{"id":"https://openalex.org/W3110852010","doi":"https://doi.org/10.1109/ismar50242.2020.00035","title":"An Efficient Planar Bundle Adjustment Algorithm","display_name":"An Efficient Planar Bundle Adjustment Algorithm","publication_year":2020,"publication_date":"2020-11-01","ids":{"openalex":"https://openalex.org/W3110852010","doi":"https://doi.org/10.1109/ismar50242.2020.00035","mag":"3110852010"},"language":"en","primary_location":{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/ismar50242.2020.00035","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},"type":"article","type_crossref":"proceedings-article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2006.00187","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060058992","display_name":"Lipu Zhou","orcid":"https://orcid.org/0000-0003-2148-393X"},"institutions":[{"id":"https://openalex.org/I4210148872","display_name":"Magic Leap (United States)","ror":"https://ror.org/058j17k65","country_code":"US","type":"company","lineage":["https://openalex.org/I4210148872"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lipu Zhou","raw_affiliation_strings":["Magic Leap"],"affiliations":[{"raw_affiliation_string":"Magic Leap","institution_ids":["https://openalex.org/I4210148872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033944804","display_name":"Daniel Koppel","orcid":null},"institutions":[{"id":"https://openalex.org/I4210148872","display_name":"Magic Leap (United States)","ror":"https://ror.org/058j17k65","country_code":"US","type":"company","lineage":["https://openalex.org/I4210148872"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Daniel Koppel","raw_affiliation_strings":["Magic Leap"],"affiliations":[{"raw_affiliation_string":"Magic Leap","institution_ids":["https://openalex.org/I4210148872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5059930482","display_name":"Hul Ju","orcid":null},"institutions":[{"id":"https://openalex.org/I4210148872","display_name":"Magic Leap (United States)","ror":"https://ror.org/058j17k65","country_code":"US","type":"company","lineage":["https://openalex.org/I4210148872"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hul Ju","raw_affiliation_strings":["Magic Leap"],"affiliations":[{"raw_affiliation_string":"Magic Leap","institution_ids":["https://openalex.org/I4210148872"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057772187","display_name":"Frank Steinbruecker","orcid":null},"institutions":[{"id":"https://openalex.org/I4210148872","display_name":"Magic Leap (United States)","ror":"https://ror.org/058j17k65","country_code":"US","type":"company","lineage":["https://openalex.org/I4210148872"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Frank Steinbruecker","raw_affiliation_strings":["Magic Leap"],"affiliations":[{"raw_affiliation_string":"Magic Leap","institution_ids":["https://openalex.org/I4210148872"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014216861","display_name":"Michael Kaess","orcid":"https://orcid.org/0000-0002-7590-3357"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"funder","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael Kaess","raw_affiliation_strings":["Carnegie Mellon University"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University","institution_ids":["https://openalex.org/I74973139"]}]}],"institution_assertions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.279,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.948467,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":93,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"136","last_page":"145"},"is_retracted":false,"is_paratext":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":1.0,"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":1.0,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9994,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9988,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/bundle-adjustment","display_name":"Bundle adjustment","score":0.8251104},{"id":"https://openalex.org/keywords/matrix","display_name":"Matrix (chemical analysis)","score":0.4462833},{"id":"https://openalex.org/keywords/least-squares-function-approximation","display_name":"Least-squares function approximation","score":0.418959}],"concepts":[{"id":"https://openalex.org/C200331156","wikidata":"https://www.wikidata.org/wiki/Q506041","display_name":"Jacobian matrix and determinant","level":2,"score":0.9044034},{"id":"https://openalex.org/C179458375","wikidata":"https://www.wikidata.org/wiki/Q1020763","display_name":"Bundle adjustment","level":3,"score":0.8251104},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.64060485},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.60066974},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5128296},{"id":"https://openalex.org/C134786449","wikidata":"https://www.wikidata.org/wiki/Q3391255","display_name":"Planar","level":2,"score":0.50977415},{"id":"https://openalex.org/C106487976","wikidata":"https://www.wikidata.org/wiki/Q685816","display_name":"Matrix (chemical analysis)","level":2,"score":0.4462833},{"id":"https://openalex.org/C17825722","wikidata":"https://www.wikidata.org/wiki/Q17285","display_name":"Plane (geometry)","level":2,"score":0.4358938},{"id":"https://openalex.org/C45923927","wikidata":"https://www.wikidata.org/wiki/Q3319230","display_name":"Non-linear least squares","level":3,"score":0.43185607},{"id":"https://openalex.org/C9936470","wikidata":"https://www.wikidata.org/wiki/Q6510405","display_name":"Least-squares function approximation","level":3,"score":0.418959},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38050398},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.37485507},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3267607},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.09822732},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09384808},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.08524141},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0},{"id":"https://openalex.org/C28826006","wikidata":"https://www.wikidata.org/wiki/Q33521","display_name":"Applied mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"is_oa":false,"landing_page_url":"https://doi.org/10.1109/ismar50242.2020.00035","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false},{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2006.00187","pdf_url":"https://arxiv.org/pdf/2006.00187","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false}],"best_oa_location":{"is_oa":true,"landing_page_url":"https://arxiv.org/abs/2006.00187","pdf_url":"https://arxiv.org/pdf/2006.00187","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_indexed_in_scopus":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":["Cornell University"],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false},"sustainable_development_goals":[{"score":0.75,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"grants":[],"datasets":[],"versions":[],"referenced_works_count":43,"referenced_works":["https://openalex.org/W145691285","https://openalex.org/W1484371059","https://openalex.org/W1592619852","https://openalex.org/W1968315983","https://openalex.org/W1987648924","https://openalex.org/W1992989752","https://openalex.org/W1994075312","https://openalex.org/W1996520948","https://openalex.org/W2001790138","https://openalex.org/W2013503831","https://openalex.org/W2033819227","https://openalex.org/W2070352439","https://openalex.org/W2080823437","https://openalex.org/W2110357983","https://openalex.org/W2112082021","https://openalex.org/W2124313187","https://openalex.org/W2132512702","https://openalex.org/W2133192850","https://openalex.org/W2171363519","https://openalex.org/W2236623899","https://openalex.org/W2256578114","https://openalex.org/W2277848489","https://openalex.org/W2471962767","https://openalex.org/W2560609797","https://openalex.org/W2563286913","https://openalex.org/W2566881119","https://openalex.org/W2738816079","https://openalex.org/W2779304298","https://openalex.org/W2798513908","https://openalex.org/W2798909945","https://openalex.org/W2886388988","https://openalex.org/W2887096906","https://openalex.org/W2892147056","https://openalex.org/W2895823395","https://openalex.org/W2908603664","https://openalex.org/W2909157769","https://openalex.org/W2946470536","https://openalex.org/W2968190521","https://openalex.org/W2987901038","https://openalex.org/W3000528040","https://openalex.org/W3089432818","https://openalex.org/W3100207723","https://openalex.org/W3102327032"],"related_works":["https://openalex.org/W4380487384","https://openalex.org/W4378552425","https://openalex.org/W327962130","https://openalex.org/W3030161631","https://openalex.org/W2939592218","https://openalex.org/W2359835307","https://openalex.org/W2026673180","https://openalex.org/W200101083","https://openalex.org/W1997338499","https://openalex.org/W1959514624"],"abstract_inverted_index":{"This":[0,106,199],"paper":[1,155],"presents":[2],"an":[3,157],"efficient":[4,158],"algorithm":[5,238,257],"for":[6,25,70,104,146,160,213],"the":[7,11,39,45,58,82,85,90,161,165,185,193,202,216,226,242,247,250,270,274],"least-squares":[8,31,143],"problem":[9,32,43,144,163],"using":[10,164,249,273],"point-to-plane":[12,166],"cost,":[13],"which":[14,136],"aims":[15],"to":[16,38,77,246,265,269],"jointly":[17],"optimize":[18],"depth":[19,72,123],"sensor":[20,124],"poses":[21],"and":[22,44,80,174,179,189,220,262],"plane":[23,132],"parameters":[24],"3D":[26,110,214],"reconstruction.":[27,52],"We":[28,168],"call":[29],"this":[30,42,154],"Planar":[33],"Bundle":[34,47],"Adjustment":[35,48],"(PBA),":[36],"due":[37],"similarity":[40],"between":[41],"original":[46,186],"(BA)":[49],"in":[50,57,67,94,99,130,138,192],"visual":[51,95],"As":[53],"planes":[54,207],"ubiquitously":[55],"exist":[56],"man-made":[59],"environment,":[60],"they":[61,182],"are":[62,208],"generally":[63,194],"used":[64],"as":[65],"landmarks":[66],"SLAM":[68],"algorithms":[69],"various":[71],"sensors.":[73],"PBA":[74,162],"is":[75,107,156,258],"important":[76],"reduce":[78,241],"drift":[79],"improve":[81],"quality":[83],"of":[84,128,153],"map.":[86],"However,":[87],"directly":[88],"adopting":[89],"well-established":[91],"BA":[92,252],"framework":[93],"reconstruction":[96],"will":[97],"result":[98],"a":[100,109,117,122,131,134,139,147,170,175],"very":[101,140],"inefficient":[102],"solution":[103,159,248,272],"PBA.":[105],"because":[108],"point":[111],"only":[112],"has":[113],"one":[114],"observation":[115],"at":[116,133],"camera":[118],"pose.":[119],"In":[120,254],"contrast,":[121],"can":[125,183,223,239],"record":[126],"hundreds":[127],"points":[129],"time,":[135],"results":[137,234],"large":[141],"nonlinear":[142],"even":[145],"small-scale":[148],"space.":[149],"The":[150],"main":[151],"contribution":[152],"cost.":[167,204],"introduce":[169],"reduced":[171,176,217],"Jacobian":[172,187,218],"matrix":[173,188,219],"residual":[177,190,221],"vector,":[178],"prove":[180],"that":[181,236],"replace":[184,225],"vector":[191,222],"adopted":[195],"Levenberg-Marquardt":[196],"(LM)":[197],"algorithm.":[198],"significantly":[200,240],"reduces":[201],"computational":[203,243],"Besides,":[205],"when":[206],"combined":[209],"with":[210],"other":[211],"features":[212],"reconstruction,":[215],"also":[224],"corresponding":[227],"parts":[228],"derived":[229],"from":[230],"planes.":[231],"Our":[232],"experimental":[233],"show":[235],"our":[237,256],"time":[244],"compared":[245,268],"traditional":[251],"framework.":[253],"addition,":[255],"faster,":[259],"more":[260,263],"accurate,":[261],"robust":[264],"initialization":[266],"errors":[267],"start-of-the-art":[271],"plane-to-plane":[275],"cost":[276],"[3].":[277]},"abstract_inverted_index_v3":null,"cited_by_api_url":"https://api.openalex.org/works?filter=cites:W3110852010","counts_by_year":[{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":1}],"updated_date":"2025-02-25T03:15:40.265323","created_date":"2020-12-21"}