{"id":"https://openalex.org/W7127968123","doi":"https://doi.org/10.1109/iccma67641.2025.11369549","title":"Privacy-Preserving 3D Lidar-Based Multi-Modal Activity Recognition in Human-Robot Interaction","display_name":"Privacy-Preserving 3D Lidar-Based Multi-Modal Activity Recognition in Human-Robot Interaction","publication_year":2025,"publication_date":"2025-11-24","ids":{"openalex":"https://openalex.org/W7127968123","doi":"https://doi.org/10.1109/iccma67641.2025.11369549"},"language":null,"primary_location":{"id":"doi:10.1109/iccma67641.2025.11369549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccma67641.2025.11369549","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 13th International Conference on Control, Mechatronics and Automation (ICCMA)","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/A5071020268","display_name":"Adel Baselizadeh","orcid":"https://orcid.org/0009-0005-7561-8889"},"institutions":[{"id":"https://openalex.org/I184942183","display_name":"University of Oslo","ror":"https://ror.org/01xtthb56","country_code":"NO","type":"education","lineage":["https://openalex.org/I184942183"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Adel Baselizadeh","raw_affiliation_strings":["University of Oslo,Department of Informatics,Oslo,Norway"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Oslo,Department of Informatics,Oslo,Norway","institution_ids":["https://openalex.org/I184942183"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125114347","display_name":"Md Zia Uddin","orcid":null},"institutions":[{"id":"https://openalex.org/I173888879","display_name":"SINTEF","ror":"https://ror.org/01f677e56","country_code":"NO","type":"facility","lineage":["https://openalex.org/I173888879"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Md Zia Uddin","raw_affiliation_strings":["SINTEF Digital,Department of Sustainable Communication Technologies,Oslo,Norway"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"SINTEF Digital,Department of Sustainable Communication Technologies,Oslo,Norway","institution_ids":["https://openalex.org/I173888879"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061869177","display_name":"Weria Khaksar","orcid":"https://orcid.org/0000-0002-6400-3150"},"institutions":[{"id":"https://openalex.org/I54108979","display_name":"Norwegian University of Life Sciences","ror":"https://ror.org/04a1mvv97","country_code":"NO","type":"education","lineage":["https://openalex.org/I54108979"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Weria Khaksar","raw_affiliation_strings":["Norwegian University of Life Sciences,Faculty of Science and Technology,&#x00C5;s,Norway"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Norwegian University of Life Sciences,Faculty of Science and Technology,&#x00C5;s,Norway","institution_ids":["https://openalex.org/I54108979"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Diana Saplacan Lindblom","orcid":null},"institutions":[{"id":"https://openalex.org/I184942183","display_name":"University of Oslo","ror":"https://ror.org/01xtthb56","country_code":"NO","type":"education","lineage":["https://openalex.org/I184942183"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Diana Saplacan Lindblom","raw_affiliation_strings":["University of Oslo,Department of Informatics,Oslo,Norway"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Oslo,Department of Informatics,Oslo,Norway","institution_ids":["https://openalex.org/I184942183"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071144214","display_name":"Jim T\u00f8rresen","orcid":"https://orcid.org/0000-0003-0556-0288"},"institutions":[{"id":"https://openalex.org/I184942183","display_name":"University of Oslo","ror":"https://ror.org/01xtthb56","country_code":"NO","type":"education","lineage":["https://openalex.org/I184942183"]}],"countries":["NO"],"is_corresponding":false,"raw_author_name":"Jim Torresen","raw_affiliation_strings":["University of Oslo,Department of Informatics,Oslo,Norway"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Oslo,Department of Informatics,Oslo,Norway","institution_ids":["https://openalex.org/I184942183"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9349,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.82904363,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"516","last_page":"523"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.6085000038146973,"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":0.6085000038146973,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.25119999051094055,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.01640000008046627,"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/activity-recognition","display_name":"Activity recognition","score":0.7397000193595886},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.574999988079071},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5515000224113464},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.510200023651123},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.47870001196861267},{"id":"https://openalex.org/keywords/human\u2013robot-interaction","display_name":"Human\u2013robot interaction","score":0.4372999966144562},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.414000004529953}],"concepts":[{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.7397000193595886},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6868000030517578},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5852000117301941},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.574999988079071},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5515000224113464},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.510200023651123},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.47870001196861267},{"id":"https://openalex.org/C145460709","wikidata":"https://www.wikidata.org/wiki/Q859951","display_name":"Human\u2013robot interaction","level":3,"score":0.4372999966144562},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4269999861717224},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.414000004529953},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.39980000257492065},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.38190001249313354},{"id":"https://openalex.org/C72634772","wikidata":"https://www.wikidata.org/wiki/Q386824","display_name":"Data integration","level":2,"score":0.3382999897003174},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.29789999127388},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2879999876022339},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.2777999937534332},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.274399995803833},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.2712000012397766},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.26429998874664307},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2628999948501587}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccma67641.2025.11369549","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccma67641.2025.11369549","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 13th International Conference on Control, Mechatronics and Automation (ICCMA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W2009119496","https://openalex.org/W2079537345","https://openalex.org/W2157883849","https://openalex.org/W2180635266","https://openalex.org/W2321254964","https://openalex.org/W2526578496","https://openalex.org/W2751303130","https://openalex.org/W2773432235","https://openalex.org/W2809786260","https://openalex.org/W2898898181","https://openalex.org/W2946490545","https://openalex.org/W2964165364","https://openalex.org/W2979737317","https://openalex.org/W3025798404","https://openalex.org/W3135450917","https://openalex.org/W3168997536","https://openalex.org/W3173512142","https://openalex.org/W3202774651","https://openalex.org/W3211522713","https://openalex.org/W4292261871","https://openalex.org/W4366250349","https://openalex.org/W4385489385","https://openalex.org/W4387123871","https://openalex.org/W4389051223","https://openalex.org/W4392657667","https://openalex.org/W4403919645"],"related_works":[],"abstract_inverted_index":{"Human":[0],"activity":[1],"recognition":[2],"(HAR)":[3],"involves":[4],"using":[5,87],"sensors":[6,113],"to":[7,15,58,97,151,197],"collect":[8],"human":[9],"data,":[10,63],"which":[11,67],"is":[12,29],"then":[13],"analyzed":[14],"identify":[16],"their":[17,141],"activities.":[18],"HAR":[19,52,78,99,144],"has":[20],"numerous":[21],"applications":[22],"across":[23],"various":[24,158,218],"fields.":[25],"One":[26],"significant":[27],"area":[28],"human-robot":[30],"interaction":[31],"(HRI).":[32],"Recognizing":[33],"user":[34,62,159,185,219],"activities":[35,160,220],"provides":[36],"robots":[37],"with":[38,71,90,108,174,190],"valuable":[39],"insights":[40],"into":[41],"the":[42,46,59,81,103,153,206,210],"user\u2019s":[43],"status,":[44],"enhancing":[45],"efficiency":[47],"of":[48,61,83,105],"HRI.":[49,162,222],"However,":[50],"developing":[51],"models":[53],"presents":[54],"privacy":[55],"challenges":[56],"due":[57],"collection":[60],"especially":[64],"in":[65,216],"robots,":[66],"are":[68,137,145],"often":[69],"equipped":[70],"diverse":[72],"sensors.":[73],"This":[74,163],"paper":[75,85,181],"proposes":[76],"privacy-preserving":[77,88,171],"methods":[79],"within":[80],"context":[82],"HRI.The":[84],"investigates":[86],"sensors,":[89,110,116,119,168,172],"a":[91,191,195],"particular":[92],"focus":[93],"on":[94],"3D":[95,106],"Lidar,":[96],"develop":[98],"models.":[100],"It":[101],"explores":[102],"integration":[104],"Lidar":[107],"other":[109],"including":[111,117,131,169,187],"user-wearable":[112],"and":[114,133,140,193],"robot-based":[115],"force/torque":[118],"through":[120],"multimodal":[121,154],"deep":[122],"learning":[123],"(DL)":[124],"approaches.":[125],"Various":[126],"DL-based":[127],"sensor":[128],"fusion":[129,135],"methods,":[130],"data-level":[132],"feature-level":[134,211],"approaches,":[136],"thoroughly":[138],"examined,":[139],"accuracies":[142],"for":[143,178],"compared.A":[146],"novel":[147],"dataset":[148,164],"was":[149],"collected":[150],"train":[152],"DL":[155],"models,":[156],"capturing":[157],"during":[161,221],"leverages":[165],"10":[166],"different":[167],"9":[170],"along":[173],"an":[175,213],"RGB":[176],"camera":[177],"reference.":[179],"The":[180,201],"considers":[182],"nine":[183],"distinct":[184],"activities,":[186],"physical":[188],"interactions":[189],"robot":[192,196],"commanding":[194],"perform":[198],"specific":[199],"tasks.":[200],"results":[202],"indicate":[203],"that":[204],"integrating":[205],"sensors\u2019":[207],"data":[208],"at":[209],"achieves":[212],"80.73%":[214],"accuracy":[215],"recognizing":[217]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-07T00:00:00"}
