{"id":"https://openalex.org/W3010807655","doi":"https://doi.org/10.1109/apsipaasc47483.2019.9023188","title":"An RGB Gait Anonymization Model for Low-Quality Silhouettes","display_name":"An RGB Gait Anonymization Model for Low-Quality Silhouettes","publication_year":2019,"publication_date":"2019-11-01","ids":{"openalex":"https://openalex.org/W3010807655","doi":"https://doi.org/10.1109/apsipaasc47483.2019.9023188","mag":"3010807655"},"language":"en","primary_location":{"id":"doi:10.1109/apsipaasc47483.2019.9023188","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc47483.2019.9023188","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","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/A5061227505","display_name":"Ngoc-Dung T. Tieu","orcid":null},"institutions":[{"id":"https://openalex.org/I200475212","display_name":"The Graduate University for Advanced Studies, SOKENDAI","ror":"https://ror.org/0516ah480","country_code":"JP","type":"education","lineage":["https://openalex.org/I200475212"]},{"id":"https://openalex.org/I4210110163","display_name":"Nippon Soken (Japan)","ror":"https://ror.org/01yk36x23","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210110163"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Ngoc-Dung T. Tieu","raw_affiliation_strings":["SOKENDAI, Kanagawa, Japan"],"affiliations":[{"raw_affiliation_string":"SOKENDAI, Kanagawa, Japan","institution_ids":["https://openalex.org/I4210110163","https://openalex.org/I200475212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101654553","display_name":"Huy H. Nguyen","orcid":"https://orcid.org/0000-0002-2000-7977"},"institutions":[{"id":"https://openalex.org/I200475212","display_name":"The Graduate University for Advanced Studies, SOKENDAI","ror":"https://ror.org/0516ah480","country_code":"JP","type":"education","lineage":["https://openalex.org/I200475212"]},{"id":"https://openalex.org/I4210110163","display_name":"Nippon Soken (Japan)","ror":"https://ror.org/01yk36x23","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210110163"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Huy H. Nguyen","raw_affiliation_strings":["SOKENDAI, Kanagawa, Japan"],"affiliations":[{"raw_affiliation_string":"SOKENDAI, Kanagawa, Japan","institution_ids":["https://openalex.org/I4210110163","https://openalex.org/I200475212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012466506","display_name":"Fuming Fang","orcid":"https://orcid.org/0000-0002-9332-3735"},"institutions":[{"id":"https://openalex.org/I184597095","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I184597095","https://openalex.org/I4210158934"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Fuming Fang","raw_affiliation_strings":["National Institute of Informatics, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"National Institute of Informatics, Tokyo, Japan","institution_ids":["https://openalex.org/I184597095"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007639385","display_name":"Junichi Yamagishi","orcid":"https://orcid.org/0000-0003-2752-3955"},"institutions":[{"id":"https://openalex.org/I184597095","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I184597095","https://openalex.org/I4210158934"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Junichi Yamagishi","raw_affiliation_strings":["National Institute of Informatics, Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"National Institute of Informatics, Tokyo, Japan","institution_ids":["https://openalex.org/I184597095"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044556342","display_name":"Isao Echizen","orcid":"https://orcid.org/0000-0003-4908-1860"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Isao Echizen","raw_affiliation_strings":["The University of Tokyo, Japan"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5061227505"],"corresponding_institution_ids":["https://openalex.org/I200475212","https://openalex.org/I4210110163"],"apc_list":null,"apc_paid":null,"fwci":0.5869,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.66072744,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1686","last_page":"1693"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9962000250816345,"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/T11309","display_name":"Music and Audio Processing","score":0.9692999720573425,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/silhouette","display_name":"Silhouette","score":0.9602695107460022},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7473651766777039},{"id":"https://openalex.org/keywords/gait","display_name":"Gait","score":0.6953144073486328},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6274940967559814},{"id":"https://openalex.org/keywords/naturalness","display_name":"Naturalness","score":0.6233063340187073},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6211594343185425},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.588927686214447},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3276042342185974},{"id":"https://openalex.org/keywords/physical-medicine-and-rehabilitation","display_name":"Physical medicine and rehabilitation","score":0.07405450940132141}],"concepts":[{"id":"https://openalex.org/C58103923","wikidata":"https://www.wikidata.org/wiki/Q2286025","display_name":"Silhouette","level":2,"score":0.9602695107460022},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7473651766777039},{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.6953144073486328},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6274940967559814},{"id":"https://openalex.org/C134537474","wikidata":"https://www.wikidata.org/wiki/Q17144832","display_name":"Naturalness","level":2,"score":0.6233063340187073},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6211594343185425},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.588927686214447},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3276042342185974},{"id":"https://openalex.org/C99508421","wikidata":"https://www.wikidata.org/wiki/Q2678675","display_name":"Physical medicine and rehabilitation","level":1,"score":0.07405450940132141},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"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/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/apsipaasc47483.2019.9023188","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipaasc47483.2019.9023188","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life below water","score":0.44999998807907104,"id":"https://metadata.un.org/sdg/14"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1548605257","https://openalex.org/W2038176251","https://openalex.org/W2049579184","https://openalex.org/W2104335344","https://openalex.org/W2121147465","https://openalex.org/W2126680226","https://openalex.org/W2322772590","https://openalex.org/W2331128040","https://openalex.org/W2469134594","https://openalex.org/W2475287302","https://openalex.org/W2519536754","https://openalex.org/W2557414982","https://openalex.org/W2621350877","https://openalex.org/W2725422033","https://openalex.org/W2769810959","https://openalex.org/W2787766454","https://openalex.org/W2892341857","https://openalex.org/W2896515397","https://openalex.org/W2939752039","https://openalex.org/W2949099979","https://openalex.org/W2962960341","https://openalex.org/W2963037989","https://openalex.org/W2963470893","https://openalex.org/W2963684088","https://openalex.org/W2964203186","https://openalex.org/W4294619240","https://openalex.org/W4320013936","https://openalex.org/W6675575696","https://openalex.org/W6702130928","https://openalex.org/W6726983635","https://openalex.org/W6739139180"],"related_works":["https://openalex.org/W2029561777","https://openalex.org/W1622964048","https://openalex.org/W30315714","https://openalex.org/W172797710","https://openalex.org/W120096811","https://openalex.org/W2945912943","https://openalex.org/W4254098118","https://openalex.org/W2124490647","https://openalex.org/W2923160319","https://openalex.org/W2587763979"],"abstract_inverted_index":{"Gait":[0],"anonymization":[1,47],"while":[2,185],"maintaining":[3,186],"naturalness":[4,177],"is":[5,23,84],"used":[6,85],"for":[7,38,49,60],"protecting":[8],"a":[9,17,78,95,109,115],"person's":[10],"identity":[11],"against":[12],"gait":[13,34,46,90,137],"recognition":[14],"systems":[15],"when":[16],"video":[18],"of":[19,127,166,173],"the":[20,62,88,136,149,153,159,164,167],"person":[21],"walking":[22],"uploaded":[24],"to":[25,86,93,122,132],"social":[26],"media.":[27],"There":[28],"has":[29],"been":[30],"some":[31],"research":[32],"on":[33,101,134],"anonymization,":[35],"but":[36],"only":[37],"high-quality":[39,102,110],"silhouette":[40,51,103,112,117,124,155],"gaits.":[41],"We":[42],"present":[43],"an":[44],"RGB":[45],"model":[48,70,181],"low-quality":[50,116],"gaits":[52,59,129,184],"that":[53,179],"can":[54,107,182],"generate":[55,108],"natural,":[56],"seamless":[57],"anonymized":[58,111,154],"which":[61,147],"original":[63,89,168],"silhouettes":[64],"cannot":[65],"be":[66],"extracted":[67],"correctly.":[68],"Our":[69],"includes":[71],"two":[72],"main":[73,145],"networks.":[74],"The":[75,143],"first":[76,150,160],"one,":[77,151],"deep":[79],"convolutional":[80],"generative":[81],"adversarial":[82],"network,":[83,146],"anonymize":[87,183],"by":[91,158,162],"adding":[92],"it":[94,131],"random":[96],"noise":[97],"vector.":[98],"By":[99],"training":[100],"data,":[104],"this":[105],"network":[106,161],"sequence":[113,156],"from":[114],"one.":[118],"Restricting":[119],"its":[120],"input":[121],"binary":[123],"sequences":[125],"instead":[126],"color":[128,165],"forces":[130],"focus":[133],"anonymizing":[135],"rather":[138],"than":[139],"changing":[140],"body":[141],"color.":[142],"second":[144],"follows":[148],"colorizes":[152],"generated":[157],"using":[163],"gait.":[169],"Evaluation":[170],"in":[171],"terms":[172],"success":[174],"rate":[175],"and":[176],"demonstrated":[178],"our":[180],"naturalness.":[187]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
