{"id":"https://openalex.org/W4406459562","doi":"https://doi.org/10.1109/bigdata62323.2024.10825650","title":"User Privacy in Skeleton-based Motion Data","display_name":"User Privacy in Skeleton-based Motion Data","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406459562","doi":"https://doi.org/10.1109/bigdata62323.2024.10825650"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825650","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825650","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","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/A5102886863","display_name":"Thomas H. Carr","orcid":"https://orcid.org/0009-0006-6039-0209"},"institutions":[{"id":"https://openalex.org/I102149020","display_name":"University of North Carolina at Charlotte","ror":"https://ror.org/04dawnj30","country_code":"US","type":"education","lineage":["https://openalex.org/I102149020"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Thomas Carr","raw_affiliation_strings":["University of North Carolina at Charlotte,Charlotte,NC,USA"],"affiliations":[{"raw_affiliation_string":"University of North Carolina at Charlotte,Charlotte,NC,USA","institution_ids":["https://openalex.org/I102149020"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100730268","display_name":"Depeng Xu","orcid":"https://orcid.org/0000-0002-0371-1815"},"institutions":[{"id":"https://openalex.org/I102149020","display_name":"University of North Carolina at Charlotte","ror":"https://ror.org/04dawnj30","country_code":"US","type":"education","lineage":["https://openalex.org/I102149020"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Depeng Xu","raw_affiliation_strings":["University of North Carolina at Charlotte,Charlotte,NC,USA"],"affiliations":[{"raw_affiliation_string":"University of North Carolina at Charlotte,Charlotte,NC,USA","institution_ids":["https://openalex.org/I102149020"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5102886863"],"corresponding_institution_ids":["https://openalex.org/I102149020"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26669739,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"8219","last_page":"8221"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9955999851226807,"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"}},"topics":[{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9955999851226807,"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":0.9886000156402588,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9869999885559082,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.703836977481842},{"id":"https://openalex.org/keywords/skeleton","display_name":"Skeleton (computer programming)","score":0.590883195400238},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.44320148229599},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3466706871986389}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.703836977481842},{"id":"https://openalex.org/C18969341","wikidata":"https://www.wikidata.org/wiki/Q1169129","display_name":"Skeleton (computer programming)","level":2,"score":0.590883195400238},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.44320148229599},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3466706871986389},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825650","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825650","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","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":10,"referenced_works":["https://openalex.org/W2794597556","https://openalex.org/W3034999503","https://openalex.org/W3101257721","https://openalex.org/W4313029666","https://openalex.org/W4382318144","https://openalex.org/W4387849007","https://openalex.org/W4387968033","https://openalex.org/W4396822023","https://openalex.org/W6734194636","https://openalex.org/W6866753374"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2953562271","https://openalex.org/W2376932109","https://openalex.org/W2001405890"],"abstract_inverted_index":{"Capturing":[0],"skeleton":[1,37,79,185],"data":[2,32,38],"is":[3,138],"an":[4,139],"important":[5],"area":[6],"of":[7,29,57],"computer":[8],"vision,":[9],"especially":[10],"for":[11,176,182],"use":[12],"in":[13,67],"a":[14,55,68,97,110,126,170],"virtual":[15],"reality":[16],"(VR)":[17],"setting.":[18],"As":[19],"new":[20,98,127],"techniques":[21,149],"to":[22,40,47,113,150],"extract":[23],"skeletons":[24,62],"come":[25],"out,":[26],"the":[27,36,73,78,83,120,130,154],"popularity":[28],"skeleton-based":[30],"motion":[31,142,172],"has":[33],"increased.":[34],"While":[35],"appears":[39],"be":[41,45],"anonymous,":[42],"it":[43],"can":[44],"exploited":[46],"discover":[48],"personally":[49],"identifiable":[50],"information":[51],"(PII).":[52],"This":[53],"poses":[54],"risk":[56],"unintentional":[58],"privacy":[59,74,84],"leakages":[60],"when":[61],"are":[63,118],"publicly":[64],"displayed,":[65],"like":[66],"VR":[69],"environment.":[70],"We":[71],"explore":[72],"implications":[75],"posed":[76],"by":[77,159],"data,":[80],"focusing":[81],"on":[82],"and":[85,88,152],"utility":[86],"trade-off":[87],"current":[89],"privacy-preserving":[90],"techniques.":[91],"In":[92],"this":[93],"paper,":[94],"we":[95,124,146,168],"propose":[96,125,169],"baseline":[99],"attack":[100],"model":[101,136,174],"Linkage":[102],"Attack":[103],"Neural":[104],"Network":[105],"(LAN)":[106],"that":[107,137],"acts":[108],"as":[109],"matching":[111],"classifier":[112],"distinguish":[114],"whether":[115],"two":[116],"skeleton-sequences":[117],"from":[119],"same":[121],"actor.":[122],"Then":[123],"defense":[128],"model,":[129],"Privacy-centric":[131],"Deep":[132],"Motion":[133],"Retargeting":[134],"(PMR)":[135],"adversarial/cooperatively":[140],"trained":[141],"retargeting":[143,173],"model.":[144],"Additionally,":[145],"incorporate":[147],"explanation":[148],"identify":[151],"mask":[153],"most":[155],"privacy-sensitive":[156],"joints,":[157],"either":[158],"zeroing":[160],"them":[161],"out":[162],"or":[163],"adding":[164],"controlled":[165],"noise.":[166],"Finally,":[167],"transformer-based":[171],"designed":[175],"real-time":[177],"applications,":[178],"leveraging":[179],"autoregressive":[180],"decoding":[181],"continuous,":[183],"frame-by-frame":[184],"generation.":[186]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}