{"id":"https://openalex.org/W2150823086","doi":"https://doi.org/10.1109/ivs.2014.6856498","title":"Pedestrian path prediction using body language traits","display_name":"Pedestrian path prediction using body language traits","publication_year":2014,"publication_date":"2014-06-01","ids":{"openalex":"https://openalex.org/W2150823086","doi":"https://doi.org/10.1109/ivs.2014.6856498","mag":"2150823086"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2014.6856498","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2014.6856498","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","raw_type":"proceedings-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/A5110273645","display_name":"R. Quintero","orcid":null},"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":"R. Quintero","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/A5075002026","display_name":"Jo\u00e3o Almeida","orcid":"https://orcid.org/0000-0001-6634-6213"},"institutions":[{"id":"https://openalex.org/I60858718","display_name":"University of Aveiro","ror":"https://ror.org/00nt41z93","country_code":"PT","type":"education","lineage":["https://openalex.org/I60858718"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"J. Almeida","raw_affiliation_strings":["Universidade de Aveiro, Aveiro, Aveiro, PT"],"affiliations":[{"raw_affiliation_string":"Universidade de Aveiro, Aveiro, Aveiro, PT","institution_ids":["https://openalex.org/I60858718"]}]},{"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":"D. F. 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":"M. A. 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":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5110273645"],"corresponding_institution_ids":["https://openalex.org/I189268942"],"apc_list":null,"apc_paid":null,"fwci":5.167,"has_fulltext":false,"cited_by_count":50,"citation_normalized_percentile":{"value":0.95235202,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"317","last_page":"323"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9994999766349792,"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":0.9994999766349792,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9945999979972839,"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/T10370","display_name":"Traffic and Road Safety","score":0.9851999878883362,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/pedestrian","display_name":"Pedestrian","score":0.837840735912323},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6762038469314575},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6311630010604858},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5549086332321167},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5047820806503296},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5002193450927734},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48944130539894104},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.4414921700954437},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4296055734157562},{"id":"https://openalex.org/keywords/curse-of-dimensionality","display_name":"Curse of dimensionality","score":0.4187568128108978},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.39204517006874084},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.35838794708251953},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32238391041755676},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.22854381799697876}],"concepts":[{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.837840735912323},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6762038469314575},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6311630010604858},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5549086332321167},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5047820806503296},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5002193450927734},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48944130539894104},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.4414921700954437},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4296055734157562},{"id":"https://openalex.org/C111030470","wikidata":"https://www.wikidata.org/wiki/Q1430460","display_name":"Curse of dimensionality","level":2,"score":0.4187568128108978},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39204517006874084},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.35838794708251953},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32238391041755676},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.22854381799697876},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","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":3,"locations":[{"id":"doi:10.1109/ivs.2014.6856498","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2014.6856498","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.708.6842","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.708.6842","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.isislab.es/sotelo/ieeeIV14_Prediction-FinalVersion.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.720.8792","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.720.8792","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.isislab.es/llorca/publications_files/IV2014_PedPre.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6399999856948853,"id":"https://metadata.un.org/sdg/11","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/W1570439160","https://openalex.org/W1900101064","https://openalex.org/W1980985548","https://openalex.org/W1998625821","https://openalex.org/W2004641798","https://openalex.org/W2031454541","https://openalex.org/W2031638733","https://openalex.org/W2051812123","https://openalex.org/W2097412577","https://openalex.org/W2098792943","https://openalex.org/W2110404686","https://openalex.org/W2117248802","https://openalex.org/W2121955477","https://openalex.org/W2124609748","https://openalex.org/W2125896931","https://openalex.org/W2126413547","https://openalex.org/W2150066425","https://openalex.org/W2155135999","https://openalex.org/W2168356304","https://openalex.org/W2169779569","https://openalex.org/W6676272486","https://openalex.org/W6678680539"],"related_works":["https://openalex.org/W2392100589","https://openalex.org/W2512789322","https://openalex.org/W2101960027","https://openalex.org/W2197846993","https://openalex.org/W1976827262","https://openalex.org/W49697837","https://openalex.org/W3122828758","https://openalex.org/W2170799233","https://openalex.org/W2768112316","https://openalex.org/W4311388919"],"abstract_inverted_index":{"Driver":[0],"Assistance":[1],"Systems":[2],"have":[3],"achieved":[4,150],"a":[5,27,46,83,138,152],"high":[6,113],"level":[7],"of":[8,17,29,51,104,115,155],"maturity":[9],"in":[10,26,42,49,76,82,126,137],"the":[11,59,71,89,102,112,116,127,134],"latest":[12],"years.":[13],"As":[14],"an":[15],"example":[16],"that,":[18],"sophisticated":[19],"pedestrian":[20,37,73,135],"protection":[21],"systems":[22],"are":[23,95],"already":[24],"available":[25],"number":[28],"commercial":[30],"vehicles":[31],"from":[32],"several":[33],"OEMs.":[34],"However,":[35],"accurate":[36,145],"path":[38,80,146],"prediction":[39,81,147],"is":[40],"needed":[41],"order":[43,77],"to":[44,78],"go":[45],"step":[47],"further":[48],"terms":[50],"safety":[52],"and":[53,63,93,123,131],"reliability,":[54],"since":[55],"it":[56],"can":[57,148],"make":[58],"difference":[60],"between":[61],"effective":[62],"non-effective":[64],"intervention.":[65],"In":[66],"this":[67,87],"paper,":[68],"we":[69],"consider":[70],"three-dimensional":[72],"body":[74,91],"language":[75],"perform":[79],"probabilistic":[84],"framework.":[85],"For":[86],"purpose,":[88],"different":[90],"parts":[92],"joints":[94,122],"detected":[96],"using":[97],"stereo":[98],"vision.":[99],"We":[100],"propose":[101],"use":[103],"GPDM":[105],"(Gaussian":[106],"Process":[107],"Dynamical":[108],"Models)":[109],"for":[110,132],"reducing":[111],"dimensionality":[114],"input":[117],"feature":[118],"vector":[119],"(composed":[120],"by":[121],"displacement":[124],"vectors)":[125],"3D":[128],"pose":[129],"space":[130],"learning":[133],"dynamics":[136],"latent":[139],"space.":[140],"Experimental":[141],"results":[142],"show":[143],"that":[144],"be":[149],"at":[151],"time":[153],"horizon":[154],"\u2248":[156],"0.8":[157],"s.":[158]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":11},{"year":2018,"cited_by_count":7},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
