{"id":"https://openalex.org/W2561834749","doi":"https://doi.org/10.1109/btas.2016.7791184","title":"Long-term people reidentification using anthropometric signature","display_name":"Long-term people reidentification using anthropometric signature","publication_year":2016,"publication_date":"2016-09-01","ids":{"openalex":"https://openalex.org/W2561834749","doi":"https://doi.org/10.1109/btas.2016.7791184","mag":"2561834749"},"language":"en","primary_location":{"id":"doi:10.1109/btas.2016.7791184","is_oa":false,"landing_page_url":"https://doi.org/10.1109/btas.2016.7791184","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5006323738","display_name":"Mohamed Hasan","orcid":"https://orcid.org/0000-0002-7477-7133"},"institutions":[{"id":"https://openalex.org/I207547235","display_name":"Benha University","ror":"https://ror.org/03tn5ee41","country_code":"EG","type":"education","lineage":["https://openalex.org/I207547235"]},{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["EG","JP"],"is_corresponding":false,"raw_author_name":"Mohamed Hasan","raw_affiliation_strings":["Osaka University - Japan, Benha University- Egypt"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Osaka University - Japan, Benha University- Egypt","institution_ids":["https://openalex.org/I207547235","https://openalex.org/I98285908"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008868094","display_name":"Noborou Babaguchi","orcid":null},"institutions":[{"id":"https://openalex.org/I98285908","display_name":"The University of Osaka","ror":"https://ror.org/035t8zc32","country_code":"JP","type":"education","lineage":["https://openalex.org/I98285908"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Noborou Babaguchi","raw_affiliation_strings":["Osaka University Osaka - Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Osaka University Osaka - Japan","institution_ids":["https://openalex.org/I98285908"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.0978,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.76221668,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/T11448","display_name":"Face recognition and analysis","score":0.9958999752998352,"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":0.9951000213623047,"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/biometrics","display_name":"Biometrics","score":0.8444030284881592},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.6545698642730713},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6525270938873291},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6238154172897339},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5986868739128113},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5940472483634949},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5692557096481323},{"id":"https://openalex.org/keywords/signature","display_name":"Signature (topology)","score":0.4887568950653076},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.47859832644462585},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4622350335121155},{"id":"https://openalex.org/keywords/feature-selection","display_name":"Feature selection","score":0.4605599343776703},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44994276762008667},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.4343957006931305},{"id":"https://openalex.org/keywords/anthropometry","display_name":"Anthropometry","score":0.42884647846221924},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36724990606307983},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3557926118373871},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2754667103290558},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.11865726113319397},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.09148991107940674}],"concepts":[{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.8444030284881592},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.6545698642730713},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6525270938873291},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6238154172897339},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5986868739128113},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5940472483634949},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5692557096481323},{"id":"https://openalex.org/C2779696439","wikidata":"https://www.wikidata.org/wiki/Q7512811","display_name":"Signature (topology)","level":2,"score":0.4887568950653076},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.47859832644462585},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4622350335121155},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.4605599343776703},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44994276762008667},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.4343957006931305},{"id":"https://openalex.org/C61427482","wikidata":"https://www.wikidata.org/wiki/Q6656244","display_name":"Anthropometry","level":2,"score":0.42884647846221924},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36724990606307983},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3557926118373871},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2754667103290558},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.11865726113319397},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.09148991107940674},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/btas.2016.7791184","is_oa":false,"landing_page_url":"https://doi.org/10.1109/btas.2016.7791184","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE 8th International Conference on Biometrics Theory, Applications and Systems (BTAS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W90353859","https://openalex.org/W138224622","https://openalex.org/W1480376833","https://openalex.org/W1505602316","https://openalex.org/W1545140005","https://openalex.org/W1557470315","https://openalex.org/W1580948147","https://openalex.org/W1594368566","https://openalex.org/W1808603090","https://openalex.org/W1979820753","https://openalex.org/W1980506481","https://openalex.org/W1981119104","https://openalex.org/W1988790447","https://openalex.org/W2005220741","https://openalex.org/W2042436258","https://openalex.org/W2046434485","https://openalex.org/W2095212070","https://openalex.org/W2100028243","https://openalex.org/W2104311988","https://openalex.org/W2114147878","https://openalex.org/W2114976918","https://openalex.org/W2129846893","https://openalex.org/W2154499867","https://openalex.org/W2164598857","https://openalex.org/W2166530187","https://openalex.org/W2167292325","https://openalex.org/W2293946304","https://openalex.org/W2911964244","https://openalex.org/W3014865320","https://openalex.org/W4285719527","https://openalex.org/W6603697666","https://openalex.org/W6633495413","https://openalex.org/W6635569327","https://openalex.org/W6675261842","https://openalex.org/W6677275180","https://openalex.org/W6696884280"],"related_works":["https://openalex.org/W2076845124","https://openalex.org/W2183964146","https://openalex.org/W2062586268","https://openalex.org/W2379932303","https://openalex.org/W4300873085","https://openalex.org/W2019582947","https://openalex.org/W3147744369","https://openalex.org/W3212688212","https://openalex.org/W1524372968","https://openalex.org/W4241440711"],"abstract_inverted_index":{"Anthropometric":[0],"biometrics":[1,22],"are":[2],"the":[3,20,60,87,103,108,137,146],"most":[4],"suitable":[5],"features":[6],"for":[7],"long-term":[8],"people":[9,31],"reidentification.":[10],"However,":[11],"feature":[12,35],"selection":[13],"is":[14,53,73,84,98,123],"still":[15],"a":[16,39,46,49],"major":[17],"problem":[18],"in":[19],"anthropometric":[21,51],"literature.":[23],"In":[24],"this":[25],"paper,":[26],"we":[27],"aim":[28],"at":[29,67],"improving":[30],"reidentification":[32],"by":[33,75,86],"enhancing":[34],"selection.":[36],"Based":[37],"on":[38,45,125],"statistical":[40],"analysis":[41],"of":[42,64,139,145],"body":[43,66,93,105,113],"measurements":[44],"large-scale":[47],"dataset,":[48],"new":[50],"signature":[52,57],"introduced.":[54],"The":[55,120],"proposed":[56,99],"describes":[58],"both":[59],"size":[61,72],"and":[62,117,131],"shape":[63,83],"human":[65],"specific":[68],"anatomical":[69],"landmarks.":[70],"While":[71],"measured":[74],"Euclidian":[76],"distance":[77,89],"between":[78],"four":[79,91],"skeleton":[80],"joint":[81],"pairs,":[82],"described":[85],"surface":[88],"along":[90],"circular":[92,104],"parts.":[94],"A":[95],"novel":[96],"algorithm":[97],"to":[100,143],"automatically":[101],"segment":[102],"parts":[106],"from":[107],"subject":[109],"point":[110],"cloud":[111],"using":[112,129],"geometry,":[114],"cylindrical":[115],"fitting":[116],"soft":[118],"clustering.":[119],"overall":[121],"system":[122],"evaluated":[124],"two":[126],"public":[127],"datasets":[128],"CMC":[130],"nAUC":[132],"metrics.":[133],"Experimental":[134],"results":[135],"show":[136],"effectiveness":[138],"our":[140],"method":[141],"compared":[142],"state":[144],"art.":[147]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
