{"id":"https://openalex.org/W4410068145","doi":"https://doi.org/10.1145/3715014.3722069","title":"PIPE: Privacy-preserving 6DoF Pose Estimation for Immersive Applications","display_name":"PIPE: Privacy-preserving 6DoF Pose Estimation for Immersive Applications","publication_year":2025,"publication_date":"2025-05-04","ids":{"openalex":"https://openalex.org/W4410068145","doi":"https://doi.org/10.1145/3715014.3722069"},"language":"en","primary_location":{"id":"doi:10.1145/3715014.3722069","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3715014.3722069","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd ACM Conference on Embedded Networked Sensor Systems","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3715014.3722069","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057560778","display_name":"Nan Wu","orcid":"https://orcid.org/0000-0003-4875-2941"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nan Wu","raw_affiliation_strings":["George Mason University, Fairfax, Virginia, USA"],"raw_orcid":"https://orcid.org/0000-0003-4875-2941","affiliations":[{"raw_affiliation_string":"George Mason University, Fairfax, Virginia, USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034037032","display_name":"Ruizhi Cheng","orcid":"https://orcid.org/0000-0002-3942-5167"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ruizhi Cheng","raw_affiliation_strings":["George Mason University, Fairfax, Virginia, USA"],"raw_orcid":"https://orcid.org/0000-0002-3942-5167","affiliations":[{"raw_affiliation_string":"George Mason University, Fairfax, Virginia, USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065505890","display_name":"Songqing Chen","orcid":"https://orcid.org/0000-0003-4650-7125"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Songqing Chen","raw_affiliation_strings":["George Mason University, Fairfax, Virginia, USA"],"raw_orcid":"https://orcid.org/0000-0003-4650-7125","affiliations":[{"raw_affiliation_string":"George Mason University, Fairfax, Virginia, USA","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078582134","display_name":"Bo Han","orcid":"https://orcid.org/0000-0001-7042-3322"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Bo Han","raw_affiliation_strings":["George Mason University, Fairfax, Virginia, USA"],"raw_orcid":"https://orcid.org/0000-0001-7042-3322","affiliations":[{"raw_affiliation_string":"George Mason University, Fairfax, Virginia, USA","institution_ids":["https://openalex.org/I162714631"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I162714631"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"518","last_page":"532"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9959999918937683,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9959999918937683,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10036","display_name":"Advanced Neural Network Applications","score":0.9865000247955322,"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/T10888","display_name":"Augmented Reality Applications","score":0.9857000112533569,"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/computer-science","display_name":"Computer science","score":0.7960027456283569},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.4645765721797943},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.46412965655326843},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.459375262260437},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4188275933265686},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40748077630996704},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0687904953956604}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7960027456283569},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.4645765721797943},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.46412965655326843},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.459375262260437},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4188275933265686},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40748077630996704},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0687904953956604},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3715014.3722069","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3715014.3722069","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd ACM Conference on Embedded Networked Sensor Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3715014.3722069","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3715014.3722069","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 23rd ACM Conference on Embedded Networked Sensor Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":79,"referenced_works":["https://openalex.org/W125693051","https://openalex.org/W1552672384","https://openalex.org/W1557590790","https://openalex.org/W1599667215","https://openalex.org/W1642358959","https://openalex.org/W1677409904","https://openalex.org/W1873763122","https://openalex.org/W1915485278","https://openalex.org/W1989476314","https://openalex.org/W2026830782","https://openalex.org/W2031381049","https://openalex.org/W2031533839","https://openalex.org/W2033819227","https://openalex.org/W2060871119","https://openalex.org/W2085261163","https://openalex.org/W2110357983","https://openalex.org/W2117228865","https://openalex.org/W2124313187","https://openalex.org/W2129000642","https://openalex.org/W2133665775","https://openalex.org/W2149745530","https://openalex.org/W2151103935","https://openalex.org/W2154553365","https://openalex.org/W2162996853","https://openalex.org/W2164327070","https://openalex.org/W2165698076","https://openalex.org/W2170102584","https://openalex.org/W2171033594","https://openalex.org/W2171298586","https://openalex.org/W2200124539","https://openalex.org/W2338881754","https://openalex.org/W2344474200","https://openalex.org/W2467391961","https://openalex.org/W2471962767","https://openalex.org/W2477079838","https://openalex.org/W2522940611","https://openalex.org/W2529154467","https://openalex.org/W2536680313","https://openalex.org/W2560835477","https://openalex.org/W2563408008","https://openalex.org/W2605756146","https://openalex.org/W2606882085","https://openalex.org/W2740418457","https://openalex.org/W2792793629","https://openalex.org/W2799112149","https://openalex.org/W2898344194","https://openalex.org/W2900934586","https://openalex.org/W2918056293","https://openalex.org/W2951881930","https://openalex.org/W2962705366","https://openalex.org/W2963243246","https://openalex.org/W2963989815","https://openalex.org/W2973990459","https://openalex.org/W2979771948","https://openalex.org/W3043075211","https://openalex.org/W3047931833","https://openalex.org/W3048409441","https://openalex.org/W3080770848","https://openalex.org/W3102327032","https://openalex.org/W3106739298","https://openalex.org/W3136046080","https://openalex.org/W3150051545","https://openalex.org/W3153022867","https://openalex.org/W3168520278","https://openalex.org/W3176547129","https://openalex.org/W4231831269","https://openalex.org/W4240266525","https://openalex.org/W4248598408","https://openalex.org/W4285029766","https://openalex.org/W4295886237","https://openalex.org/W4295979748","https://openalex.org/W4313128201","https://openalex.org/W4313154644","https://openalex.org/W4376626884","https://openalex.org/W4378696892","https://openalex.org/W4380928270","https://openalex.org/W4385080273","https://openalex.org/W4404034618","https://openalex.org/W4404034694"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Image-based":[0,69],"mapping":[1],"and":[2,33,115,146,156,190],"localization":[3],"offer":[4],"six":[5],"degrees":[6],"of":[7,51,76,90,174],"freedom":[8],"(6DoF)":[9],"pose":[10,97,112,161,201],"estimation":[11,98,113,162,202],"for":[12,96],"immersive":[13],"applications.":[14],"This":[15],"is":[16,78],"achieved":[17],"by":[18,55,80,141,150,194],"matching,":[19],"on":[20],"a":[21,28,38,66,87,167],"server,":[22],"2D":[23],"visual":[24],"features":[25,35,91],"extracted":[26,92],"from":[27,93],"mobile":[29],"device's":[30],"camera":[31,56,94],"view":[32],"3D":[34],"stored":[36],"in":[37,177],"map.":[39],"While":[40],"effective,":[41],"this":[42,60],"process":[43],"may":[44],"lead":[45],"to":[46,131,159,170,196],"privacy":[47,101,107,175,189],"breaches":[48],"(e.g.,":[49,118,204],"exposure":[50],"sensitive":[52],"information":[53],"captured":[54],"views).":[57],"To":[58,121],"tackle":[59],"crucial":[61],"issue,":[62],"we":[63,165],"present":[64],"PIPE,":[65],"first-of-its-kind":[67],"Privacy-preserving":[68],"6DoF":[70],"Pose":[71],"Estimation":[72],"system.":[73],"The":[74],"design":[75],"PIPE":[77,125,185],"motivated":[79],"our":[81],"key":[82],"observation":[83],"that":[84,184],"uploading":[85],"only":[86],"small":[88],"amount":[89],"views":[95],"could":[99],"reduce":[100,132,191],"leakage.":[102],"However,":[103],"trade-offs":[104],"exist":[105],"between":[106],"preservation,":[108],"system":[109,116],"utility":[110],"(i.e.,":[111],"accuracy),":[114],"performance":[117,181],"end-to-end":[119,192],"latency).":[120],"balance":[122],"the":[123,128,153,172],"trade-offs,":[124],"deliberately":[126],"explores":[127],"feature-detection":[129],"space":[130],"computation":[133],"latency,":[134],"designs":[135],"an":[136],"efficient":[137],"feature":[138,148],"ranking":[139,155],"method":[140],"judiciously":[142],"utilizing":[143],"map":[144],"data,":[145],"optimizes":[147],"selection":[149],"jointly":[151],"considering":[152],"features'":[154],"spatial":[157],"distribution":[158],"improve":[160],"accuracy.":[163],"Moreover,":[164],"construct":[166],"learning-based":[168],"metric":[169],"quantify":[171],"extent":[173],"leakage":[176],"images.":[178],"Our":[179],"extensive":[180],"evaluation":[182],"reveals":[183],"can":[186],"effectively":[187],"preserve":[188],"latency":[193],"up":[195],"22.6%,":[197],"while":[198],"marginally":[199],"affecting":[200],"accuracy":[203],"as":[205,207],"low":[206],"2.7%).":[208]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}