{"id":"https://openalex.org/W2809138304","doi":"https://doi.org/10.1109/ivs.2018.8500676","title":"Gaussian Process Based Motion Pattern Recognition with Sequential Local Models","display_name":"Gaussian Process Based Motion Pattern Recognition with Sequential Local Models","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2809138304","doi":"https://doi.org/10.1109/ivs.2018.8500676","mag":"2809138304"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2018.8500676","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2018.8500676","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-148724","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042676602","display_name":"Mattias Tiger","orcid":"https://orcid.org/0000-0002-8546-4431"},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Mattias Tiger","raw_affiliation_strings":["Department of Computer and Information Science, Link\u00f6ping University, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, Link\u00f6ping University, Sweden","institution_ids":["https://openalex.org/I102134673"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014042891","display_name":"Fredrik Heintz","orcid":"https://orcid.org/0000-0002-9595-2471"},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Fredrik Heintz","raw_affiliation_strings":["Department of Computer and Information Science, Link\u00f6ping University, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer and Information Science, Link\u00f6ping University, Sweden","institution_ids":["https://openalex.org/I102134673"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I102134673"],"apc_list":null,"apc_paid":null,"fwci":0.5405,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.60020608,"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":"1143","last_page":"1149"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9966999888420105,"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"}},"topics":[{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9966999888420105,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9952999949455261,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9937000274658203,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/trajectory","display_name":"Trajectory","score":0.7863767147064209},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7743128538131714},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6476765871047974},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.6475026607513428},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.6193451285362244},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5912953019142151},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.5733621120452881},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.5702088475227356},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.45329493284225464},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4369547367095947},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.42772865295410156},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41770774126052856},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3973020315170288},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38084620237350464},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.32180896401405334},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10233494639396667}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.7863767147064209},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7743128538131714},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6476765871047974},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.6475026607513428},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.6193451285362244},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5912953019142151},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.5733621120452881},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.5702088475227356},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.45329493284225464},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4369547367095947},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.42772865295410156},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41770774126052856},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3973020315170288},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38084620237350464},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.32180896401405334},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10233494639396667},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ivs.2018.8500676","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2018.8500676","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"},{"id":"pmh:oai:DiVA.org:liu-148724","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-148724","pdf_url":null,"source":{"id":"https://openalex.org/S4306400838","display_name":"DiVA (Linkoping University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I102134673","host_organization_name":"Link\u00f6ping University","host_organization_lineage":["https://openalex.org/I102134673"],"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":null,"raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:DiVA.org:liu-148724","is_oa":true,"landing_page_url":"http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-148724","pdf_url":null,"source":{"id":"https://openalex.org/S4306400838","display_name":"DiVA (Linkoping University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I102134673","host_organization_name":"Link\u00f6ping University","host_organization_lineage":["https://openalex.org/I102134673"],"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":null,"raw_type":"info:eu-repo/semantics/conferenceObject"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.8299999833106995,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W47556920","https://openalex.org/W1746819321","https://openalex.org/W1864335429","https://openalex.org/W1984896301","https://openalex.org/W2053154970","https://openalex.org/W2092272787","https://openalex.org/W2102341081","https://openalex.org/W2103926622","https://openalex.org/W2105242877","https://openalex.org/W2105813220","https://openalex.org/W2108317465","https://openalex.org/W2122377431","https://openalex.org/W2139320687","https://openalex.org/W2139630381","https://openalex.org/W2142125366","https://openalex.org/W2168292091","https://openalex.org/W4211049957","https://openalex.org/W6675685141","https://openalex.org/W6676327744","https://openalex.org/W6678278778","https://openalex.org/W6680921807","https://openalex.org/W6681310799"],"related_works":["https://openalex.org/W3162200841","https://openalex.org/W2586280620","https://openalex.org/W2805505483","https://openalex.org/W253106158","https://openalex.org/W2384744344","https://openalex.org/W1799694159","https://openalex.org/W2393169196","https://openalex.org/W2366610330","https://openalex.org/W2169866437","https://openalex.org/W1964286703"],"abstract_inverted_index":{"Conventional":[0],"trajectory-based":[1],"vehicular":[2],"traffic":[3],"analysis":[4],"approaches":[5,131],"work":[6],"well":[7],"in":[8,50,70,88,104,189],"simple":[9],"environments":[10,25,60],"such":[11,26,47],"as":[12,27],"a":[13,116,161],"single":[14],"crossing":[15],"but":[16],"they":[17],"do":[18],"not":[19],"scale":[20],"to":[21,41],"more":[22,58],"structurally":[23],"complex":[24,59],"networks":[28],"of":[29,46,64,66,84,91,139,147],"interconnected":[30],"crossings":[31],"(e.g.,":[32],"urban":[33,190],"road":[34],"networks).":[35],"Local":[36],"trajectory":[37,150],"models":[38],"are":[39],"necessary":[40],"cope":[42],"with":[43,106],"the":[44,62,82,89,125,137,145,148,153,168,173],"multi-modality":[45],"structures,":[48],"which":[49,73,107,123],"turn":[51],"introduces":[52],"new":[53],"challenges.":[54,76],"These":[55],"larger":[56],"and":[57,68,144],"increase":[61],"occurrences":[63],"lack":[65],"motion":[67,85,94,108,129],"self-overlaps":[69],"observed":[71,102,149],"trajectories":[72,103],"impose":[74],"further":[75,157],"In":[77],"this":[78,133],"paper":[79],"we":[80],"consider":[81],"problem":[83],"pattern":[86,95,109,130],"recognition":[87],"setting":[90],"sequential":[92],"local":[93,141],"models.":[96],"That":[97],"is,":[98],"classifying":[99],"sub-trajectories":[100],"from":[101,167,185],"accordance":[105],"that":[110,159],"best":[111],"explains":[112],"it.":[113],"We":[114,135,156],"introduce":[115],"Gaussian":[117],"process":[118],"(GP)":[119],"based":[120,128],"modeling":[121],"approach":[122,177],"outperforms":[124],"state-of-the-art":[126],"GP":[127],"at":[132],"task.":[134],"investigate":[136],"impact":[138],"varying":[140],"model":[142],"overlap":[143],"length":[146],"trace":[151],"on":[152],"classification":[154,174],"quality.":[155],"show":[158],"introducing":[160],"pre-processing":[162],"step":[163],"filtering":[164],"out":[165],"stops":[166],"training":[169],"data":[170,184],"significantly":[171],"improves":[172],"performance.":[175],"The":[176],"is":[178],"evaluated":[179],"using":[180],"real":[181],"GPS":[182],"position":[183],"city":[186],"buses":[187],"driving":[188],"areas.":[191]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2026-08-19T15:00:24.278416","created_date":"2025-10-10T00:00:00"}