{"id":"https://openalex.org/W2807456624","doi":"https://doi.org/10.1109/tits.2018.2836305","title":"Pedestrian Path, Pose, and Intention Prediction Through Gaussian Process Dynamical Models and Pedestrian Activity Recognition","display_name":"Pedestrian Path, Pose, and Intention Prediction Through Gaussian Process Dynamical Models and Pedestrian Activity Recognition","publication_year":2018,"publication_date":"2018-05-31","ids":{"openalex":"https://openalex.org/W2807456624","doi":"https://doi.org/10.1109/tits.2018.2836305","mag":"2807456624"},"language":"en","primary_location":{"id":"doi:10.1109/tits.2018.2836305","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2018.2836305","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"},"type":"article","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/A5103054713","display_name":"Ra\u00fal Quintero Minguez","orcid":"https://orcid.org/0000-0003-0955-933X"},"institutions":[{"id":"https://openalex.org/I189268942","display_name":"Universidad de Alcal\u00e1","ror":"https://ror.org/04pmn0e78","country_code":"ES","type":"education","lineage":["https://openalex.org/I189268942"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Raul Quintero Minguez","raw_affiliation_strings":["Computer Engineering Department, University of Alcal\u00e1, Alcal\u00e1 de Henares, Spain"],"affiliations":[{"raw_affiliation_string":"Computer Engineering Department, University of Alcal\u00e1, Alcal\u00e1 de Henares, Spain","institution_ids":["https://openalex.org/I189268942"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027189195","display_name":"I. Parra","orcid":"https://orcid.org/0000-0002-3889-018X"},"institutions":[{"id":"https://openalex.org/I189268942","display_name":"Universidad de Alcal\u00e1","ror":"https://ror.org/04pmn0e78","country_code":"ES","type":"education","lineage":["https://openalex.org/I189268942"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Ignacio Parra Alonso","raw_affiliation_strings":["Computer Engineering Department, University of Alcal\u00e1, Alcal\u00e1 de Henares, Spain"],"affiliations":[{"raw_affiliation_string":"Computer Engineering Department, University of Alcal\u00e1, Alcal\u00e1 de Henares, Spain","institution_ids":["https://openalex.org/I189268942"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016004555","display_name":"David Fern\u00e1ndez Llorca","orcid":"https://orcid.org/0000-0003-2433-7110"},"institutions":[{"id":"https://openalex.org/I189268942","display_name":"Universidad de Alcal\u00e1","ror":"https://ror.org/04pmn0e78","country_code":"ES","type":"education","lineage":["https://openalex.org/I189268942"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"David Fernandez-Llorca","raw_affiliation_strings":["Computer Engineering Department, University of Alcal\u00e1, Alcal\u00e1 de Henares, Spain"],"affiliations":[{"raw_affiliation_string":"Computer Engineering Department, University of Alcal\u00e1, Alcal\u00e1 de Henares, Spain","institution_ids":["https://openalex.org/I189268942"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002294104","display_name":"Miguel \u00c1ngel Sotelo","orcid":"https://orcid.org/0000-0001-8809-2103"},"institutions":[{"id":"https://openalex.org/I189268942","display_name":"Universidad de Alcal\u00e1","ror":"https://ror.org/04pmn0e78","country_code":"ES","type":"education","lineage":["https://openalex.org/I189268942"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Miguel Angel Sotelo","raw_affiliation_strings":["Computer Engineering Department, University of Alcal\u00e1, Alcal\u00e1 de Henares, Spain"],"affiliations":[{"raw_affiliation_string":"Computer Engineering Department, University of Alcal\u00e1, Alcal\u00e1 de Henares, Spain","institution_ids":["https://openalex.org/I189268942"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103054713"],"corresponding_institution_ids":["https://openalex.org/I189268942"],"apc_list":null,"apc_paid":null,"fwci":8.2448,"has_fulltext":false,"cited_by_count":169,"citation_normalized_percentile":{"value":0.98318904,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"20","issue":"5","first_page":"1803","last_page":"1814"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T12740","display_name":"Gait Recognition and Analysis","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9976000189781189,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9954000115394592,"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/pedestrian","display_name":"Pedestrian","score":0.9206012487411499},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.6097089052200317},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5962944626808167},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.57032710313797},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5675188302993774},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5562684535980225},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5138080716133118},{"id":"https://openalex.org/keywords/collision","display_name":"Collision","score":0.5013089179992676},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.49003732204437256},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.45528894662857056},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.4348233640193939},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.42470741271972656},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4205154776573181},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.33985716104507446},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2463790774345398},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.16530841588974},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.1317254602909088}],"concepts":[{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.9206012487411499},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.6097089052200317},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5962944626808167},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.57032710313797},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5675188302993774},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5562684535980225},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5138080716133118},{"id":"https://openalex.org/C121704057","wikidata":"https://www.wikidata.org/wiki/Q352070","display_name":"Collision","level":2,"score":0.5013089179992676},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.49003732204437256},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.45528894662857056},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.4348233640193939},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.42470741271972656},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4205154776573181},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.33985716104507446},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2463790774345398},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.16530841588974},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.1317254602909088},{"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tits.2018.2836305","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tits.2018.2836305","pdf_url":null,"source":{"id":"https://openalex.org/S144771191","display_name":"IEEE Transactions on Intelligent Transportation Systems","issn_l":"1524-9050","issn":["1524-9050","1558-0016"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Intelligent Transportation Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W365842767","https://openalex.org/W1896053897","https://openalex.org/W1936415111","https://openalex.org/W1937999893","https://openalex.org/W1954601274","https://openalex.org/W1976051126","https://openalex.org/W1980985548","https://openalex.org/W1982230942","https://openalex.org/W1987194151","https://openalex.org/W1990707145","https://openalex.org/W1996133250","https://openalex.org/W2004641798","https://openalex.org/W2004815690","https://openalex.org/W2010256323","https://openalex.org/W2031638733","https://openalex.org/W2035057357","https://openalex.org/W2041529535","https://openalex.org/W2045783520","https://openalex.org/W2047203401","https://openalex.org/W2054911734","https://openalex.org/W2059764760","https://openalex.org/W2070100336","https://openalex.org/W2101415982","https://openalex.org/W2108560551","https://openalex.org/W2123430619","https://openalex.org/W2124609748","https://openalex.org/W2126413547","https://openalex.org/W2128769005","https://openalex.org/W2135142117","https://openalex.org/W2150823086","https://openalex.org/W2166063021","https://openalex.org/W2197015301","https://openalex.org/W2286744228","https://openalex.org/W2342006632","https://openalex.org/W2559085405","https://openalex.org/W2566769445","https://openalex.org/W2592796807","https://openalex.org/W2607205416","https://openalex.org/W2758850938","https://openalex.org/W2793807616","https://openalex.org/W4253823815","https://openalex.org/W6633014903","https://openalex.org/W6684451488","https://openalex.org/W6734203242"],"related_works":["https://openalex.org/W2392100589","https://openalex.org/W2512789322","https://openalex.org/W2101960027","https://openalex.org/W2197846993","https://openalex.org/W2972620127","https://openalex.org/W2899977359","https://openalex.org/W1630669003","https://openalex.org/W2981141433","https://openalex.org/W1992295166","https://openalex.org/W2143508933"],"abstract_inverted_index":{"According":[0],"to":[1,18,63,72,164],"several":[2],"reports":[3],"published":[4],"by":[5],"worldwide":[6],"organizations,":[7],"thousands":[8],"of":[9,29,44,112,130,147,150,183,197,213,231],"pedestrians":[10],"die":[11],"in":[12,75],"road":[13],"accidents":[14],"every":[15],"year.":[16],"Due":[17],"this":[19,56,58,139],"fact,":[20],"vehicular":[21],"technologies":[22],"have":[23],"been":[24],"evolving":[25],"with":[26,180,194],"the":[27,42,49,90,141,160,177,192,200,203,225],"intent":[28],"reducing":[30],"these":[31],"fatalities.":[32],"This":[33,77,169],"evolution":[34],"has":[35],"not":[36],"finished":[37],"yet,":[38],"since,":[39],"for":[40,127,206,222],"instance,":[41],"predictions":[43],"pedestrian":[45,66,102,131,167],"paths":[46],"could":[47],"improve":[48],"current":[50],"automatic":[51],"emergency":[52],"braking":[53],"systems.":[54],"For":[55,138],"reason,":[57,140],"paper":[59],"proposes":[60],"a":[61,124,210,229],"method":[62,78,143,170],"predict":[64],"future":[65,114,166],"paths,":[67],"poses,":[68],"and":[69,117,156,158,185],"intentions":[70,188],"up":[71],"1":[73,214],"s":[74,215,233],"advance.":[76],"is":[79,109,216,234],"based":[80],"on":[81],"balanced":[82],"Gaussian":[83],"process":[84],"dynamical":[85],"models":[86,146],"(B-GPDMs),":[87],"which":[88],"reduce":[89],"3-D":[91],"time-related":[92],"information":[93],"extracted":[94],"from":[95],"key":[96],"points":[97],"or":[98],"joints":[99],"placed":[100],"along":[101],"bodies":[103],"into":[104],"low-dimensional":[105],"spaces.":[106],"The":[107],"B-GPDM":[108],"also":[110],"capable":[111],"inferring":[113],"latent":[115],"positions":[116],"reconstruct":[118],"their":[119],"associated":[120],"observations.":[121],"However,":[122],"learning":[123],"generic":[125],"model":[126,163],"all":[128],"kinds":[129],"activities":[132,173,208],"normally":[133],"provides":[134],"less":[135],"accurate":[136],"predictions.":[137],"proposed":[142],"obtains":[144],"multiple":[145],"four":[148],"types":[149],"activity,":[151],"i.e.,":[152],"walking,":[153],"stopping,":[154],"starting,":[155],"standing,":[157],"selects":[159],"most":[161],"similar":[162],"estimate":[165],"states.":[168],"detects":[171],"starting":[172,223],"125":[174],"ms":[175,190],"after":[176],"gait":[178],"initiation":[179],"an":[181,195],"accuracy":[182,196],"80%":[184],"recognizes":[186],"stopping":[187,207],"58.33":[189],"before":[191],"event":[193],"70%.":[198],"Concerning":[199],"path":[201],"prediction,":[202],"mean":[204,226],"error":[205,227],"at":[209,228],"time-to-event":[211],"(TTE)":[212],"238.01":[217],"\u00b1":[218,236],"206.93":[219],"mm":[220],"and,":[221],"actions,":[224],"TTE":[230],"0":[232],"331.93":[235],"254.73":[237],"mm.":[238]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":23},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":30},{"year":2021,"cited_by_count":35},{"year":2020,"cited_by_count":21},{"year":2019,"cited_by_count":17},{"year":2018,"cited_by_count":1}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}