{"id":"https://openalex.org/W2066975876","doi":"https://doi.org/10.1155/2010/712854","title":"Vehicle Trajectory Estimation Using Spatio-Temporal MCMC","display_name":"Vehicle Trajectory Estimation Using Spatio-Temporal MCMC","publication_year":2010,"publication_date":"2010-05-03","ids":{"openalex":"https://openalex.org/W2066975876","doi":"https://doi.org/10.1155/2010/712854","mag":"2066975876"},"language":"en","primary_location":{"id":"doi:10.1155/2010/712854","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2010/712854","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1155/2010/712854","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1155/2010/712854","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112678627","display_name":"Yann Goyat","orcid":null},"institutions":[{"id":"https://openalex.org/I4210144122","display_name":"Laboratoire de Chimie des Polym\u00e8res Organiques","ror":"https://ror.org/056n05x05","country_code":"FR","type":"facility","lineage":["https://openalex.org/I1294671590","https://openalex.org/I1294671590","https://openalex.org/I15057530","https://openalex.org/I4210128300","https://openalex.org/I4210144122","https://openalex.org/I4210160189"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Yann Goyat","raw_affiliation_strings":["LCPC, Route de Bouaye, 44341, Bouguenais, France","LCPC, Bouguenais, France#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LCPC, Route de Bouaye, 44341, Bouguenais, France","institution_ids":["https://openalex.org/I4210144122"]},{"raw_affiliation_string":"LCPC, Bouguenais, France#TAB#","institution_ids":["https://openalex.org/I4210144122"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040478758","display_name":"Thierry Ch\u00e2teau","orcid":"https://orcid.org/0000-0003-4854-5686"},"institutions":[{"id":"https://openalex.org/I198244214","display_name":"Universit\u00e9 Clermont Auvergne","ror":"https://ror.org/01a8ajp46","country_code":"FR","type":"education","lineage":["https://openalex.org/I198244214"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Thierry Chateau","raw_affiliation_strings":["LASMEA, Universit\u00e9 Blaise Pascal, 24 Avenue des landais, 63177, Aubi\u00e8re, France","LASMEA, Universit\u00e9 Blaise-Pascal, Aubi\u00e8re, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LASMEA, Universit\u00e9 Blaise Pascal, 24 Avenue des landais, 63177, Aubi\u00e8re, France","institution_ids":["https://openalex.org/I198244214"]},{"raw_affiliation_string":"LASMEA, Universit\u00e9 Blaise-Pascal, Aubi\u00e8re, France","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020062297","display_name":"Fran\u00e7ois Bardet","orcid":null},"institutions":[{"id":"https://openalex.org/I198244214","display_name":"Universit\u00e9 Clermont Auvergne","ror":"https://ror.org/01a8ajp46","country_code":"FR","type":"education","lineage":["https://openalex.org/I198244214"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Francois Bardet","raw_affiliation_strings":["LASMEA, Universit\u00e9 Blaise Pascal, 24 Avenue des landais, 63177, Aubi\u00e8re, France","LASMEA, Universit\u00e9 Blaise-Pascal, Aubi\u00e8re, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"LASMEA, Universit\u00e9 Blaise Pascal, 24 Avenue des landais, 63177, Aubi\u00e8re, France","institution_ids":["https://openalex.org/I198244214"]},{"raw_affiliation_string":"LASMEA, Universit\u00e9 Blaise-Pascal, Aubi\u00e8re, France","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5112678627"],"corresponding_institution_ids":["https://openalex.org/I4210144122"],"apc_list":{"value":1140,"currency":"GBP","value_usd":1398},"apc_paid":{"value":1140,"currency":"GBP","value_usd":1398},"fwci":2.3259,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.8904629,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"2010","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9990000128746033,"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"}},"topics":[{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9990000128746033,"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"}},{"id":"https://openalex.org/T10711","display_name":"Target Tracking and Data Fusion in Sensor Networks","score":0.9973999857902527,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9940999746322632,"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/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.7835435271263123},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7018852829933167},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6847492456436157},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6745462417602539},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.6474841833114624},{"id":"https://openalex.org/keywords/global-positioning-system","display_name":"Global Positioning System","score":0.5721780061721802},{"id":"https://openalex.org/keywords/kinematics","display_name":"Kinematics","score":0.5476374626159668},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5223437547683716},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.48424646258354187},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.47614550590515137},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.43392056226730347},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4300592243671417},{"id":"https://openalex.org/keywords/random-walk","display_name":"Random walk","score":0.4173222780227661},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.35978472232818604},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3119666278362274},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.26690012216567993},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.23368823528289795},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21108153462409973},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.15790000557899475},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08015012741088867}],"concepts":[{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.7835435271263123},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7018852829933167},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6847492456436157},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6745462417602539},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.6474841833114624},{"id":"https://openalex.org/C60229501","wikidata":"https://www.wikidata.org/wiki/Q18822","display_name":"Global Positioning System","level":2,"score":0.5721780061721802},{"id":"https://openalex.org/C39920418","wikidata":"https://www.wikidata.org/wiki/Q11476","display_name":"Kinematics","level":2,"score":0.5476374626159668},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5223437547683716},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.48424646258354187},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.47614550590515137},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.43392056226730347},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4300592243671417},{"id":"https://openalex.org/C121194460","wikidata":"https://www.wikidata.org/wiki/Q856741","display_name":"Random walk","level":2,"score":0.4173222780227661},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.35978472232818604},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3119666278362274},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.26690012216567993},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.23368823528289795},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21108153462409973},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.15790000557899475},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08015012741088867},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","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},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1155/2010/712854","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2010/712854","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1155/2010/712854","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:HAL:hal-00587921v1","is_oa":true,"landing_page_url":"https://hal.science/hal-00587921","pdf_url":null,"source":{"id":"https://openalex.org/S4306402512","display_name":"HAL (Le Centre pour la Communication Scientifique Directe)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1294671590","host_organization_name":"Centre National de la Recherche Scientifique","host_organization_lineage":["https://openalex.org/I1294671590"],"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":"EURASIP Journal on Advances in Signal Processing, 2010, 2010, 8p. &#x27E8;10.1155/2010/712854&#x27E9;","raw_type":"Journal articles"},{"id":"pmh:oai:doaj.org/article:36ea9793a70a4a1dbb718acf9a0f0558","is_oa":false,"landing_page_url":"https://doaj.org/article/36ea9793a70a4a1dbb718acf9a0f0558","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"EURASIP Journal on Advances in Signal Processing, Vol 2010 (2010)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/2010/712854","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2010/712854","pdf_url":"https://asp-eurasipjournals.springeropen.com/counter/pdf/10.1155/2010/712854","source":{"id":"https://openalex.org/S35920007","display_name":"EURASIP Journal on Advances in Signal Processing","issn_l":"1687-6172","issn":["1687-6172","1687-6180"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EURASIP Journal on Advances in Signal Processing","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.699999988079071,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2066975876.pdf","grobid_xml":"https://content.openalex.org/works/W2066975876.grobid-xml"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W2098669323","https://openalex.org/W2113926057","https://openalex.org/W2117082318","https://openalex.org/W2141251974","https://openalex.org/W2153689886","https://openalex.org/W2158634074","https://openalex.org/W2159128898","https://openalex.org/W2161406034","https://openalex.org/W2162919312","https://openalex.org/W2167149169","https://openalex.org/W2295262250"],"related_works":["https://openalex.org/W2126907425","https://openalex.org/W2208639223","https://openalex.org/W2114656557","https://openalex.org/W1499764293","https://openalex.org/W2195963939","https://openalex.org/W2514372983","https://openalex.org/W4245379261","https://openalex.org/W2075503097","https://openalex.org/W1497303808","https://openalex.org/W2029412444"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"an":[3],"algorithm":[4,177],"for":[5],"modeling":[6],"and":[7,97],"tracking":[8],"vehicles":[9],"in":[10,102,142],"video":[11,155],"sequences":[12,156],"within":[13],"one":[14],"integrated":[15],"framework.":[16],"Most":[17],"of":[18,50,62,65,75,83,94,108],"the":[19,58,63,72,81,91,95,106,109,117,175],"solutions":[20],"are":[21],"based":[22],"on":[23,57,153],"sequential":[24,180],"methods":[25,69],"that":[26,42,71,136,174],"make":[27],"inference":[28,40,68,181],"according":[29,46],"to":[30,47,80,104,144],"current":[31],"information.":[32],"In":[33],"contrast,":[34],"we":[35,159],"propose":[36],"a":[37,44,48,54,98,130,138,165,179],"deferred":[38,66],"logical":[39,67],"method":[41,152],"makes":[43],"decision":[45],"sequence":[49],"observations,":[51],"thus":[52],"processing":[53],"spatio-temporal":[55],"search":[56],"whole":[59],"trajectory.":[60],"One":[61],"drawbacks":[64],"is":[70,126],"solution":[73,124,182],"space":[74,107,125],"hypotheses":[76],"grows":[77],"exponentially":[78],"related":[79],"depth":[82],"observation.":[84],"Our":[85],"approach":[86],"takes":[87],"into":[88],"account":[89],"both":[90],"kinematic":[92],"model":[93,101,115],"vehicle":[96],"driver":[99],"behavior":[100],"order":[103,143],"reduce":[105],"solutions.":[110],"The":[111,123],"resulting":[112],"proposed":[113,176],"state":[114],"explains":[116],"trajectory":[118],"with":[119,129],"only":[120],"11":[121],"parameters.":[122],"then":[127],"sampled":[128],"Markov":[131],"Chain":[132],"Monte":[133],"Carlo":[134],"(MCMC)":[135],"uses":[137],"model-driven":[139],"proposal":[140],"distribution":[141],"control":[145],"random":[146],"walk":[147],"behavior.":[148],"We":[149],"demonstrate":[150],"our":[151],"real":[154],"from":[157],"which":[158],"have":[160],"ground":[161],"truth":[162],"provided":[163],"by":[164],"RTK":[166],"GPS":[167],"(Real-Time":[168],"Kinematic":[169],"GPS).":[170],"Experimental":[171],"results":[172],"show":[173],"outperforms":[178],"(particle":[183],"filter).":[184]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
