{"id":"https://openalex.org/W4402666371","doi":"https://doi.org/10.1109/lra.2024.3466070","title":"Multimodal Active Measurement for Human Mesh Recovery in Close Proximity","display_name":"Multimodal Active Measurement for Human Mesh Recovery in Close Proximity","publication_year":2024,"publication_date":"2024-09-20","ids":{"openalex":"https://openalex.org/W4402666371","doi":"https://doi.org/10.1109/lra.2024.3466070"},"language":"en","primary_location":{"id":"doi:10.1109/lra.2024.3466070","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2024.3466070","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766","2377-3774"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-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/A5101638574","display_name":"Takahiro Maeda","orcid":"https://orcid.org/0000-0002-9911-6235"},"institutions":[{"id":"https://openalex.org/I4840577","display_name":"Toyota Technological Institute","ror":"https://ror.org/001hv0k59","country_code":"JP","type":"education","lineage":["https://openalex.org/I4840577"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takahiro Maeda","raw_affiliation_strings":["Toyota Technological Institute, Nagoya, Japan","Toyota Technological Institute, Nagoya, Aichi, Japan"],"raw_orcid":"https://orcid.org/0000-0002-9911-6235","affiliations":[{"raw_affiliation_string":"Toyota Technological Institute, Nagoya, Japan","institution_ids":["https://openalex.org/I4840577"]},{"raw_affiliation_string":"Toyota Technological Institute, Nagoya, Aichi, Japan","institution_ids":["https://openalex.org/I4840577"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042147200","display_name":"Keisuke Takeshita","orcid":"https://orcid.org/0000-0003-0942-0514"},"institutions":[{"id":"https://openalex.org/I4210137853","display_name":"Toyota Motor Corporation (Japan)","ror":"https://ror.org/02zqm6r10","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210125472","https://openalex.org/I4210137853"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Keisuke Takeshita","raw_affiliation_strings":["R-Frontier Division, Frontier Research Center, Toyota Motor Corporation, Aichi, Japan","R-Frontier Division, Frontier Research Center, Toyota Motor Corporation, Toyota, Aichi, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"R-Frontier Division, Frontier Research Center, Toyota Motor Corporation, Aichi, Japan","institution_ids":["https://openalex.org/I4210137853"]},{"raw_affiliation_string":"R-Frontier Division, Frontier Research Center, Toyota Motor Corporation, Toyota, Aichi, Japan","institution_ids":["https://openalex.org/I4210137853"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053167635","display_name":"Norimichi Ukita","orcid":"https://orcid.org/0000-0002-0240-1065"},"institutions":[{"id":"https://openalex.org/I4840577","display_name":"Toyota Technological Institute","ror":"https://ror.org/001hv0k59","country_code":"JP","type":"education","lineage":["https://openalex.org/I4840577"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Norimichi Ukita","raw_affiliation_strings":["Toyota Technological Institute, Nagoya, Japan","Toyota Technological Institute, Nagoya, Aichi, Japan"],"raw_orcid":"https://orcid.org/0000-0002-0240-1065","affiliations":[{"raw_affiliation_string":"Toyota Technological Institute, Nagoya, Japan","institution_ids":["https://openalex.org/I4840577"]},{"raw_affiliation_string":"Toyota Technological Institute, Nagoya, Aichi, Japan","institution_ids":["https://openalex.org/I4840577"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5104242922","display_name":"Kazuhito Tanaka","orcid":null},"institutions":[{"id":"https://openalex.org/I4210137853","display_name":"Toyota Motor Corporation (Japan)","ror":"https://ror.org/02zqm6r10","country_code":"JP","type":"company","lineage":["https://openalex.org/I4210125472","https://openalex.org/I4210137853"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kazuhito Tanaka","raw_affiliation_strings":["R-Frontier Division, Frontier Research Center, Toyota Motor Corporation, Aichi, Japan","R-Frontier Division, Frontier Research Center, Toyota Motor Corporation, Toyota, Aichi, Japan"],"raw_orcid":"https://orcid.org/0009-0001-7800-308X","affiliations":[{"raw_affiliation_string":"R-Frontier Division, Frontier Research Center, Toyota Motor Corporation, Aichi, Japan","institution_ids":["https://openalex.org/I4210137853"]},{"raw_affiliation_string":"R-Frontier Division, Frontier Research Center, Toyota Motor Corporation, Toyota, Aichi, Japan","institution_ids":["https://openalex.org/I4210137853"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.124,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.36693348,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"9","issue":"11","first_page":"9970","last_page":"9977"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.8985000252723694,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T12740","display_name":"Gait Recognition and Analysis","score":0.8985000252723694,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.805899977684021,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.8043000102043152,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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":0.4829675257205963}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4829675257205963}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2024.3466070","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2024.3466070","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766","2377-3774"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1967554269","https://openalex.org/W2080690152","https://openalex.org/W2483862638","https://openalex.org/W2559085405","https://openalex.org/W2605243700","https://openalex.org/W2797184202","https://openalex.org/W2885365305","https://openalex.org/W2895748257","https://openalex.org/W2898073175","https://openalex.org/W2947311533","https://openalex.org/W2963468256","https://openalex.org/W2963995996","https://openalex.org/W2964291722","https://openalex.org/W2964304707","https://openalex.org/W2970285700","https://openalex.org/W2981561950","https://openalex.org/W2990673575","https://openalex.org/W3035186639","https://openalex.org/W3035237020","https://openalex.org/W3035549967","https://openalex.org/W3107167007","https://openalex.org/W3128810022","https://openalex.org/W3161298928","https://openalex.org/W3171097378","https://openalex.org/W3175852502","https://openalex.org/W3203745449","https://openalex.org/W3204956438","https://openalex.org/W4200304330","https://openalex.org/W4214517305","https://openalex.org/W4214619583","https://openalex.org/W4214770715","https://openalex.org/W4312261745","https://openalex.org/W4312677021","https://openalex.org/W4312874524","https://openalex.org/W4383108563","https://openalex.org/W4390873180","https://openalex.org/W6637967152","https://openalex.org/W6780031573","https://openalex.org/W6786132994","https://openalex.org/W6860003303"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052","https://openalex.org/W2382290278","https://openalex.org/W4395014643"],"abstract_inverted_index":{"For":[0,67],"physical":[1,46],"human-robot":[2],"interactions":[3],"(pHRI),":[4],"a":[5,15,198],"robot":[6,24,44],"needs":[7],"to":[8,42,52,120,132,161],"estimate":[9],"the":[10,23,28,36,43,80,142,153,158,162,168,172,182],"accurate":[11],"body":[12,31,107,122],"pose":[13,65,165,170],"of":[14,63,79,144],"target":[16,29,37],"person.":[17],"However,":[18],"in":[19,60,70],"these":[20],"pHRI":[21],"scenarios,":[22],"cannot":[25],"fully":[26],"observe":[27],"person's":[30],"with":[32,83,124,186,202],"equipped":[33,81],"cameras":[34,82],"because":[35],"person":[38],"must":[39],"be":[40],"close":[41,49],"for":[45,104],"interaction.":[47],"This":[48],"distance":[50],"leads":[51],"severe":[53],"truncation":[54,133],"and":[55,57,85,93,101,114,146],"occlusions":[56],"thus":[58],"results":[59],"poor":[61],"accuracy":[62,69],"human":[64,106,195],"estimation.":[66],"better":[68],"this":[71],"challenging":[72],"environment,":[73],"we":[74,156],"propose":[75],"anactive":[76],"measurementandsensor":[77],"fusionframework":[78],"touch":[84,145],"ranging":[86,94,147],"sensors":[87,148],"such":[88,205],"as":[89,206],"2D":[90],"LiDAR.":[91],"Touch":[92],"sensor":[95,115,159],"measurements":[96,143,160],"are":[97,117,149],"sparse":[98],"but":[99],"reliable":[100,151],"informative":[102],"cues":[103],"localizing":[105],"parts.":[108],"In":[109,136],"ouractive":[110],"measurementprocess,":[111],"camera":[112],"viewpoints":[113],"placements":[116],"dynamically":[118],"optimized":[119],"measure":[121],"parts":[123],"higher":[125],"estimation":[126],"uncertainty,":[127],"which":[128],"is":[129],"closely":[130],"related":[131],"or":[134],"occlusion.":[135],"oursensor":[137],"fusion":[138],"process,":[139],"assuming":[140],"that":[141],"more":[150],"than":[152],"camera-based":[154,163],"estimations,":[155],"fuse":[157],"estimated":[164,169,194],"by":[166,208],"aligning":[167],"towards":[171],"measured":[173],"points.":[174],"Our":[175],"proposed":[176],"method":[177,192],"outperformed":[178],"previous":[179],"methods":[180],"on":[181],"standard":[183],"occlusion":[184,207],"benchmark":[185],"simulated":[187],"active":[188],"measurement.":[189],"Furthermore,":[190],"our":[191],"reliably":[193],"poses":[196],"using":[197],"real":[199],"robot,":[200],"even":[201],"practical":[203],"constraints":[204],"blankets.":[209]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-08-03T07:22:36.454288","created_date":"2025-10-10T00:00:00"}