{"id":"https://openalex.org/W3209691850","doi":"https://doi.org/10.1109/fg52635.2021.9666987","title":"From Face to Gait: Weakly-Supervised Learning of Gender Information from Walking Patterns","display_name":"From Face to Gait: Weakly-Supervised Learning of Gender Information from Walking Patterns","publication_year":2021,"publication_date":"2021-12-15","ids":{"openalex":"https://openalex.org/W3209691850","doi":"https://doi.org/10.1109/fg52635.2021.9666987","mag":"3209691850"},"language":"en","primary_location":{"id":"doi:10.1109/fg52635.2021.9666987","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg52635.2021.9666987","pdf_url":null,"source":{"id":"https://openalex.org/S4363608446","display_name":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","raw_type":"proceedings-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/A5061675137","display_name":"Andy C\u01cetrun\u01ce","orcid":"https://orcid.org/0000-0001-5324-0428"},"institutions":[{"id":"https://openalex.org/I61641377","display_name":"Universitatea Na\u021bional\u0103 de \u0218tiin\u021b\u0103 \u0219i Tehnologie Politehnica Bucure\u0219ti","ror":"https://ror.org/0558j5q12","country_code":"RO","type":"education","lineage":["https://openalex.org/I61641377"]}],"countries":["RO"],"is_corresponding":true,"raw_author_name":"Andy Catruna","raw_affiliation_strings":["University Politehnica of Bucharest"],"affiliations":[{"raw_affiliation_string":"University Politehnica of Bucharest","institution_ids":["https://openalex.org/I61641377"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070209606","display_name":"Adrian Cosma","orcid":"https://orcid.org/0000-0003-0307-2520"},"institutions":[{"id":"https://openalex.org/I61641377","display_name":"Universitatea Na\u021bional\u0103 de \u0218tiin\u021b\u0103 \u0219i Tehnologie Politehnica Bucure\u0219ti","ror":"https://ror.org/0558j5q12","country_code":"RO","type":"education","lineage":["https://openalex.org/I61641377"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Adrian Cosma","raw_affiliation_strings":["University Politehnica of Bucharest"],"affiliations":[{"raw_affiliation_string":"University Politehnica of Bucharest","institution_ids":["https://openalex.org/I61641377"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006093696","display_name":"Emilian R\u01cedoi","orcid":"https://orcid.org/0000-0002-1177-5288"},"institutions":[{"id":"https://openalex.org/I61641377","display_name":"Universitatea Na\u021bional\u0103 de \u0218tiin\u021b\u0103 \u0219i Tehnologie Politehnica Bucure\u0219ti","ror":"https://ror.org/0558j5q12","country_code":"RO","type":"education","lineage":["https://openalex.org/I61641377"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Ion Emilian Radoi","raw_affiliation_strings":["University Politehnica of Bucharest"],"affiliations":[{"raw_affiliation_string":"University Politehnica of Bucharest","institution_ids":["https://openalex.org/I61641377"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5061675137"],"corresponding_institution_ids":["https://openalex.org/I61641377"],"apc_list":null,"apc_paid":null,"fwci":2.3063,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.88903127,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"4","issue":null,"first_page":"1","last_page":"5"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9995999932289124,"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":0.9995999932289124,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9968000054359436,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9945999979972839,"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/leverage","display_name":"Leverage (statistics)","score":0.7493876814842224},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.726988673210144},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6951080560684204},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5993218421936035},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5445554256439209},{"id":"https://openalex.org/keywords/demographics","display_name":"Demographics","score":0.5004537105560303},{"id":"https://openalex.org/keywords/gait","display_name":"Gait","score":0.48635560274124146},{"id":"https://openalex.org/keywords/active-appearance-model","display_name":"Active appearance model","score":0.4590001106262207},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.4563089907169342},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.45470955967903137},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.44483983516693115},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1164461076259613},{"id":"https://openalex.org/keywords/physical-medicine-and-rehabilitation","display_name":"Physical medicine and rehabilitation","score":0.09214702248573303},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0780634880065918}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7493876814842224},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.726988673210144},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6951080560684204},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5993218421936035},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5445554256439209},{"id":"https://openalex.org/C2780084366","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demographics","level":2,"score":0.5004537105560303},{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.48635560274124146},{"id":"https://openalex.org/C83248878","wikidata":"https://www.wikidata.org/wiki/Q344000","display_name":"Active appearance model","level":3,"score":0.4590001106262207},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.4563089907169342},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.45470955967903137},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.44483983516693115},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1164461076259613},{"id":"https://openalex.org/C99508421","wikidata":"https://www.wikidata.org/wiki/Q2678675","display_name":"Physical medicine and rehabilitation","level":1,"score":0.09214702248573303},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0780634880065918},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","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/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/fg52635.2021.9666987","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg52635.2021.9666987","pdf_url":null,"source":{"id":"https://openalex.org/S4363608446","display_name":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.4000000059604645}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1514928307","https://openalex.org/W1522301498","https://openalex.org/W1821462560","https://openalex.org/W1998667615","https://openalex.org/W2018110376","https://openalex.org/W2045983032","https://openalex.org/W2104335344","https://openalex.org/W2126680226","https://openalex.org/W2194775991","https://openalex.org/W2341528187","https://openalex.org/W2510725918","https://openalex.org/W2565447158","https://openalex.org/W2592232824","https://openalex.org/W2739195814","https://openalex.org/W2762538733","https://openalex.org/W2777027507","https://openalex.org/W2782782072","https://openalex.org/W2797382244","https://openalex.org/W2902407103","https://openalex.org/W2903787679","https://openalex.org/W2907332482","https://openalex.org/W2920830204","https://openalex.org/W2946948417","https://openalex.org/W2949650786","https://openalex.org/W2950134147","https://openalex.org/W2955425717","https://openalex.org/W2962954622","https://openalex.org/W2963266717","https://openalex.org/W2963854019","https://openalex.org/W2967013449","https://openalex.org/W2967052791","https://openalex.org/W2998229299","https://openalex.org/W3000959322","https://openalex.org/W3012974261","https://openalex.org/W3099325804","https://openalex.org/W3101998545","https://openalex.org/W3120764656","https://openalex.org/W3123386074","https://openalex.org/W3156263601","https://openalex.org/W3157911070","https://openalex.org/W3160348986","https://openalex.org/W3172770836","https://openalex.org/W4226055600","https://openalex.org/W6631190155","https://openalex.org/W6638523607","https://openalex.org/W6675575696","https://openalex.org/W6687483927","https://openalex.org/W6756215566","https://openalex.org/W6757093742","https://openalex.org/W6762718338","https://openalex.org/W6766710928"],"related_works":["https://openalex.org/W3121380072","https://openalex.org/W2058403539","https://openalex.org/W2942793592","https://openalex.org/W2602311653","https://openalex.org/W2333615638","https://openalex.org/W2964230772","https://openalex.org/W2768231286","https://openalex.org/W2409976527","https://openalex.org/W626576356","https://openalex.org/W4379251913"],"abstract_inverted_index":{"Obtaining":[0],"demographics":[1],"information":[2,71],"from":[3,57],"video":[4],"is":[5,39,51,137],"valuable":[6],"for":[7,19,68],"a":[8,65],"range":[9],"of":[10,72,78,83,122],"real-world":[11,34],"applications.":[12],"While":[13],"approaches":[14],"that":[15],"leverage":[16],"facial":[17,86,115,135],"features":[18],"gender":[20,70],"inference":[21],"are":[22],"very":[23],"successful":[24],"in":[25,32,133],"restrained":[26],"environments,":[27],"they":[28],"do":[29],"not":[30,40,52,142],"work":[31],"most":[33],"scenarios":[35,132],"when":[36],"the":[37,42,45,49,58,126,144,148],"subject":[38],"facing":[41,143],"camera,":[43],"has":[44],"face":[46,50,149],"obstructed":[47],"or":[48,60,111,146],"clear":[53],"due":[54,139],"to":[55,89,98,128,131,140],"distance":[56],"camera":[59,145],"poor":[61],"resolution.":[62],"We":[63,80],"propose":[64],"weakly-supervised":[66],"method":[67],"learning":[69],"people":[73],"based":[74],"on":[75,109],"their":[76],"manner":[77],"walking.":[79],"make":[81],"use":[82],"state-of-the":[84],"art":[85],"analysis":[87,116,136],"models":[88,117],"automatically":[90],"annotate":[91],"front-":[92],"view":[93],"walking":[94],"sequences":[95],"and":[96,125],"generalise":[97,130],"unseen":[99],"angles":[100],"by":[101],"leveraging":[102],"gait-based":[103],"label":[104],"propagation.":[105],"Our":[106],"results":[107],"show":[108],"par":[110],"higher":[112],"performance":[113],"with":[114,118],"an":[119],"F1":[120],"score":[121],"91":[123],"%":[124],"ability":[127],"successfully":[129],"which":[134],"unfeasible":[138],"subjects":[141],"having":[147],"obstructed.":[150]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
