{"id":"https://openalex.org/W3126148377","doi":"https://doi.org/10.1109/3dv50981.2020.00076","title":"Visualizing Spectral Bundle Adjustment Uncertainty","display_name":"Visualizing Spectral Bundle Adjustment Uncertainty","publication_year":2020,"publication_date":"2020-11-01","ids":{"openalex":"https://openalex.org/W3126148377","doi":"https://doi.org/10.1109/3dv50981.2020.00076","mag":"3126148377"},"language":"en","primary_location":{"id":"doi:10.1109/3dv50981.2020.00076","is_oa":false,"landing_page_url":"https://doi.org/10.1109/3dv50981.2020.00076","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on 3D Vision (3DV)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5091086473","display_name":"Kyle Wilson","orcid":"https://orcid.org/0009-0007-2374-6330"},"institutions":[{"id":"https://openalex.org/I24796534","display_name":"Washington College","ror":"https://ror.org/02vk0qj37","country_code":"US","type":"education","lineage":["https://openalex.org/I24796534"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kyle Wilson","raw_affiliation_strings":["Washington College, Chestertown, MD"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Washington College, Chestertown, MD","institution_ids":["https://openalex.org/I24796534"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013922391","display_name":"Scott Wehrwein","orcid":"https://orcid.org/0000-0002-1199-0412"},"institutions":[{"id":"https://openalex.org/I52669646","display_name":"Western Washington University","ror":"https://ror.org/05wn7r715","country_code":"US","type":"education","lineage":["https://openalex.org/I52669646"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Scott Wehrwein","raw_affiliation_strings":["Western Washington University, Bellingham, WA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Western Washington University, Bellingham, WA","institution_ids":["https://openalex.org/I52669646"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.18881955,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"663","last_page":"671"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9972000122070312,"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"}},"topics":[{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9972000122070312,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.996399998664856,"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/T11583","display_name":"Advanced Measurement and Metrology Techniques","score":0.991100013256073,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/bundle-adjustment","display_name":"Bundle adjustment","score":0.7928773760795593},{"id":"https://openalex.org/keywords/bundle","display_name":"Bundle","score":0.7212192416191101},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.6537076234817505},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5842908620834351},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.5793346166610718},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.5559294819831848},{"id":"https://openalex.org/keywords/structure-from-motion","display_name":"Structure from motion","score":0.46187734603881836},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.43580490350723267},{"id":"https://openalex.org/keywords/uncertainty-quantification","display_name":"Uncertainty quantification","score":0.4275257885456085},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.40708523988723755},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.34976738691329956},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2767128646373749},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.243274986743927},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.19778713583946228},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.11158442497253418}],"concepts":[{"id":"https://openalex.org/C179458375","wikidata":"https://www.wikidata.org/wiki/Q1020763","display_name":"Bundle adjustment","level":3,"score":0.7928773760795593},{"id":"https://openalex.org/C2778134712","wikidata":"https://www.wikidata.org/wiki/Q1047307","display_name":"Bundle","level":2,"score":0.7212192416191101},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.6537076234817505},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5842908620834351},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.5793346166610718},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.5559294819831848},{"id":"https://openalex.org/C146159030","wikidata":"https://www.wikidata.org/wiki/Q7625099","display_name":"Structure from motion","level":3,"score":0.46187734603881836},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.43580490350723267},{"id":"https://openalex.org/C32230216","wikidata":"https://www.wikidata.org/wiki/Q7882499","display_name":"Uncertainty quantification","level":2,"score":0.4275257885456085},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.40708523988723755},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.34976738691329956},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2767128646373749},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.243274986743927},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.19778713583946228},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.11158442497253418},{"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/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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/3dv50981.2020.00076","is_oa":false,"landing_page_url":"https://doi.org/10.1109/3dv50981.2020.00076","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 International Conference on 3D Vision (3DV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W35220799","https://openalex.org/W1484371059","https://openalex.org/W1506690472","https://openalex.org/W1576347883","https://openalex.org/W1663973292","https://openalex.org/W1804110266","https://openalex.org/W1820096659","https://openalex.org/W2051142108","https://openalex.org/W2107557752","https://openalex.org/W2112634643","https://openalex.org/W2120575449","https://openalex.org/W2124313187","https://openalex.org/W2163446794","https://openalex.org/W2170842420","https://openalex.org/W2471962767","https://openalex.org/W2594639291","https://openalex.org/W2807146880","https://openalex.org/W2887296834","https://openalex.org/W4205293427","https://openalex.org/W4248598408","https://openalex.org/W4320800818","https://openalex.org/W6629250111","https://openalex.org/W6638553236","https://openalex.org/W6676930848"],"related_works":["https://openalex.org/W159468655","https://openalex.org/W2550823067","https://openalex.org/W2371097030","https://openalex.org/W2805880315","https://openalex.org/W2071638828","https://openalex.org/W2170070567","https://openalex.org/W117099968","https://openalex.org/W3016388161","https://openalex.org/W2416513692","https://openalex.org/W4365211488"],"abstract_inverted_index":{"Bundle":[0,122],"adjustment":[1,23],"is":[2,45,168],"the":[3,41,49,68,100,118,130,150,155],"gold":[4],"standard":[5],"for":[6,21,54,113,175],"refining":[7],"solutions":[8,24],"to":[9,25,38,129],"geometric":[10],"computer":[11],"vision":[12],"problems.":[13,29,56],"This":[14],"paper":[15,106],"develops":[16],"an":[17,33],"uncertainty":[18,31,78],"visualization":[19],"technique":[20],"bundle":[22],"Structure":[26,176],"from":[27,35,177],"Motion":[28],"Propagating":[30],"through":[32],"optimization-":[34],"measurement":[36],"uncertainties":[37,39],"in":[40,79,99,149],"resulting":[42,145],"parameter":[43],"estimates-":[44],"well":[46],"understood.":[47],"However,":[48],"calculations":[50],"involved":[51],"fail":[52],"numerically":[53,110],"real":[55],"Often":[57],"we":[58,107,139],"cope":[59],"by":[60],"considering":[61],"only":[62],"individual":[63],"variances,":[64],"but":[65],"this":[66,105,141,166],"ignores":[67],"important":[69],"mutual":[70],"dependencies":[71],"between":[72],"parameters.":[73,137],"The":[74,144],"dominant":[75,115],"modes":[76,159],"of":[77,117,120,133,160],"most":[80],"models":[81],"are":[82],"large":[83],"motions":[84],"involving":[85],"nearly":[86],"all":[87],"parameters":[88],"at":[89],"once.":[90],"These":[91],"frequently":[92],"look":[93],"like":[94],"flexions,":[95],"stretchings,":[96],"and":[97,135,157],"bendings":[98],"overall":[101],"scene":[102],"structure.":[103],"In":[104],"present":[108],"a":[109,121,161,169],"tractable":[111],"method":[112],"computing":[114],"eigenvectors":[116],"covariance":[119],"Adjustment":[123],"solution.":[124],"We":[125,163],"pay":[126],"careful":[127],"attention":[128],"mismatched":[131],"scales":[132],"rotational":[134],"translational":[136],"Finally,":[138],"animate":[140],"spectral":[142],"information.":[143],"interactive":[146],"visualizations":[147],"(included":[148],"supplemental)":[151],"give":[152],"insight":[153],"into":[154],"quality":[156],"failure":[158],"model.":[162],"hope":[164],"that":[165],"work":[167],"step":[170],"towards":[171],"broader":[172],"uncertainty-aware":[173],"computation":[174],"Motion.":[178]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
