{"id":"https://openalex.org/W4394994988","doi":"https://doi.org/10.1109/tvt.2024.3391834","title":"Attribute-Consistency Reversible Pedestrian De-Identification in Intelligent Transportation","display_name":"Attribute-Consistency Reversible Pedestrian De-Identification in Intelligent Transportation","publication_year":2024,"publication_date":"2024-04-22","ids":{"openalex":"https://openalex.org/W4394994988","doi":"https://doi.org/10.1109/tvt.2024.3391834"},"language":"en","primary_location":{"id":"doi:10.1109/tvt.2024.3391834","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2024.3391834","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","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/A5100800913","display_name":"Guiliang Feng","orcid":null},"institutions":[{"id":"https://openalex.org/I169071405","display_name":"Hebei North University","ror":"https://ror.org/03hqwnx39","country_code":"CN","type":"education","lineage":["https://openalex.org/I169071405"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guiliang Feng","raw_affiliation_strings":["School of Information Science and Engineering, Hebei North University, Zhangjiakou, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Hebei North University, Zhangjiakou, China","institution_ids":["https://openalex.org/I169071405"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5004354714","display_name":"Ting Yan","orcid":"https://orcid.org/0000-0002-8919-7131"},"institutions":[{"id":"https://openalex.org/I169071405","display_name":"Hebei North University","ror":"https://ror.org/03hqwnx39","country_code":"CN","type":"education","lineage":["https://openalex.org/I169071405"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ting Yan","raw_affiliation_strings":["School of Information Science and Engineering, Hebei North University, Zhangjiakou, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Hebei North University, Zhangjiakou, China","institution_ids":["https://openalex.org/I169071405"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5063439671","display_name":"Jingjing Yang","orcid":"https://orcid.org/0000-0003-2751-2930"},"institutions":[{"id":"https://openalex.org/I169071405","display_name":"Hebei North University","ror":"https://ror.org/03hqwnx39","country_code":"CN","type":"education","lineage":["https://openalex.org/I169071405"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingjing Yang","raw_affiliation_strings":["School of Information Science and Engineering, Hebei North University, Zhangjiakou, China"],"affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, Hebei North University, Zhangjiakou, China","institution_ids":["https://openalex.org/I169071405"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100800913"],"corresponding_institution_ids":["https://openalex.org/I169071405"],"apc_list":null,"apc_paid":null,"fwci":0.2782,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.52015029,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"74","issue":"2","first_page":"2187","last_page":"2197"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9679999947547913,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9679999947547913,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.6784288883209229},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5843742489814758},{"id":"https://openalex.org/keywords/intelligent-transportation-system","display_name":"Intelligent transportation system","score":0.5471763014793396},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.5192342400550842},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5085843801498413},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3443114459514618},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.31989938020706177},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.3072766363620758},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2563904821872711}],"concepts":[{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.6784288883209229},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5843742489814758},{"id":"https://openalex.org/C47796450","wikidata":"https://www.wikidata.org/wiki/Q508378","display_name":"Intelligent transportation system","level":2,"score":0.5471763014793396},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.5192342400550842},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5085843801498413},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3443114459514618},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.31989938020706177},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.3072766363620758},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2563904821872711},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tvt.2024.3391834","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvt.2024.3391834","pdf_url":null,"source":{"id":"https://openalex.org/S10936095","display_name":"IEEE Transactions on Vehicular Technology","issn_l":"0018-9545","issn":["0018-9545","1939-9359"],"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 Vehicular Technology","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G660474997","display_name":null,"funder_award_id":"F2021405001","funder_id":"https://openalex.org/F4320322163","funder_display_name":"Natural Science Foundation of Hebei Province"}],"funders":[{"id":"https://openalex.org/F4320322163","display_name":"Natural Science Foundation of Hebei Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1949591461","https://openalex.org/W1982925187","https://openalex.org/W1999478721","https://openalex.org/W2031489346","https://openalex.org/W2057047227","https://openalex.org/W2123175289","https://openalex.org/W2129305389","https://openalex.org/W2133665775","https://openalex.org/W2204750386","https://openalex.org/W2341680599","https://openalex.org/W2575032143","https://openalex.org/W2585635281","https://openalex.org/W2604463754","https://openalex.org/W2735777250","https://openalex.org/W2963073614","https://openalex.org/W2975612241","https://openalex.org/W2998792609","https://openalex.org/W2998989269","https://openalex.org/W3035574324","https://openalex.org/W3087801137","https://openalex.org/W3138898594","https://openalex.org/W3208592291","https://openalex.org/W3216279502","https://openalex.org/W4213277438","https://openalex.org/W4220798878","https://openalex.org/W4288055256","https://openalex.org/W4290993799","https://openalex.org/W4304092264","https://openalex.org/W4304099369","https://openalex.org/W4312242770","https://openalex.org/W4312429278","https://openalex.org/W4313013512","https://openalex.org/W4319300176","https://openalex.org/W4323065287","https://openalex.org/W4361801760","https://openalex.org/W4376272248","https://openalex.org/W4385800797","https://openalex.org/W4386453747","https://openalex.org/W4387587526","https://openalex.org/W4388336622","https://openalex.org/W4391021823","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6850255533"],"related_works":["https://openalex.org/W2392100589","https://openalex.org/W2512789322","https://openalex.org/W2101960027","https://openalex.org/W2197846993","https://openalex.org/W566791342","https://openalex.org/W3136214354","https://openalex.org/W3172487415","https://openalex.org/W608736979","https://openalex.org/W631954924","https://openalex.org/W2148933895"],"abstract_inverted_index":{"With":[0],"the":[1,10,74,87,106,148,213,244,279,282,287],"rise":[2],"of":[3,12,76,89,130,215,281,289],"video":[4],"monitoring":[5],"and":[6,15,46,92,122,142,168,195,266,273,292,319],"intelligent":[7,13,120,290,317],"applications":[8],"in":[9,175,286,316],"field":[11],"transportation":[14,121,291,318],"pedestrian":[16,39,47,77,123,139,144,155,179,188,201,228,293,320],"navigation,":[17],"concerns":[18],"over":[19],"privacy":[20,58,314],"protection":[21,315],"have":[22],"become":[23],"more":[24],"prominent.":[25],"One":[26],"such":[27,163],"application":[28],"is":[29,158,206,232],"person":[30,93,260],"re-identification,":[31],"which":[32],"utilizes":[33,192],"deep":[34],"learning":[35,151],"models":[36],"with":[37,250],"individual":[38],"images":[40,180,235],"to":[41,101,198,208,242],"enable":[42],"efficient":[43],"traffic":[44],"management":[45],"guidance.":[48],"While":[49],"this":[50,109,210],"technology":[51],"has":[52],"societal":[53],"benefits,":[54],"it":[55],"also":[56],"raises":[57],"concerns.":[59],"Current":[60],"de-identification":[61],"methods":[62],"use":[63],"image":[64,145,229],"processing":[65],"techniques":[66],"like":[67],"blurring":[68],"or":[69],"pixelation,":[70],"but":[71],"they":[72],"compromise":[73],"realism":[75],"attributes":[78,156,176],"crucial":[79],"for":[80,119,313],"identification.":[81],"Additionally,":[82],"previous":[83],"research":[84],"often":[85],"neglects":[86],"importance":[88],"identity":[90],"restoration":[91],"attributes,":[94],"as":[95,164],"law":[96],"enforcement":[97],"may":[98],"require":[99],"access":[100],"original":[102,245],"information.":[103,185,222],"To":[104,223],"achieve":[105,224],"above":[107],"goals,":[108],"paper":[110],"proposes":[111],"a":[112,153,226,239,310],"Attribute-Consistency":[113],"Reversible":[114],"Pedestrian":[115],"De-Identification":[116],"(ACRPD)":[117],"framework":[118,128],"navigation":[124,321],"scenarios.":[125,252],"The":[126,186,295],"ACRPD":[127,284,299],"consists":[129],"three":[131],"main":[132],"processes,":[133],"including":[134],"attribute-level":[135,149],"contrastive":[136,150],"learning,":[137],"cross-view":[138,187,196],"anonymization":[140,189],"generation,":[141],"raw":[143,227,246],"recovery.":[146],"In":[147],"process,":[152],"pairwise":[154],"predictor":[157,172],"trained":[159],"using":[160],"attribute":[161,193,217,302],"labels":[162],"ID,":[165],"gender,":[166],"age,":[167],"wearing":[169],"hats.":[170],"This":[171],"ensures":[173],"consistency":[174,197,303],"between":[177],"anonymized":[178,200],"while":[181,219,304],"excluding":[182],"sensitive":[183],"ID":[184,221,307],"generation":[190],"module":[191],"transformation":[194],"generate":[199],"images.":[202],"An":[203],"adversarial":[204],"mechanism":[205],"employed":[207],"train":[209],"module,":[211],"ensuring":[212,248],"preservation":[214],"important":[216],"information":[218],"removing":[220],"reversibility,":[225],"recovery":[230,240],"stage":[231],"introduced.":[233],"Anonymized":[234],"are":[236],"fed":[237],"into":[238],"generator":[241],"reconstruct":[243],"images,":[247],"compatibility":[249],"authorized":[251],"Extensive":[253],"experiments":[254],"conducted":[255],"on":[256,271],"two":[257],"widely":[258],"utilized":[259],"re-identification":[261],"datasets,":[262],"achieving":[263],"average":[264],"12.1%":[265],"5.0%":[267],"rank-1":[268],"accuracies":[269],"respectively":[270],"Market":[272],"MSMT17":[274],"datasets":[275],"after":[276],"anonymized,":[277],"demonstrate":[278],"effectiveness":[280],"proposed":[283],"method":[285],"context":[288],"navigation.":[294],"results":[296],"indicate":[297],"that":[298],"successfully":[300],"maintains":[301],"preserving":[305],"privacy-sensitive":[306],"information,":[308],"providing":[309],"promising":[311],"solution":[312],"applications.":[322]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}