{"id":"https://openalex.org/W4382317332","doi":"https://doi.org/10.3390/jimaging12060247","title":"A Robust 3D Registration Method via Simultaneous Inlier Identification and Model Estimation","display_name":"A Robust 3D Registration Method via Simultaneous Inlier Identification and Model Estimation","publication_year":2026,"publication_date":"2026-06-01","ids":{"openalex":"https://openalex.org/W4382317332","doi":"https://doi.org/10.3390/jimaging12060247","pmid":"https://pubmed.ncbi.nlm.nih.gov/42346910"},"language":"en","primary_location":{"id":"doi:10.3390/jimaging12060247","is_oa":true,"landing_page_url":"https://doi.org/10.3390/jimaging12060247","pdf_url":null,"source":{"id":"https://openalex.org/S2736465063","display_name":"Journal of Imaging","issn_l":"2313-433X","issn":["2313-433X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Imaging","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","datacite","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.3390/jimaging12060247","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5108482499","display_name":"Xianyun Qian","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xianyun Qian","raw_affiliation_strings":["School of Integrated Circuits, Shanghai Jiao Tong University, Shanghai 200240, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Integrated Circuits, Shanghai Jiao Tong University, Shanghai 200240, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5143165392","display_name":"Fei Wen","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Fei Wen","raw_affiliation_strings":["School of Integrated Circuits, Shanghai Jiao Tong University, Shanghai 200240, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Integrated Circuits, Shanghai Jiao Tong University, Shanghai 200240, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032986088","display_name":"Peilin Liu","orcid":"https://orcid.org/0000-0002-5321-2336"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peilin Liu","raw_affiliation_strings":["School of Integrated Circuits, Shanghai Jiao Tong University, Shanghai 200240, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Integrated Circuits, Shanghai Jiao Tong University, Shanghai 200240, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":{"value":1600,"currency":"CHF","value_usd":1782},"apc_paid":{"value":1600,"currency":"CHF","value_usd":1782},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.00100364,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"12","issue":"6","first_page":"247","last_page":"247"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9872999787330627,"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"}},"topics":[{"id":"https://openalex.org/T10500","display_name":"Sparse and Compressive Sensing Techniques","score":0.9872999787330627,"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"}},{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9857000112533569,"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"}},{"id":"https://openalex.org/T12072","display_name":"Machine Learning and Algorithms","score":0.9797999858856201,"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/outlier","display_name":"Outlier","score":0.8331049680709839},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.7171474695205688},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.665030837059021},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6303229928016663},{"id":"https://openalex.org/keywords/ransac","display_name":"RANSAC","score":0.6166055798530579},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5155008435249329},{"id":"https://openalex.org/keywords/relaxation","display_name":"Relaxation (psychology)","score":0.5018467903137207},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4889456033706665},{"id":"https://openalex.org/keywords/robust-statistics","display_name":"Robust statistics","score":0.46618813276290894},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.44247156381607056},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3662624955177307},{"id":"https://openalex.org/keywords/applied-mathematics","display_name":"Applied mathematics","score":0.3371769189834595},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.28828567266464233},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19436269998550415},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1384117603302002}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.8331049680709839},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.7171474695205688},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.665030837059021},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6303229928016663},{"id":"https://openalex.org/C114744707","wikidata":"https://www.wikidata.org/wiki/Q218533","display_name":"RANSAC","level":3,"score":0.6166055798530579},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5155008435249329},{"id":"https://openalex.org/C2776029896","wikidata":"https://www.wikidata.org/wiki/Q3935810","display_name":"Relaxation (psychology)","level":2,"score":0.5018467903137207},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4889456033706665},{"id":"https://openalex.org/C67226441","wikidata":"https://www.wikidata.org/wiki/Q1665389","display_name":"Robust statistics","level":3,"score":0.46618813276290894},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.44247156381607056},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3662624955177307},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.3371769189834595},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.28828567266464233},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19436269998550415},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1384117603302002},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0}],"mesh":[],"locations_count":6,"locations":[{"id":"doi:10.3390/jimaging12060247","is_oa":true,"landing_page_url":"https://doi.org/10.3390/jimaging12060247","pdf_url":null,"source":{"id":"https://openalex.org/S2736465063","display_name":"Journal of Imaging","issn_l":"2313-433X","issn":["2313-433X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Imaging","raw_type":"journal-article"},{"id":"pmid:42346910","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/42346910","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of imaging","raw_type":"Journal Article"},{"id":"pmh:oai:arXiv.org:2008.01574","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2008.01574","pdf_url":"https://arxiv.org/pdf/2008.01574","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"text"},{"id":"pmh:oai:doaj.org/article:26b7b8a5fd3340569d55e6a85d21ab35","is_oa":false,"landing_page_url":"https://doaj.org/article/26b7b8a5fd3340569d55e6a85d21ab35","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Journal of Imaging, Vol 12, Iss 6, p 247 (2026)","raw_type":"article"},{"id":"pmh:oai:pubmedcentral.nih.gov:13301893","is_oa":true,"landing_page_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC13301893/","pdf_url":null,"source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"J Imaging","raw_type":"Text"},{"id":"doi:10.48550/arxiv.2008.01574","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2008.01574","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.3390/jimaging12060247","is_oa":true,"landing_page_url":"https://doi.org/10.3390/jimaging12060247","pdf_url":null,"source":{"id":"https://openalex.org/S2736465063","display_name":"Journal of Imaging","issn_l":"2313-433X","issn":["2313-433X"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Imaging","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.7099999785423279,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2769402452","https://openalex.org/W2091258128","https://openalex.org/W1983540692","https://openalex.org/W4313645560","https://openalex.org/W2046343964","https://openalex.org/W4379515847","https://openalex.org/W2216963642","https://openalex.org/W2283061017","https://openalex.org/W3121734683","https://openalex.org/W4210897550"],"abstract_inverted_index":{"Robust":[0],"3D":[1,105,132,199,285],"registration":[2,36,205,216,271,286],"is":[3,15],"a":[4,61,87,112,145,269],"fundamental":[5],"problem":[6],"in":[7,26,128,230,261,287],"computer":[8,290],"vision":[9],"and":[10,31,51,89,97,121,125,172,202,214,233,251,292],"robotics,":[11,289],"where":[12],"the":[13,18,27,54,129,155,161,185,189,195,220,237,240,279],"goal":[14],"to":[16,183,249],"estimate":[17,53],"geometric":[19,293],"transformation":[20,99],"between":[21],"two":[22],"sets":[23],"of":[24,29,131,274,281],"measurements":[25],"presence":[28],"noise":[30,232],"outlier":[32,246],"contamination.":[33],"Existing":[34],"robust":[35,62,140],"methods":[37,66,222,242],"are":[38,243],"mainly":[39],"built":[40],"on":[41,211],"either":[42],"maximum":[43],"consensus":[44],"(MC)":[45],"estimators,":[46],"which":[47,58],"first":[48],"identify":[49],"inliers":[50],"then":[52],"transformation,":[55],"or":[56,255],"M-estimators,":[57],"directly":[59],"optimize":[60],"objective.":[63],"However,":[64],"MC-based":[65,139],"typically":[67],"ignore":[68],"residual":[69,148,152],"magnitudes":[70,153],"during":[71],"inlier":[72,95,119,156,191],"selection,":[73],"while":[74],"many":[75],"M-estimators":[76],"do":[77],"not":[78],"explicitly":[79],"couple":[80],"inlier/outlier":[81],"identification":[82,96,120],"with":[83,138,179,225,258],"model":[84,122],"estimation.":[85],"Thus,":[86],"unified":[88,113],"efficient":[90],"framework":[91,197],"that":[92,219],"jointly":[93],"performs":[94],"accurate":[98],"estimation":[100,123],"remains":[101],"desirable":[102],"for":[103,117,198,283],"challenging":[104],"registration.":[106,133],"In":[107,236],"this":[108],"work,":[109],"we":[110,165],"introduce":[111],"truncated-loss":[114],"based":[115],"formulation":[116],"simultaneous":[118],"(SIME)":[124],"study":[126],"it":[127,150],"context":[130],"We":[134,193],"show":[135,278],"that,":[136],"compared":[137],"fitting,":[141],"SIME":[142,266,282],"can":[143],"achieve":[144,253],"lower":[146],"fitting":[147],"because":[149],"incorporates":[151],"into":[154],"selection":[157],"process.":[158],"To":[159],"solve":[160],"resulting":[162],"nonconvex":[163],"problem,":[164],"develop":[166],"an":[167,175],"alternating":[168],"minimization":[169],"(AM)":[170,267],"algorithm,":[171],"further":[173],"propose":[174],"AM":[176],"method":[177],"embedded":[178],"semidefinite":[180],"relaxation":[181],"(AM-R)":[182],"alleviate":[184],"difficulty":[186],"caused":[187],"by":[188],"binary":[190],"variables.":[192],"instantiate":[194],"proposed":[196,221,241],"rotation":[200],"search":[201],"rigid":[203],"point-set":[204],"using":[206],"quaternion-based":[207],"formulations.":[208],"Experimental":[209],"results":[210,277],"both":[212],"simulated":[213],"real-world":[215],"tasks":[217],"demonstrate":[218],"compare":[223],"favorably":[224],"strong":[226],"baseline":[227],"solvers,":[228],"especially":[229],"high":[231],"extreme":[234],"outliers.":[235],"synthetic":[238],"experiments,":[239],"evaluated":[244],"under":[245],"ratios":[247],"up":[248],"95%":[250],"consistently":[252],"competitive":[254],"better":[256],"accuracy,":[257],"clear":[259],"advantages":[260],"high-noise":[262],"cases.":[263],"On":[264],"3DMatch,":[265],"achieves":[268],"mean":[270],"success":[272],"rate":[273],"91.0%.":[275],"These":[276],"potential":[280],"reliable":[284],"practical":[288],"vision,":[291],"perception":[294],"applications.":[295]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2025-10-10T00:00:00"}