name":"Scanner","level":2,"score":0.46394893527030945},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.15780127048492432}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tim.2021.3106126","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2021.3106126","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"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 Instrumentation and Measurement","raw_type":"journal-article"},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/04b1b1c7-4568-4fb9-957b-2a994a12ff70","is_oa":false,"landing_page_url":"https://research.manchester.ac.uk/en/publications/04b1b1c7-4568-4fb9-957b-2a994a12ff70","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":"Kaashki, N N, Hu, P & Munteanu, A 2021, 'Deep Learning-Based Automated Extraction of Anthropometric Measurements from a Single 3D Scan', IEEE Transactions on Instrumentation and Measurement. https://doi.org/10.1109/TIM.2021.3106126","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:vubissmart:VUBISSMART:2000:152363","is_oa":false,"landing_page_url":"https://biblio.vub.ac.be/vubir/deep-learningbased-automated-extraction-of-anthropometric-measurements-from-a-single-3d-scan(6e85c5ea-2e56-4a5c-84e0-a073f0ff30fe).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:2000:207754","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":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4726753931","display_name":null,"funder_award_id":"G084117","funder_id":"https://openalex.org/F4320321730","funder_display_name":"Fonds Wetenschappelijk Onderzoek"}],"funders":[{"id":"https://openalex.org/F4320321730","display_name":"Fonds Wetenschappelijk Onderzoek","ror":"https://ror.org/03qtxy027"},{"id":"https://openalex.org/F4320322852","display_name":"Innoviris","ror":"https://ror.org/04af9zr29"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1594957066","https://openalex.org/W1920022804","https://openalex.org/W1923752253","https://openalex.org/W1967554269","https://openalex.org/W1990078388","https://openalex.org/W2002071766","https://openalex.org/W2007206727","https://openalex.org/W2011797001","https://openalex.org/W2025299767","https://openalex.org/W2027451432","https://openalex.org/W2063085086","https://openalex.org/W2067724039","https://openalex.org/W2083624955","https://openalex.org/W2091085232","https://openalex.org/W2097563957","https://openalex.org/W2119539052","https://openalex.org/W2134236847","https://openalex.org/W2137044594","https://openalex.org/W2168722300","https://openalex.org/W2169014193","https://openalex.org/W2210786185","https://openalex.org/W2327037637","https://openalex.org/W2411407426","https://openalex.org/W2518108298","https://openalex.org/W2558748708","https://openalex.org/W2560609797","https://openalex.org/W2576289912","https://openalex.org/W2603429625","https://openalex.org/W2609798133","https://openalex.org/W2753170255","https://openalex.org/W2774220748","https://openalex.org/W2800698956","https://openalex.org/W2804055080","https://openalex.org/W2883758202","https://openalex.org/W2885213688","https://openalex.org/W2902035653","https://openalex.org/W2909578416","https://openalex.org/W2946759175","https://openalex.org/W2963121255","https://openalex.org/W2963263347","https://openalex.org/W2964121744","https://openalex.org/W2964253930","https://openalex.org/W2968418133","https://openalex.org/W2979750740","https://openalex.org/W2980382063","https://openalex.org/W3002625094","https://openalex.org/W3013687892","https://openalex.org/W3045066578","https://openalex.org/W3049667295","https://openalex.org/W3091620196","https://openalex.org/W3120769869","https://openalex.org/W3158686964","https://openalex.org/W4231947885","https://openalex.org/W6631190155","https://openalex.org/W6635797942","https://openalex.org/W6640300118","https://openalex.org/W6726497184","https://openalex.org/W6739778489","https://openalex.org/W6747904511","https://openalex.org/W6770413209","https://openalex.org/W6789372728"],"related_works":["https://openalex.org/W4245233074","https://openalex.org/W4232857084","https://openalex.org/W1517555227","https://openalex.org/W762151464","https://openalex.org/W2389610024","https://openalex.org/W4239804034","https://openalex.org/W2911295078","https://openalex.org/W2167528937","https://openalex.org/W2653993779","https://openalex.org/W2001485867"],"abstract_inverted_index":{"The":[0,80,101,206],"appearance":[1],"of":[2,20,36,182],"3D":[3,67],"scanners,":[4],"generating":[5],"point":[6,162,183],"clouds,":[7],"has":[8,103],"revolutionized":[9],"anthropometric":[10,41,48],"data":[11,18],"collection":[12],"systems":[13],"and":[14,31,53,77,128,224,234,247,260],"its":[15],"applications.":[16],"Anthropometric":[17,142],"is":[19,82,90,120,155],"paramount":[21],"importance":[22],"in":[23,73,95],"several":[24],"applications,":[25],"including":[26],"fashion":[27],"design,":[28],"medical":[29],"diagnosis":[30],"virtual":[32],"character":[33],"modelling,":[34],"all":[35],"which":[37,89,119,194],"require":[38],"an":[39,107,191,237],"fully-automatic":[40],"measurement":[42,49,207],"extraction":[43,50,144],"method.":[44],"3D-based":[45],"methods":[46,68],"for":[47,139,177],"become":[51],"more":[52,54],"popular":[55],"due":[56],"to":[57,62,93,104,110,115,126,157,189,196,201,264],"their":[58],"improved":[59],"accuracy":[60],"compared":[61],"classical":[63],"image-based":[64],"approaches.":[65],"Existing":[66],"can":[69,169],"be":[70,170],"mainly":[71],"classified":[72],"two":[74],"categories:":[75],"landmark":[76],"template-based":[78],"methods.":[79],"former":[81],"highly":[83,91],"dependent":[84],"on":[85,146,212,242,248],"the":[86,96,117,136,213,219,243,249,254],"estimated":[87],"landmarks":[88],"sensitive":[92,125],"noise":[94,127],"input":[97],"or":[98],"missing":[99,129],"data.":[100,130],"latter":[102],"iteratively":[105],"solve":[106],"objective":[108],"function":[109],"deform":[111,197],"a":[112,198,203,231,265],"body":[113],"template":[114,199,215],"fit":[116,202],"scan,":[118],"time-consuming":[121],"while":[122],"being":[123],"also":[124],"In":[131],"this":[132,187],"study,":[133],"we":[134],"propose":[135],"first":[137],"approach":[138],"automatic":[140],"contact-less":[141],"Measurements":[143],"based":[145],"Deep-Learning":[147],"(AM-DL).":[148],"A":[149],"novel":[150],"module":[151,188],"dubbed":[152],"Multi-scale":[153,167],"EdgeConv":[154,168],"proposed":[156,220,255],"learn":[158],"local":[159],"features":[160],"from":[161],"clouds":[163],"at":[164],"multiple":[165],"scales.":[166],"directly":[171],"integrated":[172],"with":[173],"other":[174],"neural":[175],"networks":[176],"various":[178],"tasks,":[179],"e.g.,":[180],"classification":[181],"clouds.":[184],"We":[185],"exploit":[186],"design":[190],"encoder-decoder":[192],"architecture":[193],"learns":[195],"model":[200],"given":[204],"scan.":[205],"values":[208],"are":[209],"then":[210],"calculated":[211],"deformed":[214],"model.":[216],"To":[217],"evaluate":[218],"method,":[221],"27":[222],"female":[223],"25":[225],"male":[226],"subjects":[227],"were":[228],"scanned":[229],"using":[230],"photogrametry-based":[232],"scanner":[233],"measured":[235],"by":[236],"experienced":[238],"tailor.":[239,267],"Experimental":[240],"results":[241],"synthetic":[244],"ModelNet40":[245],"dataset":[246],"real":[250],"scans":[251],"demonstrate":[252],"that":[253],"method":[256],"outperforms":[257],"state-of-the-art":[258],"methods,":[259],"performs":[261],"sufficiently":[262],"close":[263],"professional":[266]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":8}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}