{"id":"https://openalex.org/W3210053704","doi":"https://doi.org/10.1145/3447993.3483244","title":"RFID and camera fusion for recognition of human-object interactions","display_name":"RFID and camera fusion for recognition of human-object interactions","publication_year":2021,"publication_date":"2021-10-25","ids":{"openalex":"https://openalex.org/W3210053704","doi":"https://doi.org/10.1145/3447993.3483244","mag":"3210053704"},"language":"en","primary_location":{"id":"doi:10.1145/3447993.3483244","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447993.3483244","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th Annual International Conference on Mobile Computing and Networking","raw_type":"proceedings-article"},"type":"conference-paper","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/A5009324770","display_name":"Xiulong Liu","orcid":"https://orcid.org/0000-0002-4746-5599"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiulong Liu","raw_affiliation_strings":["Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100765517","display_name":"Dongdong Liu","orcid":"https://orcid.org/0000-0002-7877-5477"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongdong Liu","raw_affiliation_strings":["Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5002640738","display_name":"Jiuwu Zhang","orcid":"https://orcid.org/0000-0001-9286-4217"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiuwu Zhang","raw_affiliation_strings":["Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054698524","display_name":"Tao Gu","orcid":"https://orcid.org/0000-0002-1350-6639"},"institutions":[{"id":"https://openalex.org/I99043593","display_name":"Macquarie University","ror":"https://ror.org/01sf06y89","country_code":"AU","type":"education","lineage":["https://openalex.org/I99043593"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Tao Gu","raw_affiliation_strings":["Macquarie University, Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Macquarie University, Sydney, Australia","institution_ids":["https://openalex.org/I99043593"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111982109","display_name":"Keqiu Li","orcid":"https://orcid.org/0000-0003-1758-3030"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Keqiu Li","raw_affiliation_strings":["Tianjin University, Tianjin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":42,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"296","last_page":"308"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9959999918937683,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T10653","display_name":"Robot Manipulation and Learning","score":0.988099992275238,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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":0.8198468685150146},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7003873586654663},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6894042491912842},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.43487024307250977},{"id":"https://openalex.org/keywords/offset","display_name":"Offset (computer science)","score":0.4264596700668335}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8198468685150146},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7003873586654663},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6894042491912842},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.43487024307250977},{"id":"https://openalex.org/C175291020","wikidata":"https://www.wikidata.org/wiki/Q1156822","display_name":"Offset (computer science)","level":2,"score":0.4264596700668335},{"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:10.1145/3447993.3483244","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3447993.3483244","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 27th Annual International Conference on Mobile Computing and Networking","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.800000011920929,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1615828794","https://openalex.org/W1966217482","https://openalex.org/W2079566955","https://openalex.org/W2095396347","https://openalex.org/W2133365802","https://openalex.org/W2141336889","https://openalex.org/W2155983176","https://openalex.org/W2322989609","https://openalex.org/W2471695703","https://openalex.org/W2519985940","https://openalex.org/W2525860450","https://openalex.org/W2583148033","https://openalex.org/W2606998139","https://openalex.org/W2624822259","https://openalex.org/W2791862000","https://openalex.org/W2802187623","https://openalex.org/W2920700366","https://openalex.org/W2930506945","https://openalex.org/W2950821050","https://openalex.org/W2963015168","https://openalex.org/W2995786667","https://openalex.org/W3047296477","https://openalex.org/W3047312827","https://openalex.org/W3094509709","https://openalex.org/W3206423893","https://openalex.org/W6637677336","https://openalex.org/W6750156365","https://openalex.org/W6782028424","https://openalex.org/W7008161479"],"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":{"Recognition":[0],"of":[1,94,116,135,176,184,214,246],"human-object":[2,138,261],"interactions":[3,43],"is":[4,34],"practically":[5],"important":[6],"in":[7,47,217,227,270],"various":[8],"human-centric":[9],"sensing":[10,164],"scenarios":[11],"such":[12],"as":[13],"smart":[14],"supermarket,":[15],"factory,":[16],"and":[17,28,49,121,260],"home.":[18],"This":[19],"paper":[20],"proposes":[21],"an":[22,98,264],"RF-Camera":[23,252],"system":[24],"by":[25,69,128,198],"fusing":[26],"RFID":[27,224,236],"Computer":[29],"Vision":[30],"(CV)":[31],"techniques,":[32],"which":[33,77,130,228],"the":[35,40,63,78,91,113,117,124,174,185,244,255],"first":[36,55],"work":[37],"to":[38,61,72,89,150,159,172,204,242],"recognize":[39,254],"human":[41,258],"gestural":[42,256],"with":[44,131,189,263],"physical":[45,114],"objects":[46],"multi-subject":[48],"multi-object":[50],"scenarios.":[51],"In":[52],"RF-Camera,":[53,145],"we":[54,111,166,193,220],"propose":[56,86,167,221],"a":[57,73,87,168,200,222],"dimension":[58],"reduction":[59],"method":[60,88],"transform":[62],"subject's":[64,79],"3D":[65],"hand":[66,206],"trajectory":[67,197],"captured":[68,205],"depth":[70],"camera":[71],"2D":[74],"image,":[75],"using":[76],"gesture":[80],"can":[81,140,233,253],"be":[82,141,151],"recognized.":[83],"We":[84,238],"also":[85],"extract":[90],"facial":[92],"image":[93,99],"target":[95,187,195,215],"subject":[96],"from":[97,162],"that":[100,251],"may":[101],"contain":[102],"irrelevant":[103,160],"subjects,":[104],"thereby":[105],"further":[106,122],"recognizing":[107],"his/her":[108],"identity.":[109],"Finally,":[110],"model":[112],"movements":[115],"held":[118,186],"object's":[119],"tag":[120,125,137,188,196],"predict":[123,181],"phase":[126,133,182],"data,":[127,165],"comparing":[129],"real":[132],"data":[134,157,183,232],"each":[136],"matching":[139,262],"discovered.":[142],"When":[143],"implementing":[144],"three":[146],"technical":[147],"challenges":[148],"need":[149],"addressed.":[152],"(i)":[153],"To":[154,180,209],"remove":[155],"noisy":[156],"corresponding":[158],"actions":[161],"raw":[163],"state":[169],"transition":[170],"diagram":[171],"determine":[173],"boundary":[175],"effective":[177],"data.":[178],"(ii)":[179],"unknown":[190],"hand-tag":[191,202],"offset,":[192],"quantify":[194],"adding":[199],"variable":[201],"vector":[203],"trajectory.":[207],"(iii)":[208],"ensure":[210],"high":[211],"reading":[212],"rates":[213],"tags":[216],"tag-dense":[218],"scenarios,":[219],"CV-assisted":[223],"scheduling":[225],"method,":[226],"analytics":[229],"on":[230],"CV":[231],"help":[234],"schedule":[235],"readings.":[237],"conduct":[239],"extensive":[240],"experiments":[241],"evaluate":[243],"performance":[245],"RF-Camera.":[247],"Experimental":[248],"results":[249],"demonstrate":[250],"actions,":[257],"identity":[259],"average":[265],"accuracy":[266],"higher":[267],"than":[268],"90%":[269],"most":[271],"cases.":[272]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":12},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
