{"id":"https://openalex.org/W2901456780","doi":"https://doi.org/10.1109/coase.2018.8560497","title":"Probabilistic Pose Estimation of Deformable Linear Objects","display_name":"Probabilistic Pose Estimation of Deformable Linear Objects","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2901456780","doi":"https://doi.org/10.1109/coase.2018.8560497","mag":"2901456780"},"language":"en","primary_location":{"id":"doi:10.1109/coase.2018.8560497","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coase.2018.8560497","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/10453/128550","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5052594146","display_name":"Yujun Lai","orcid":"https://orcid.org/0000-0002-9381-5836"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yujun Lai","raw_affiliation_strings":["Department of Biomedical Engineering, University of Glasgow, Glasgow, U.K"],"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, University of Glasgow, Glasgow, U.K","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5064083873","display_name":"James Poon","orcid":"https://orcid.org/0000-0003-2721-1820"},"institutions":[{"id":"https://openalex.org/I155125353","display_name":"Universit\u00e0 Campus Bio-Medico","ror":"https://ror.org/04gqx4x78","country_code":"IT","type":"education","lineage":["https://openalex.org/I155125353"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"James Poon","raw_affiliation_strings":["Universita Campus Bio-medico di Roma, Roma, Italy"],"affiliations":[{"raw_affiliation_string":"Universita Campus Bio-medico di Roma, Roma, Italy","institution_ids":["https://openalex.org/I155125353"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104545816","display_name":"Gavin Paul","orcid":"https://orcid.org/0000-0002-3478-0020"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gavin Paul","raw_affiliation_strings":["Department of Biomedical Engineering, University of Glasgow, Glasgow, U.K"],"affiliations":[{"raw_affiliation_string":"Department of Biomedical Engineering, University of Glasgow, Glasgow, U.K","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5110027377","display_name":"Haifeng Han","orcid":"https://orcid.org/0009-0003-1508-3996"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Haifeng Han","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5042074952","display_name":"Takamitsu Matsubara","orcid":"https://orcid.org/0000-0003-3545-4814"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Takamitsu Matsubara","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5052594146"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5077,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.74940212,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"23","issue":null,"first_page":"471","last_page":"476"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9987999796867371,"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"}},"topics":[{"id":"https://openalex.org/T12814","display_name":"Gaussian Processes and Bayesian Inference","score":0.9987999796867371,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9794999957084656,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9700000286102295,"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/computer-science","display_name":"Computer science","score":0.7459230422973633},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.644188404083252},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6370179653167725},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5938765406608582},{"id":"https://openalex.org/keywords/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.5537331700325012},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.511919379234314},{"id":"https://openalex.org/keywords/graphical-model","display_name":"Graphical model","score":0.49877476692199707},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.47622305154800415},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.4574716091156006},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.4424188733100891},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35271939635276794}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7459230422973633},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.644188404083252},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6370179653167725},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5938765406608582},{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.5537331700325012},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.511919379234314},{"id":"https://openalex.org/C155846161","wikidata":"https://www.wikidata.org/wiki/Q1143367","display_name":"Graphical model","level":2,"score":0.49877476692199707},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.47622305154800415},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.4574716091156006},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.4424188733100891},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35271939635276794},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/coase.2018.8560497","is_oa":false,"landing_page_url":"https://doi.org/10.1109/coase.2018.8560497","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE 14th International Conference on Automation Science and Engineering (CASE)","raw_type":"proceedings-article"},{"id":"pmh:oai:opus.lib.uts.edu.au:10453/128550","is_oa":true,"landing_page_url":"http://hdl.handle.net/10453/128550","pdf_url":null,"source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"}],"best_oa_location":{"id":"pmh:oai:opus.lib.uts.edu.au:10453/128550","is_oa":true,"landing_page_url":"http://hdl.handle.net/10453/128550","pdf_url":null,"source":{"id":"https://openalex.org/S4306401357","display_name":"UTS ePRESS (University of Technology Sydney)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I114017466","host_organization_name":"University of Technology Sydney","host_organization_lineage":["https://openalex.org/I114017466"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Proceeding"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1545568999","https://openalex.org/W1595159159","https://openalex.org/W1709959390","https://openalex.org/W1973310094","https://openalex.org/W1996616201","https://openalex.org/W2037201547","https://openalex.org/W2043488348","https://openalex.org/W2096404799","https://openalex.org/W2097412577","https://openalex.org/W2105755445","https://openalex.org/W2124609748","https://openalex.org/W2129100877","https://openalex.org/W2133294540","https://openalex.org/W2139659525","https://openalex.org/W2161649716","https://openalex.org/W2168826207","https://openalex.org/W2171074980","https://openalex.org/W2583121115","https://openalex.org/W2590683186","https://openalex.org/W2620478555","https://openalex.org/W2740055579","https://openalex.org/W2761826485","https://openalex.org/W3083587944","https://openalex.org/W4211049957","https://openalex.org/W4235609608","https://openalex.org/W6637739723","https://openalex.org/W6739008134","https://openalex.org/W6741869387"],"related_works":["https://openalex.org/W2109986081","https://openalex.org/W4388311650","https://openalex.org/W5922282","https://openalex.org/W1974056099","https://openalex.org/W4245343541","https://openalex.org/W2386077341","https://openalex.org/W563589758","https://openalex.org/W62490179","https://openalex.org/W2954004777","https://openalex.org/W2776613281"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,25,31,45],"probabilistic":[4],"framework":[5,17,100],"for":[6,66],"online":[7],"tracking":[8],"of":[9,41,47,69,96,111],"nodes":[10,70],"along":[11],"deformable":[12],"linear":[13],"objects.":[14],"The":[15,38],"proposed":[16,113],"does":[18],"not":[19],"require":[20],"an":[21],"a-priori":[22],"model;":[23],"instead,":[24],"Bayesian":[26],"Committee":[27],"Machine,":[28],"starting":[29],"as":[30],"tabula":[32],"rasa,":[33],"accumulates":[34],"knowledge":[35],"over":[36],"time.":[37],"key":[39],"benefits":[40],"this":[42],"approach":[43],"are":[44],"lack":[46],"reliance":[48],"upon":[49],"extensive":[50],"pre-training":[51],"data,":[52],"which":[53],"can":[54,88],"be":[55,89],"difficult":[56],"to":[57,72,107],"obtain":[58],"in":[59],"sufficiently":[60],"large":[61],"quantities,":[62],"and":[63],"the":[64,78,84,97,109,112],"ability":[65],"robust":[67],"estimation":[68],"subject":[71],"occlusion.":[73],"Another":[74],"benefit":[75],"is":[76],"that":[77],"uncertainties":[79],"obtained":[80],"during":[81],"inference":[82],"from":[83],"underlying":[85],"Gaussian":[86],"Processes":[87],"beneficial":[90],"towards":[91],"subsequent":[92],"handling":[93],"tasks.":[94],"Comparisons":[95],"non-time":[98],"series":[99],"were":[101],"conducted":[102],"against":[103],"conventional":[104],"regression":[105],"models":[106],"measure":[108],"efficacy":[110],"framework.":[114]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
