{"id":"https://openalex.org/W3133710162","doi":"https://doi.org/10.48550/arxiv.2103.04357","title":"IRON: Invariant-based Highly Robust Point Cloud Registration","display_name":"IRON: Invariant-based Highly Robust Point Cloud Registration","publication_year":2021,"publication_date":"2021-03-07","ids":{"openalex":"https://openalex.org/W3133710162","doi":"https://doi.org/10.48550/arxiv.2103.04357","mag":"3133710162"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2103.04357","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2103.04357","pdf_url":"https://arxiv.org/pdf/2103.04357","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,"listed_in":[],"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":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2103.04357","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049126624","display_name":"Lei Sun","orcid":"https://orcid.org/0000-0003-4135-6858","observed_orcids":["https://orcid.org/0000-0003-4135-6858"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Sun, Lei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5049126624"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9682999849319458,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9682999849319458,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.004900000058114529,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.0035000001080334187,"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/point-cloud-registration","display_name":"point cloud registration","score":0.9980000257492065},{"id":"https://openalex.org/keywords/robust-estimation","display_name":"robust estimation","score":0.7210000157356262},{"id":"https://openalex.org/keywords/outlier-removal","display_name":"outlier removal","score":0.8050000071525574},{"id":"https://openalex.org/keywords/scale-estimation","display_name":"scale estimation","score":0.7360000014305115},{"id":"https://openalex.org/keywords/semidefinite-programming","display_name":"semidefinite programming","score":0.7120000123977661},{"id":"https://openalex.org/keywords/sum-of-squares-relaxation","display_name":"sum-of-squares relaxation","score":0.9959999918937683},{"id":"https://openalex.org/keywords/graduated-non-convexity","display_name":"graduated non-convexity","score":0.8970000147819519}],"concepts":[{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7615208625793457},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.581628680229187},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5639772415161133},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.5512413382530212},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.513006865978241},{"id":"https://openalex.org/C112680207","wikidata":"https://www.wikidata.org/wiki/Q714886","display_name":"Regular polygon","level":2,"score":0.47230079770088196},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.4702170193195343},{"id":"https://openalex.org/C72134830","wikidata":"https://www.wikidata.org/wiki/Q5166524","display_name":"Convexity","level":2,"score":0.44537100195884705},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.431438684463501},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4097108244895935},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3527287244796753},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","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},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2103.04357","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2103.04357","pdf_url":"https://arxiv.org/pdf/2103.04357","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,"listed_in":[],"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":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2103.04357","doi":"https://doi.org/10.48550/arxiv.2103.04357","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2103.04357","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,"listed_in":[],"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":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2103.04357","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2103.04357","pdf_url":"https://arxiv.org/pdf/2103.04357","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,"listed_in":[],"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":null,"raw_type":"text"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[{"id":"https://metadata.un.org/sdg/17","score":0.4099999964237213,"display_name":"Partnerships for the goals"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1567562836","https://openalex.org/W1957167950","https://openalex.org/W1965805571","https://openalex.org/W1967073510","https://openalex.org/W1967344706","https://openalex.org/W1972671602","https://openalex.org/W1977077642","https://openalex.org/W1988874269","https://openalex.org/W1993267444","https://openalex.org/W2007200979","https://openalex.org/W2009422376","https://openalex.org/W2025303841","https://openalex.org/W2033819227","https://openalex.org/W2049981393","https://openalex.org/W2067956279","https://openalex.org/W2071992612","https://openalex.org/W2085261163","https://openalex.org/W2086465792","https://openalex.org/W2088616581","https://openalex.org/W2090967418","https://openalex.org/W2098764590","https://openalex.org/W2115001439","https://openalex.org/W2134834581","https://openalex.org/W2156222070","https://openalex.org/W2160821342","https://openalex.org/W2161168419","https://openalex.org/W2296228853","https://openalex.org/W2745007981","https://openalex.org/W2749287221","https://openalex.org/W2769591697","https://openalex.org/W2923955646","https://openalex.org/W2962729173","https://openalex.org/W2973258311","https://openalex.org/W2981874330","https://openalex.org/W3034494757","https://openalex.org/W3111598592","https://openalex.org/W3118263378","https://openalex.org/W3207682209"],"related_works":["https://openalex.org/W1964872188","https://openalex.org/W2187391117","https://openalex.org/W1981809986","https://openalex.org/W2949367465","https://openalex.org/W2587048717","https://openalex.org/W2912909874","https://openalex.org/W4288573727","https://openalex.org/W2494876756","https://openalex.org/W2768754015","https://openalex.org/W2981448761"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,34,125,154,166],"present":[4],"IRON":[5,169],"(Invariant-based":[6],"global":[7,98,135],"Robust":[8],"estimation":[9,41],"and":[10,14,45,71,115,131,142,174],"OptimizatioN),":[11],"a":[12,23,102,108,134],"non-minimal":[13],"highly":[15,172],"robust":[16,123,175],"solution":[17],"for":[18],"point":[19,80],"cloud":[20],"registration":[21,37,99,158],"with":[22,57],"great":[24],"number":[25],"of":[26,42,79],"outliers":[27,181],"among":[28],"the":[29,36,40,62,74,83,86,96,118,183,190],"correspondences.":[30],"To":[31],"realize":[32],"this,":[33],"decouple":[35],"problem":[38,100],"into":[39,101],"scale,":[43],"rotation":[44],"translation,":[46],"respectively.":[47],"Our":[48],"first":[49],"contribution":[50,92],"is":[51,88,93,120,170,185],"to":[52,65,94],"propose":[53,127],"RANSIC":[54],"(RANdom":[55],"Samples":[56],"Invariant":[58],"Compatibility),":[59],"which":[60],"employs":[61],"invariant":[63],"compatibility":[64],"seek":[66],"inliers":[67],"from":[68],"random":[69],"samples":[70],"robustly":[72],"estimates":[73],"scale":[75,87,184],"between":[76],"two":[77],"sets":[78],"clouds":[81],"in":[82,107],"meantime.":[84],"Once":[85],"estimated,":[89],"our":[90,148,157],"second":[91],"relax":[95],"non-convex":[97],"convex":[103],"Semi-Definite":[104],"Program":[105],"(SDP)":[106],"certifiable":[109],"way":[110],"using":[111],"Sum-of-Squares":[112],"(SOS)":[113],"Relaxation":[114],"show":[116,167],"that":[117,168],"relaxation":[119],"tight.":[121],"For":[122],"estimation,":[124],"further":[126],"RT-GNC":[128],"(Rough":[129],"Trimming":[130],"Graduated":[132],"Non-Convexity),":[133],"outlier":[136],"rejection":[137],"heuristic":[138],"having":[139],"better":[140],"robustness":[141],"time-efficiency":[143],"than":[144],"traditional":[145],"GNC,":[146],"as":[147,177,179],"third":[149],"contribution.":[150],"With":[151],"these":[152],"contributions,":[153],"can":[155],"render":[156],"algorithm,":[159],"IRON.":[160],"Through":[161],"experiments":[162],"over":[163],"real":[164],"datasets,":[165],"efficient,":[171],"accurate":[173],"against":[176],"many":[178],"99%":[180],"whether":[182],"known":[186],"or":[187],"unknown,":[188],"outperforming":[189],"existing":[191],"state-of-the-art":[192],"algorithms.":[193]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2025-10-10T00:00:00"}
