{"id":"https://openalex.org/W2398098909","doi":"https://doi.org/10.1145/2851581.2889430","title":"ID-Match","display_name":"ID-Match","publication_year":2016,"publication_date":"2016-05-06","ids":{"openalex":"https://openalex.org/W2398098909","doi":"https://doi.org/10.1145/2851581.2889430","mag":"2398098909"},"language":"en","primary_location":{"id":"doi:10.1145/2851581.2889430","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2851581.2889430","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems","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/A5025051705","display_name":"Hanchuan Li","orcid":null},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Hanchuan Li","raw_affiliation_strings":["University of Washington, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101821110","display_name":"Peijin Zhang","orcid":"https://orcid.org/0000-0002-8523-5428"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Peijin Zhang","raw_affiliation_strings":["Carnegie Mellon University, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064116837","display_name":"Samer Al Moubayed","orcid":null},"institutions":[{"id":"https://openalex.org/I4210142140","display_name":"Walt Disney (United States)","ror":"https://ror.org/04eg47h42","country_code":"US","type":"company","lineage":["https://openalex.org/I4210142140"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Samer Al Moubayed","raw_affiliation_strings":["Disney Research Pittsburgh, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Disney Research Pittsburgh, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I4210142140"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039879761","display_name":"Shwetak Patel","orcid":"https://orcid.org/0000-0002-6300-4389"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shwetak N. Patel","raw_affiliation_strings":["University of Washington, Seattle, WA, USA"],"affiliations":[{"raw_affiliation_string":"University of Washington, Seattle, WA, USA","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047416400","display_name":"Alanson P. Sample","orcid":"https://orcid.org/0000-0002-8046-0538"},"institutions":[{"id":"https://openalex.org/I4210142140","display_name":"Walt Disney (United States)","ror":"https://ror.org/04eg47h42","country_code":"US","type":"company","lineage":["https://openalex.org/I4210142140"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alanson P. Sample","raw_affiliation_strings":["Disney Research Pittsburgh, Pittsburgh, PA, USA"],"affiliations":[{"raw_affiliation_string":"Disney Research Pittsburgh, Pittsburgh, PA, USA","institution_ids":["https://openalex.org/I4210142140"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5025051705"],"corresponding_institution_ids":["https://openalex.org/I201448701"],"apc_list":null,"apc_paid":null,"fwci":5.3291,"has_fulltext":false,"cited_by_count":41,"citation_normalized_percentile":{"value":0.95990849,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"7","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9973999857902527,"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/T11704","display_name":"Mobile Crowdsensing and Crowdsourcing","score":0.9954000115394592,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"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":0.7904738187789917},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6504228115081787},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6396032571792603},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.6261844635009766},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5169165134429932},{"id":"https://openalex.org/keywords/motion-capture","display_name":"Motion capture","score":0.462058424949646},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4423104226589203},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.4027687609195709},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08442878723144531}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7904738187789917},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6504228115081787},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6396032571792603},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.6261844635009766},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5169165134429932},{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.462058424949646},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4423104226589203},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4027687609195709},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08442878723144531},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2851581.2889430","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2851581.2889430","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/14","display_name":"Life below water","score":0.5400000214576721}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W127475754","https://openalex.org/W1170938179","https://openalex.org/W1542318638","https://openalex.org/W1585879837","https://openalex.org/W1969198541","https://openalex.org/W2026384490","https://openalex.org/W2028683273","https://openalex.org/W2049763311","https://openalex.org/W2069973845","https://openalex.org/W2070924230","https://openalex.org/W2100989187","https://openalex.org/W2102159398","https://openalex.org/W2102265406","https://openalex.org/W2108292920","https://openalex.org/W2123430663","https://openalex.org/W2125111937","https://openalex.org/W2129567471","https://openalex.org/W2139125750","https://openalex.org/W2145287260","https://openalex.org/W2148313857","https://openalex.org/W2152153632","https://openalex.org/W2154383790","https://openalex.org/W2158090937","https://openalex.org/W2163993204","https://openalex.org/W2186170585","https://openalex.org/W3140056478"],"related_works":["https://openalex.org/W1827696521","https://openalex.org/W2173450654","https://openalex.org/W2039848376","https://openalex.org/W2621720158","https://openalex.org/W2091722187","https://openalex.org/W2006196742","https://openalex.org/W2130272765","https://openalex.org/W4401486264","https://openalex.org/W2055991023","https://openalex.org/W2682927604"],"abstract_inverted_index":{"Technologies":[0],"that":[1,40,63,79],"allow":[2],"autonomous":[3,134],"robots":[4],"and":[5,11,37,61,88,100],"computer":[6,35],"systems":[7],"to":[8,22,48,64,92,113],"quickly":[9],"recognize":[10],"interact":[12],"with":[13,72,97,108,132],"individuals":[14,69,93],"in":[15,105,120,137],"a":[16,24,33,42,55,73],"group":[17],"setting":[18],"has":[19],"the":[20,50,115],"potential":[21],"enable":[23],"wide":[25],"range":[26],"of":[27,54,68,85,102,117,124,142],"personalized":[28],"experiences.":[29],"We":[30],"present":[31],"ID-Match,":[32],"hybrid":[34],"vision":[36],"RFID":[38,56],"system":[39,82],"uses":[41],"novel":[43],"reverse":[44],"synthetic":[45],"aperture":[46],"technique":[47],"recover":[49],"relative":[51],"motion":[52,66],"paths":[53,67],"tags":[57],"worn":[58],"by":[59],"people":[60,104],"correlate":[62],"physical":[65],"as":[70],"measured":[71],"3D":[74],"depth":[75],"camera.":[76],"Results":[77],"show":[78],"our":[80],"real-time":[81],"is":[83],"capable":[84],"simultaneously":[86],"recognizing":[87],"correctly":[89],"assigning":[90],"IDs":[91],"within":[94],"4":[95],"seconds":[96,107],"96.6%":[98],"accuracy":[99,141],"groups":[101,123],"five":[103,125],"7":[106],"95%":[109],"accuracy.":[110],"In":[111],"order":[112],"test":[114],"effectiveness":[116],"this":[118],"approach":[119],"realistic":[121],"scenarios,":[122],"participants":[126],"play":[127],"an":[128,133,138],"interactive":[129],"quiz":[130],"game":[131],"robot,":[135],"resulting":[136],"ID":[139],"assignment":[140],"93.3%.":[143]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":13},{"year":2018,"cited_by_count":8},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2016-06-24T00:00:00"}