{"id":"https://openalex.org/W7164853994","doi":"https://doi.org/10.1145/3805622.3810642","title":"LimbAug: Enhancing Virtual IMU Generalization in Human Activity Recognition via Learning Limb Movement Difference","display_name":"LimbAug: Enhancing Virtual IMU Generalization in Human Activity Recognition via Learning Limb Movement Difference","publication_year":2026,"publication_date":"2026-06-15","ids":{"openalex":"https://openalex.org/W7164853994","doi":"https://doi.org/10.1145/3805622.3810642"},"language":null,"primary_location":{"id":"doi:10.1145/3805622.3810642","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810642","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 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3805622.3810642","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5035820547","display_name":"Lingtao Huang","orcid":"https://orcid.org/0009-0003-7312-5402"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]},{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lingtao Huang","raw_affiliation_strings":["Guangzhou Insitute of Technology, Xidian University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0009-0003-7312-5402","affiliations":[{"raw_affiliation_string":"Guangzhou Insitute of Technology, Xidian University, Guangzhou, China","institution_ids":["https://openalex.org/I149594827","https://openalex.org/I37987034"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001725176","display_name":"Chengshuo Xia","orcid":"https://orcid.org/0000-0002-3937-2077"},"institutions":[{"id":"https://openalex.org/I149594827","display_name":"Xidian University","ror":"https://ror.org/05s92vm98","country_code":"CN","type":"education","lineage":["https://openalex.org/I149594827"]},{"id":"https://openalex.org/I37987034","display_name":"Guangzhou University","ror":"https://ror.org/05ar8rn06","country_code":"CN","type":"education","lineage":["https://openalex.org/I37987034"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chengshuo Xia","raw_affiliation_strings":["Guangzhou Insitute of Technology, Xidian University, Guangzhou, China"],"raw_orcid":"https://orcid.org/0000-0002-3937-2077","affiliations":[{"raw_affiliation_string":"Guangzhou Insitute of Technology, Xidian University, Guangzhou, China","institution_ids":["https://openalex.org/I149594827","https://openalex.org/I37987034"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.93945183,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1578","last_page":"1582"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.8276000022888184,"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":0.8276000022888184,"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/T12290","display_name":"Human Motion and Animation","score":0.08789999783039093,"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"}},{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.03460000082850456,"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/inertial-measurement-unit","display_name":"Inertial measurement unit","score":0.7907999753952026},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6543999910354614},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.652899980545044},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.6432999968528748},{"id":"https://openalex.org/keywords/motion-capture","display_name":"Motion capture","score":0.5604000091552734},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5566999912261963},{"id":"https://openalex.org/keywords/movement","display_name":"Movement (music)","score":0.4262999892234802}],"concepts":[{"id":"https://openalex.org/C79061980","wikidata":"https://www.wikidata.org/wiki/Q941680","display_name":"Inertial measurement unit","level":2,"score":0.7907999753952026},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6945000290870667},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6597999930381775},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6543999910354614},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.652899980545044},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.6432999968528748},{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.5604000091552734},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5566999912261963},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5374000072479248},{"id":"https://openalex.org/C2780226923","wikidata":"https://www.wikidata.org/wiki/Q929848","display_name":"Movement (music)","level":2,"score":0.4262999892234802},{"id":"https://openalex.org/C2986578859","wikidata":"https://www.wikidata.org/wiki/Q657632","display_name":"Human motion","level":3,"score":0.4205000102519989},{"id":"https://openalex.org/C150303390","wikidata":"https://www.wikidata.org/wiki/Q1983852","display_name":"Virtual actor","level":3,"score":0.4196999967098236},{"id":"https://openalex.org/C194969405","wikidata":"https://www.wikidata.org/wiki/Q170519","display_name":"Virtual reality","level":2,"score":0.4196000099182129},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.3440999984741211},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3248000144958496},{"id":"https://openalex.org/C173386949","wikidata":"https://www.wikidata.org/wiki/Q192735","display_name":"Inertial frame of reference","level":2,"score":0.322299987077713},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2799000144004822},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C25344961","wikidata":"https://www.wikidata.org/wiki/Q192726","display_name":"Virtual machine","level":2,"score":0.2689000070095062}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3805622.3810642","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810642","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 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3805622.3810642","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3805622.3810642","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 2026 International Conference on Multimedia Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G3870238250","display_name":null,"funder_award_id":"2025JC-YBQN-852","funder_id":"https://openalex.org/F4320336567","funder_display_name":"Natural Science Basic Research Program of Shaanxi Province"},{"id":"https://openalex.org/G5015740022","display_name":null,"funder_award_id":"2024M762548","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"},{"id":"https://openalex.org/F4320336567","display_name":"Natural Science Basic Research Program of Shaanxi Province","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2128892560","https://openalex.org/W2270470215","https://openalex.org/W2340025709","https://openalex.org/W2811014843","https://openalex.org/W2898073175","https://openalex.org/W2971856312","https://openalex.org/W3083323811","https://openalex.org/W3153832461","https://openalex.org/W3199905074","https://openalex.org/W3200883581","https://openalex.org/W4288079574","https://openalex.org/W4312635677","https://openalex.org/W4313121376","https://openalex.org/W4385489997","https://openalex.org/W4386076288","https://openalex.org/W4387321395","https://openalex.org/W4396832081","https://openalex.org/W4396920196","https://openalex.org/W4401452455","https://openalex.org/W4412391304","https://openalex.org/W4413146076"],"related_works":[],"abstract_inverted_index":{"Synthesizing":[0],"virtual":[1,33,118],"Inertial":[2],"Measurement":[3],"Unit":[4],"(IMU)":[5],"data":[6,35,120],"from":[7,121],"3D":[8,45,77,102,126,141],"human":[9],"motion":[10,46,59,78,103,127,142],"sequences":[11,47],"has":[12],"emerged":[13],"as":[14],"a":[15,68,87,122],"promising":[16],"strategy":[17],"to":[18,48,71,99],"mitigate":[19],"the":[20,73,113,137,148],"scarcity":[21],"of":[22,43,58,115,125,153],"labeled":[23],"datasets":[24,42],"in":[25,56],"IMU-based":[26],"Human":[27],"Activity":[28],"Recognition":[29],"(HAR).":[30],"However,":[31],"existing":[32,101],"IMU":[34,119],"driven":[36],"methods":[37],"typically":[38],"necessitate":[39],"an":[40],"extensive":[41],"diverse":[44,117],"ensure":[49],"model":[50],"performance,":[51],"which":[52],"imposes":[53],"significant":[54],"challenges":[55],"terms":[57],"resource":[60],"acquisition.":[61],"To":[62],"address":[63],"this,":[64],"we":[65],"propose":[66],"LimbAug,":[67],"framework":[69],"designed":[70],"alleviate":[72],"high":[74],"demand":[75],"for":[76],"resources":[79],"through":[80],"intelligent":[81],"limb":[82,96],"movement":[83,97],"augmentation.":[84],"By":[85],"employing":[86],"conditional":[88],"Variational":[89],"Autoencoder":[90],"(cVAE),":[91],"LimbAug":[92,133],"learns":[93],"and":[94,150],"generates":[95],"differences":[98],"augment":[100],"sequences,":[104],"effectively":[105],"mimicking":[106],"real-world":[107,157],"intra-class":[108],"diversity.":[109],"This":[110],"approach":[111],"enables":[112],"synthesis":[114],"large-scale,":[116],"limited":[123],"number":[124],"samples.":[128],"Our":[129],"experiments":[130],"demonstrate":[131],"that":[132],"not":[134],"only":[135],"reduces":[136],"reliance":[138],"on":[139,156],"vast":[140],"libraries":[143],"but":[144],"also":[145],"significantly":[146],"enhances":[147],"generalization":[149],"recognition":[151],"accuracy":[152],"HAR":[154],"models":[155],"data.":[158]},"counts_by_year":[],"updated_date":"2026-06-16T07:37:23.134862","created_date":"2026-06-16T00:00:00"}
