{"id":"https://openalex.org/W2117218989","doi":"https://doi.org/10.1109/iros.2012.6385481","title":"Gaussian Process for lens distortion modeling","display_name":"Gaussian Process for lens distortion modeling","publication_year":2012,"publication_date":"2012-10-01","ids":{"openalex":"https://openalex.org/W2117218989","doi":"https://doi.org/10.1109/iros.2012.6385481","mag":"2117218989"},"language":"en","primary_location":{"id":"doi:10.1109/iros.2012.6385481","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2012.6385481","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE/RSJ International Conference on Intelligent Robots and Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://zenodo.org/record/1273758","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5059105428","display_name":"Pradeep Ranganathan","orcid":null},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Pradeep Ranganathan","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Michigan, Ann Arbor, USA","Department of Computer Science and Engineering, Univeristy of Michigan, Ann Arbor, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Michigan, Ann Arbor, USA","institution_ids":["https://openalex.org/I27837315"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, Univeristy of Michigan, Ann Arbor, USA","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5103139078","display_name":"Edwin Olson","orcid":null},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan\u2013Ann Arbor","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Edwin Olson","raw_affiliation_strings":["Department of Computer Science and Engineering, University of Michigan, Ann Arbor, USA","Department of Computer Science and Engineering, Univeristy of Michigan, Ann Arbor, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, University of Michigan, Ann Arbor, USA","institution_ids":["https://openalex.org/I27837315"]},{"raw_affiliation_string":"Department of Computer Science and Engineering, Univeristy of Michigan, Ann Arbor, USA","institution_ids":["https://openalex.org/I27837315"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5059105428"],"corresponding_institution_ids":["https://openalex.org/I27837315"],"apc_list":null,"apc_paid":null,"fwci":0.8354,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.76630012,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3620","last_page":"3625"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10638","display_name":"Optical measurement and interference techniques","score":0.9997000098228455,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9997000098228455,"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":0.9990000128746033,"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"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9966999888420105,"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/distortion","display_name":"Distortion (music)","score":0.7503466606140137},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.6961297988891602},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.6023590564727783},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5462692379951477},{"id":"https://openalex.org/keywords/parametric-model","display_name":"Parametric model","score":0.5355443954467773},{"id":"https://openalex.org/keywords/lens","display_name":"Lens (geology)","score":0.5229324102401733},{"id":"https://openalex.org/keywords/gaussian-function","display_name":"Gaussian function","score":0.5033225417137146},{"id":"https://openalex.org/keywords/amplitude-distortion","display_name":"Amplitude distortion","score":0.49086910486221313},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4838625192642212},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.46421387791633606},{"id":"https://openalex.org/keywords/distortion-function","display_name":"Distortion function","score":0.4554961323738098},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4411272406578064},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.43429821729660034},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.43402644991874695},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.41285377740859985},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3376043736934662},{"id":"https://openalex.org/keywords/nonlinear-distortion","display_name":"Nonlinear distortion","score":0.280192494392395},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.17682147026062012},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.14241650700569153},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.11222034692764282},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.07294636964797974}],"concepts":[{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.7503466606140137},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.6961297988891602},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.6023590564727783},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5462692379951477},{"id":"https://openalex.org/C24574437","wikidata":"https://www.wikidata.org/wiki/Q7135228","display_name":"Parametric model","level":3,"score":0.5355443954467773},{"id":"https://openalex.org/C15336307","wikidata":"https://www.wikidata.org/wiki/Q1766051","display_name":"Lens (geology)","level":2,"score":0.5229324102401733},{"id":"https://openalex.org/C7218915","wikidata":"https://www.wikidata.org/wiki/Q1054475","display_name":"Gaussian function","level":3,"score":0.5033225417137146},{"id":"https://openalex.org/C201154478","wikidata":"https://www.wikidata.org/wiki/Q4748515","display_name":"Amplitude distortion","level":5,"score":0.49086910486221313},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4838625192642212},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.46421387791633606},{"id":"https://openalex.org/C2780803321","wikidata":"https://www.wikidata.org/wiki/Q5283073","display_name":"Distortion function","level":3,"score":0.4554961323738098},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4411272406578064},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.43429821729660034},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.43402644991874695},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.41285377740859985},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3376043736934662},{"id":"https://openalex.org/C173413354","wikidata":"https://www.wikidata.org/wiki/Q7049470","display_name":"Nonlinear distortion","level":4,"score":0.280192494392395},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.17682147026062012},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.14241650700569153},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.11222034692764282},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.07294636964797974},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C194257627","wikidata":"https://www.wikidata.org/wiki/Q211554","display_name":"Amplifier","level":3,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C2776257435","wikidata":"https://www.wikidata.org/wiki/Q1576430","display_name":"Bandwidth (computing)","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iros.2012.6385481","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2012.6385481","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2012 IEEE/RSJ International Conference on Intelligent Robots and Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:zenodo.org:1273758","is_oa":true,"landing_page_url":"https://zenodo.org/record/1273758","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferencePaper"}],"best_oa_location":{"id":"pmh:oai:zenodo.org:1273758","is_oa":true,"landing_page_url":"https://zenodo.org/record/1273758","pdf_url":null,"source":{"id":"https://openalex.org/S4306400562","display_name":"Zenodo (CERN European Organization for Nuclear Research)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I67311998","host_organization_name":"European Organization for Nuclear Research","host_organization_lineage":["https://openalex.org/I67311998"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferencePaper"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W36923225","https://openalex.org/W50439157","https://openalex.org/W1941181464","https://openalex.org/W1992989752","https://openalex.org/W2004398761","https://openalex.org/W2032704023","https://openalex.org/W2033819227","https://openalex.org/W2036171820","https://openalex.org/W2063880455","https://openalex.org/W2065592949","https://openalex.org/W2083786269","https://openalex.org/W2113461752","https://openalex.org/W2143266254","https://openalex.org/W2144325227","https://openalex.org/W2151221236","https://openalex.org/W2157641950","https://openalex.org/W2167667767","https://openalex.org/W2168987272","https://openalex.org/W2209124607","https://openalex.org/W2236623899","https://openalex.org/W3139739645","https://openalex.org/W3141468214","https://openalex.org/W3210232381","https://openalex.org/W4211049957","https://openalex.org/W6640629122","https://openalex.org/W6803376173"],"related_works":["https://openalex.org/W2384408398","https://openalex.org/W2804516791","https://openalex.org/W2999533062","https://openalex.org/W4312290701","https://openalex.org/W4380302106","https://openalex.org/W2027072693","https://openalex.org/W4287180928","https://openalex.org/W3161938660","https://openalex.org/W1987190824","https://openalex.org/W4285219580"],"abstract_inverted_index":{"When":[0],"calibrating":[1],"a":[2,25,32,49,62,85,90],"camera,":[3],"the":[4,11,56,71,82,96],"radial":[5,26],"component":[6],"of":[7,14,73,84,98,127],"lens":[8,20,79,128],"distortion":[9,27,47,100,129,135],"is":[10],"dominant":[12],"source":[13],"image":[15],"distortion.":[16,80],"To":[17],"model":[18,28,46,63,78,113],"this":[19,67,106,123],"distortion,":[21],"camera":[22],"models":[23],"incorporate":[24],"that":[29,122],"conforms":[30],"to":[31,45,77,110],"certain":[33],"parametric":[34,40,59,117,134],"form.":[35],"In":[36,66],"practice":[37],"however,":[38],"multiple":[39],"forms":[41],"can":[42,94],"be":[43],"used":[44],"for":[48],"given":[50],"lens.":[51],"Ideally,":[52],"one":[53],"would":[54],"choose":[55],"best":[57],"suited":[58],"form":[60],"using":[61],"selection":[64,104,114],"procedure.":[65],"work,":[68],"we":[69],"propose":[70],"use":[72,83],"Gaussian":[74,91,124],"Process":[75,92,125],"regression":[76],"With":[81],"squared":[86],"exponential":[87],"covariance":[88],"function,":[89],"(GP)":[93],"describe":[95],"space":[97,107],"smooth":[99],"functions;":[101],"kernel":[102],"hyperparameter":[103],"in":[105],"then":[108],"analogous":[109],"performing":[111],"explicit":[112],"between":[115],"possible":[116],"models.":[118,136],"Our":[119],"evaluation":[120],"shows":[121],"formulation":[126],"performs":[130],"on":[131],"par":[132],"with":[133]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}
