{"id":"https://openalex.org/W2970315767","doi":"https://doi.org/10.1109/icip.2019.8804300","title":"Multiple Motion Fields for Multiple Types of Agents","display_name":"Multiple Motion Fields for Multiple Types of Agents","publication_year":2019,"publication_date":"2019-08-26","ids":{"openalex":"https://openalex.org/W2970315767","doi":"https://doi.org/10.1109/icip.2019.8804300","mag":"2970315767"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2019.8804300","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8804300","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5018897159","display_name":"Catarina Barata","orcid":"https://orcid.org/0000-0002-2852-7723"},"institutions":[{"id":"https://openalex.org/I141596103","display_name":"University of Lisbon","ror":"https://ror.org/01c27hj86","country_code":"PT","type":"education","lineage":["https://openalex.org/I141596103"]},{"id":"https://openalex.org/I4210105462","display_name":"Lus\u00edada University of Lisbon","ror":"https://ror.org/00zjprf31","country_code":"PT","type":"education","lineage":["https://openalex.org/I4210105462","https://openalex.org/I4401200244"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Catarina Barata","raw_affiliation_strings":["Universidade de Lisboa, Lisbon, Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidade de Lisboa, Lisbon, Portugal","institution_ids":["https://openalex.org/I141596103","https://openalex.org/I4210105462"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026826555","display_name":"M\u00e1rio A. T. Figueiredo","orcid":"https://orcid.org/0000-0002-0970-7745"},"institutions":[{"id":"https://openalex.org/I141596103","display_name":"University of Lisbon","ror":"https://ror.org/01c27hj86","country_code":"PT","type":"education","lineage":["https://openalex.org/I141596103"]},{"id":"https://openalex.org/I4210105462","display_name":"Lus\u00edada University of Lisbon","ror":"https://ror.org/00zjprf31","country_code":"PT","type":"education","lineage":["https://openalex.org/I4210105462","https://openalex.org/I4401200244"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Mario A. T. Figueiredo","raw_affiliation_strings":["Universidade de Lisboa, Lisbon, Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidade de Lisboa, Lisbon, Portugal","institution_ids":["https://openalex.org/I141596103","https://openalex.org/I4210105462"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071738210","display_name":"Jorge S. Marques","orcid":"https://orcid.org/0000-0002-3800-7756"},"institutions":[{"id":"https://openalex.org/I141596103","display_name":"University of Lisbon","ror":"https://ror.org/01c27hj86","country_code":"PT","type":"education","lineage":["https://openalex.org/I141596103"]},{"id":"https://openalex.org/I4210105462","display_name":"Lus\u00edada University of Lisbon","ror":"https://ror.org/00zjprf31","country_code":"PT","type":"education","lineage":["https://openalex.org/I4210105462","https://openalex.org/I4401200244"]}],"countries":["PT"],"is_corresponding":false,"raw_author_name":"Jorge S. Marques","raw_affiliation_strings":["Universidade de Lisboa, Lisbon, Portugal"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Universidade de Lisboa, Lisbon, Portugal","institution_ids":["https://openalex.org/I141596103","https://openalex.org/I4210105462"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0915,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.34744482,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":"36","issue":null,"first_page":"1287","last_page":"1291"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998000264167786,"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"}},"topics":[{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998000264167786,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9997000098228455,"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":0.9983999729156494,"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/computer-science","display_name":"Computer science","score":0.7706291675567627},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6216560006141663},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.5648135542869568},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5041519403457642},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.48820334672927856},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4460323452949524},{"id":"https://openalex.org/keywords/drone","display_name":"Drone","score":0.44081926345825195},{"id":"https://openalex.org/keywords/expectation\u2013maximization-algorithm","display_name":"Expectation\u2013maximization algorithm","score":0.42667126655578613},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.4251982271671295},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.41925016045570374},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3687603771686554},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35881394147872925},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.1756400763988495},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10181337594985962}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7706291675567627},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6216560006141663},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.5648135542869568},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5041519403457642},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.48820334672927856},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4460323452949524},{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.44081926345825195},{"id":"https://openalex.org/C182081679","wikidata":"https://www.wikidata.org/wiki/Q1275153","display_name":"Expectation\u2013maximization algorithm","level":3,"score":0.42667126655578613},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.4251982271671295},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.41925016045570374},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3687603771686554},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35881394147872925},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.1756400763988495},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10181337594985962},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","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/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","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},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2019.8804300","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8804300","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W410107069","https://openalex.org/W1636244751","https://openalex.org/W1964971935","https://openalex.org/W1967456674","https://openalex.org/W2015876616","https://openalex.org/W2125186487","https://openalex.org/W2125838338","https://openalex.org/W2180180824","https://openalex.org/W2259801182","https://openalex.org/W2464754550","https://openalex.org/W2519586580","https://openalex.org/W2554032856","https://openalex.org/W2593042479","https://openalex.org/W2606592784","https://openalex.org/W2607296803","https://openalex.org/W2775620293","https://openalex.org/W2790747968","https://openalex.org/W2889610919","https://openalex.org/W2964232409","https://openalex.org/W4235881750","https://openalex.org/W6726469348"],"related_works":["https://openalex.org/W4229448053","https://openalex.org/W4247925126","https://openalex.org/W4327774218","https://openalex.org/W2059768187","https://openalex.org/W4312858960","https://openalex.org/W4386036939","https://openalex.org/W1976188970","https://openalex.org/W2889559465","https://openalex.org/W2990541822","https://openalex.org/W1588885902"],"abstract_inverted_index":{"Complex":[0],"surveillance":[1],"scenarios":[2],"comprise":[3],"different":[4,41,85],"types":[5,42],"of":[6,43,50],"agents":[7,86],"(e.g.,":[8],"bikers,":[9],"cars,":[10],"and":[11,54,72,83],"pedestrians)":[12],"that":[13],"must":[14],"be":[15],"efficiently":[16],"characterized":[17],"in":[18,47,87],"order":[19],"to":[20,39,70,81],"facilitate":[21],"tasks":[22],"such":[23],"as":[24],"tracking":[25],"or":[26],"abnormality":[27],"detection.":[28],"This":[29],"paper":[30],"proposes":[31],"an":[32,88],"unsupervised":[33,89],"hierarchical":[34,51],"multiple":[35],"motion":[36],"fields":[37],"model":[38,53],"represent":[40],"agents,":[44],"which":[45],"relies":[46],"the":[48,62,79],"combination":[49],"Markov":[52],"velocity":[55],"fields.":[56],"Model":[57],"parameters":[58],"are":[59],"estimated":[60],"using":[61],"expectation-maximization":[63],"algorithm.":[64],"The":[65],"proposed":[66],"framework":[67],"was":[68],"applied":[69],"synthetic":[71],"real":[73],"datasets":[74],"(Stanford":[75],"Drone":[76],"Dataset),":[77],"showing":[78],"ability":[80],"characterize":[82],"classify":[84],"way.":[90]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
