{"id":"https://openalex.org/W4408325103","doi":"https://doi.org/10.1109/globecom52923.2024.10901794","title":"A Lightweight Human Pose Estimation Approach for Edge Computing-Enabled Metaverse with Compressive Sensing","display_name":"A Lightweight Human Pose Estimation Approach for Edge Computing-Enabled Metaverse with Compressive Sensing","publication_year":2024,"publication_date":"2024-12-08","ids":{"openalex":"https://openalex.org/W4408325103","doi":"https://doi.org/10.1109/globecom52923.2024.10901794"},"language":"en","primary_location":{"id":"doi:10.1109/globecom52923.2024.10901794","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom52923.2024.10901794","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2024 - 2024 IEEE Global Communications Conference","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/A5007329852","display_name":"Nguyen Quang Hieu","orcid":"https://orcid.org/0000-0003-1517-8285"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Nguyen Quang Hieu","raw_affiliation_strings":["University of Technology,School of Electrical and Data Engineering,Sydney,Australia"],"affiliations":[{"raw_affiliation_string":"University of Technology,School of Electrical and Data Engineering,Sydney,Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007992576","display_name":"Dinh Thai Hoang","orcid":"https://orcid.org/0000-0002-9528-0863"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Dinh Thai Hoang","raw_affiliation_strings":["University of Technology,School of Electrical and Data Engineering,Sydney,Australia"],"affiliations":[{"raw_affiliation_string":"University of Technology,School of Electrical and Data Engineering,Sydney,Australia","institution_ids":["https://openalex.org/I114017466"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100697893","display_name":"Diep N. Nguyen","orcid":"https://orcid.org/0000-0003-2659-8648"},"institutions":[{"id":"https://openalex.org/I114017466","display_name":"University of Technology Sydney","ror":"https://ror.org/03f0f6041","country_code":"AU","type":"education","lineage":["https://openalex.org/I114017466"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Diep N. Nguyen","raw_affiliation_strings":["University of Technology,School of Electrical and Data Engineering,Sydney,Australia"],"affiliations":[{"raw_affiliation_string":"University of Technology,School of Electrical and Data Engineering,Sydney,Australia","institution_ids":["https://openalex.org/I114017466"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5007329852"],"corresponding_institution_ids":["https://openalex.org/I114017466"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.2937022,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1437","last_page":"1442"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9850000143051147,"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":0.9850000143051147,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9786999821662903,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.95660001039505,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.7357091903686523},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5121316909790039},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3945923149585724},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3927764296531677},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3281984031200409}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7357091903686523},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5121316909790039},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3945923149585724},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3927764296531677},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3281984031200409}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/globecom52923.2024.10901794","is_oa":false,"landing_page_url":"https://doi.org/10.1109/globecom52923.2024.10901794","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"GLOBECOM 2024 - 2024 IEEE Global Communications Conference","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":14,"referenced_works":["https://openalex.org/W143004564","https://openalex.org/W2342688137","https://openalex.org/W2605243700","https://openalex.org/W2898073175","https://openalex.org/W3133913697","https://openalex.org/W4225609743","https://openalex.org/W4380365050","https://openalex.org/W4385489997","https://openalex.org/W4390044335","https://openalex.org/W4399666227","https://openalex.org/W6640963894","https://openalex.org/W6683664273","https://openalex.org/W6735307612","https://openalex.org/W6752579191"],"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":{"The":[0],"ability":[1],"to":[2,60,70,130,168,183,244],"estimate":[3],"3D":[4,44,198,225],"movements":[5,201],"of":[6,24,89,116,197,228,234,254],"users":[7],"over":[8,39,78,119],"edge":[9],"computing-enabled":[10],"networks,":[11,15],"such":[12],"as":[13],"5G/6G":[14],"is":[16,242,251],"a":[17,107,126,136,158,169,176,213],"key":[18],"enabler":[19],"for":[20,42,110,205],"the":[21,61,65,75,86,90,132,141,149,155,163,181,185,195,203,229,235,238],"new":[22],"era":[23],"extended":[25],"reality":[26],"(XR)":[27],"and":[28,113,161,207],"Metaverse":[29,208],"applications.":[30,209],"Recent":[31],"advancements":[32],"in":[33,98],"deep":[34,177],"learning":[35],"have":[36,146],"shown":[37],"advantages":[38],"optimization":[40],"techniques":[41],"estimating":[43],"human":[45,199,226],"poses":[46,82,227],"given":[47],"spare":[48],"measurements":[49,236],"from":[50,189,237],"sensor":[51],"signals,":[52],"i.e.,":[53,248],"inertial":[54],"measurement":[55],"unit":[56],"(IMU)":[57],"sensors":[58],"attached":[59],"XR":[62,206],"devices.":[63],"However,":[64],"existing":[66],"works":[67],"lack":[68],"applicability":[69],"wireless":[71,80,121],"systems,":[72],"where":[73],"transmitting":[74],"IMU":[76,91,117,187,215],"signals":[77,92,118,188],"noisy":[79,120,190],"networks":[81],"significant":[83],"challenges.":[84],"Furthermore,":[85,173],"potential":[87],"redundancy":[88,111],"has":[93],"not":[94],"been":[95],"considered,":[96],"resulting":[97],"highly":[99,223],"redundant":[100],"transmissions.":[101],"In":[102],"this":[103],"work,":[104],"we":[105,145,174],"propose":[106],"novel":[108],"approach":[109,124],"removal":[112],"lightweight":[114],"transmission":[115,171],"environments.":[122],"Our":[123],"utilizes":[125],"random":[127],"Gaussian":[128,151],"matrix":[129,152],"transform":[131],"original":[133,186,239],"signal":[134,156],"into":[135,157],"lower-dimensional":[137,159],"space.":[138],"By":[139],"leveraging":[140],"compressive":[142],"sensing":[143],"theory,":[144],"proved":[147],"that":[148,218],"designed":[150],"can":[153,221],"project":[154],"space":[160],"preserve":[162],"Set-Restricted":[164],"Eigenvalue":[165],"condition,":[166],"subject":[167],"power":[170],"constraint.":[172],"develop":[175],"generative":[178],"model":[179],"at":[180,202],"receiver":[182,204],"recover":[184],"compressed":[191],"data,":[192],"thus":[193],"enabling":[194],"creation":[196],"body":[200],"Simulation":[210],"results":[211],"on":[212],"real-world":[214],"dataset":[216],"show":[217],"our":[219],"framework":[220],"achieve":[222],"accurate":[224],"user":[230],"using":[231],"only":[232],"82%":[233],"signals.":[240],"This":[241],"comparable":[243],"an":[245,252],"optimization-based":[246],"approach,":[247],"Lasso,":[249],"but":[250],"order":[253],"magnitude":[255],"faster.":[256]},"counts_by_year":[],"updated_date":"2025-12-21T23:12:01.093139","created_date":"2025-10-10T00:00:00"}
