{"id":"https://openalex.org/W2946305700","doi":"https://doi.org/10.1109/tase.2019.2914306","title":"Robust Generalized Point Cloud Registration With Orientational Data Based on Expectation Maximization","display_name":"Robust Generalized Point Cloud Registration With Orientational Data Based on Expectation Maximization","publication_year":2019,"publication_date":"2019-05-21","ids":{"openalex":"https://openalex.org/W2946305700","doi":"https://doi.org/10.1109/tase.2019.2914306","mag":"2946305700"},"language":"en","primary_location":{"id":"doi:10.1109/tase.2019.2914306","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2019.2914306","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"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 Transactions on Automation Science and Engineering","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/A5040071840","display_name":"Zhe Min","orcid":"https://orcid.org/0000-0002-8903-1561"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Zhe Min","raw_affiliation_strings":["Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong"],"raw_orcid":"https://orcid.org/0000-0002-8903-1561","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5048709541","display_name":"Jiaole Wang","orcid":"https://orcid.org/0000-0002-0941-8003"},"institutions":[{"id":"https://openalex.org/I111088046","display_name":"Boston University","ror":"https://ror.org/05qwgg493","country_code":"US","type":"education","lineage":["https://openalex.org/I111088046"]},{"id":"https://openalex.org/I1288882113","display_name":"Boston Children's Hospital","ror":"https://ror.org/00dvg7y05","country_code":"US","type":"healthcare","lineage":["https://openalex.org/I1288882113"]},{"id":"https://openalex.org/I136199984","display_name":"Harvard University","ror":"https://ror.org/03vek6s52","country_code":"US","type":"education","lineage":["https://openalex.org/I136199984"]},{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["HK","US"],"is_corresponding":false,"raw_author_name":"Jiaole Wang","raw_affiliation_strings":["Department of Cardiovascular Surgery, Boston Children\u2019s Hospital, Pediatric Cardiac Bioengineering Laboratory, Harvard Medical School, Boston, USA","Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong","Department of Cardiovascular Surgery, Boston Children's Hospital, Pediatric Cardiac Bioengineering Laboratory, Harvard Medical School, Boston, USA"],"raw_orcid":"https://orcid.org/0000-0002-0941-8003","affiliations":[{"raw_affiliation_string":"Department of Cardiovascular Surgery, Boston Children\u2019s Hospital, Pediatric Cardiac Bioengineering Laboratory, Harvard Medical School, Boston, USA","institution_ids":["https://openalex.org/I136199984","https://openalex.org/I1288882113"]},{"raw_affiliation_string":"Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]},{"raw_affiliation_string":"Department of Cardiovascular Surgery, Boston Children's Hospital, Pediatric Cardiac Bioengineering Laboratory, Harvard Medical School, Boston, USA","institution_ids":["https://openalex.org/I1288882113","https://openalex.org/I111088046","https://openalex.org/I136199984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5021531143","display_name":"Max Q.\u2010H. Meng","orcid":"https://orcid.org/0000-0002-5255-5898"},"institutions":[{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"HK","type":"education","lineage":["https://openalex.org/I177725633"]},{"id":"https://openalex.org/I4210116924","display_name":"Chinese University of Hong Kong, Shenzhen","ror":"https://ror.org/02d5ks197","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633","https://openalex.org/I180726961","https://openalex.org/I4210116924"]}],"countries":["CN","HK"],"is_corresponding":false,"raw_author_name":"Max Q.-H. Meng","raw_affiliation_strings":["Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong","Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-5255-5898","affiliations":[{"raw_affiliation_string":"Department of Electronic Engineering, The Chinese University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]},{"raw_affiliation_string":"Shenzhen Research Institute, The Chinese University of Hong Kong, Shenzhen, China","institution_ids":["https://openalex.org/I4210116924"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":48.5689,"has_fulltext":false,"cited_by_count":49,"citation_normalized_percentile":{"value":0.99620598,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"17","issue":"1","first_page":"207","last_page":"221"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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":0.9986000061035156,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9976000189781189,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/robustness","display_name":"Robustness (evolution)","score":0.7066550254821777},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.6776427626609802},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6750365495681763},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.6612891554832458},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.4976678192615509},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.4923652410507202},{"id":"https://openalex.org/keywords/point-set-registration","display_name":"Point set registration","score":0.4809107780456543},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.4576598107814789},{"id":"https://openalex.org/keywords/rigid-transformation","display_name":"Rigid transformation","score":0.4424183964729309},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4395899176597595},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.4250739812850952},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.4185258448123932},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.40081119537353516},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3564871549606323},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3405541777610779},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.21985462307929993},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.1015760600566864}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7066550254821777},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.6776427626609802},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6750365495681763},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.6612891554832458},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.4976678192615509},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4923652410507202},{"id":"https://openalex.org/C200336642","wikidata":"https://www.wikidata.org/wiki/Q15058706","display_name":"Point set registration","level":3,"score":0.4809107780456543},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.4576598107814789},{"id":"https://openalex.org/C126795593","wikidata":"https://www.wikidata.org/wiki/Q7333813","display_name":"Rigid transformation","level":2,"score":0.4424183964729309},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4395899176597595},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.4250739812850952},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4185258448123932},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.40081119537353516},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3564871549606323},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3405541777610779},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.21985462307929993},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.1015760600566864},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tase.2019.2914306","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tase.2019.2914306","pdf_url":null,"source":{"id":"https://openalex.org/S34881539","display_name":"IEEE Transactions on Automation Science and Engineering","issn_l":"1545-5955","issn":["1545-5955","1558-3783"],"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 Transactions on Automation Science and Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6931088166","display_name":null,"funder_award_id":"ITS/236/15","funder_id":"https://openalex.org/F4320321920","funder_display_name":"Innovation and Technology Commission"}],"funders":[{"id":"https://openalex.org/F4320321920","display_name":"Innovation and Technology Commission","ror":"https://ror.org/04vf9tr09"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W78351518","https://openalex.org/W327180933","https://openalex.org/W1599434464","https://openalex.org/W1601795611","https://openalex.org/W1663973292","https://openalex.org/W1678863187","https://openalex.org/W1953793983","https://openalex.org/W1966906328","https://openalex.org/W1970642064","https://openalex.org/W1984905474","https://openalex.org/W1988874269","https://openalex.org/W1994104838","https://openalex.org/W2015901765","https://openalex.org/W2049633694","https://openalex.org/W2049981393","https://openalex.org/W2055611542","https://openalex.org/W2059569291","https://openalex.org/W2074199334","https://openalex.org/W2074693620","https://openalex.org/W2084461520","https://openalex.org/W2097832352","https://openalex.org/W2104673011","https://openalex.org/W2114354851","https://openalex.org/W2133476816","https://openalex.org/W2134236847","https://openalex.org/W2141085506","https://openalex.org/W2142529775","https://openalex.org/W2143711534","https://openalex.org/W2145001205","https://openalex.org/W2150190641","https://openalex.org/W2164703480","https://openalex.org/W2271206385","https://openalex.org/W2338121015","https://openalex.org/W2342833881","https://openalex.org/W2594495318","https://openalex.org/W2604257183","https://openalex.org/W2654024950","https://openalex.org/W2736526012","https://openalex.org/W2738467687","https://openalex.org/W2740578684","https://openalex.org/W2745964468","https://openalex.org/W2749287221","https://openalex.org/W2751378974","https://openalex.org/W2762011240","https://openalex.org/W2765600535","https://openalex.org/W2774328584","https://openalex.org/W2810468710","https://openalex.org/W2889784867","https://openalex.org/W2924259647","https://openalex.org/W2941298512","https://openalex.org/W2942351283","https://openalex.org/W4249866455","https://openalex.org/W6602879910","https://openalex.org/W6603199352","https://openalex.org/W6635897114","https://openalex.org/W6682124274","https://openalex.org/W6743181058","https://openalex.org/W6745967568"],"related_works":["https://openalex.org/W2473373438","https://openalex.org/W2368486525","https://openalex.org/W2077224612","https://openalex.org/W2153481672","https://openalex.org/W2153238387","https://openalex.org/W4312864369","https://openalex.org/W84255947","https://openalex.org/W2014842417","https://openalex.org/W2891133681","https://openalex.org/W2968374624"],"abstract_inverted_index":{"This":[0,268],"paper":[1,236,269],"introduces":[2],"a":[3,36,44,64,77,172,204,271,291],"robust":[4,273],"generalized":[5,59,116],"point":[6,156,259],"cloud":[7],"(PC)":[8],"registration":[9,33,286,328],"method":[10,28,219,274],"that":[11,151,216,275,325],"utilizes":[12],"not":[13],"only":[14,252],"the":[15,19,30,41,62,73,86,97,106,111,137,145,148,153,164,217,221,241,253,278,299,326],"positional":[16,87,254],"but":[17],"also":[18,276],"orientation":[20],"information":[21,130,255],"associated":[22,256,281],"with":[23,257,282],"each":[24,258,283],"point.":[25,284],"The":[26,285],"proposed":[27,218,327],"solves":[29],"rigid":[31,173],"PC":[32],"problem":[34,42,99,242,287,295],"in":[35,100,158,224,308,316],"probabilistic":[37],"manner,":[38],"which":[39,133],"casts":[40],"into":[43,290],"maximum":[45,292],"likelihood":[46,293],"(ML)":[47,294],"framework.":[48,302],"A":[49],"hybrid":[50],"mixture":[51,66,79],"model":[52,67,72,80],"(HMM)":[53],"is":[54,69,82,93,131,176,288],"utilized":[55],"to":[56,71,84,95,104,140,171,234,264,334],"represent":[57,85,152],"one":[58],"PC.":[60],"In":[61,118,144,163],"HMM,":[63],"von-Mises-Fisher":[65],"(FMM)":[68],"adopted":[70,94],"orientational":[74,129],"uncertainty,":[75],"while":[76],"Gaussian":[78],"(GMM)":[81],"used":[83],"uncertainty.":[88],"An":[89],"expectation-maximization":[90,300],"(EM)":[91,301],"algorithm":[92,329],"solve":[96],"optimization":[98],"an":[101,167],"iterative":[102],"manner":[103],"find":[105],"optimal":[107],"rotation":[108],"matrix":[109,175],"and":[110,124,142,179,196,229,260,266,296,311,336,338],"translation":[112],"vector":[113],"between":[114],"two":[115,159,245],"PCs.":[117,246],"both":[119,309],"expectation":[120,310],"step":[121,126],"(E":[122],"step)":[123],"maximization":[125,312],"(M":[127],"step),":[128],"utilized,":[132],"can":[134],"potentially":[135],"improve":[136],"algorithm's":[138],"robustness":[139,263,333],"noise":[141,194,265,335],"outliers.":[143,267],"E":[146,178],"step,":[147,166],"posterior":[149],"probabilities":[150],"degree":[154],"of":[155,207,226,243],"correspondences":[157],"PCs":[160],"are":[161,188,314],"computed.":[162],"M":[165,180],"efficient":[168],"closed-form":[169],"solution":[170],"transformation":[174],"developed.":[177],"steps":[181,313],"will":[182],"iterate":[183],"until":[184],"certain":[185],"convergence":[186,230,340],"criteria":[187],"satisfied.":[189],"Extensive":[190],"experiments":[191,324],"under":[192,298],"different":[193],"levels":[195],"outlier":[197],"ratios":[198],"have":[199,320],"been":[200],"carried":[201],"out":[202],"on":[203],"data":[205],"set":[206],"femur":[208],"bone":[209],"computed":[210],"tomography":[211],"images.":[212],"Experimental":[213],"results":[214],"show":[215],"outperforms":[220],"state-of-the-art":[222],"ones":[223],"terms":[225],"accuracy,":[227,332],"robustness,":[228],"speed":[231],"significantly.":[232],"Note":[233],"Practitioners-This":[235],"was":[237],"motivated":[238],"by":[239],"solving":[240],"registering":[244],"Most":[247],"existing":[248],"approaches":[249],"generally":[250],"use":[251],"thus":[261],"lack":[262],"suggests":[270],"new":[272],"adopts":[277],"normal":[279],"vectors":[280],"cast":[289],"solved":[297],"Closed-form":[303],"solutions":[304],"for":[305],"estimating":[306],"parameters":[307],"provided":[315],"this":[317],"paper.":[318],"We":[319],"demonstrated":[321],"through":[322],"extensive":[323],"achieves":[330],"improved":[331],"outliers,":[337],"faster":[339],"speed.":[341]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":5}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
