{"id":"https://openalex.org/W1972948502","doi":"https://doi.org/10.1109/cvpr.2011.5995736","title":"A generative statistical model for tracking multiple smooth trajectories","display_name":"A generative statistical model for tracking multiple smooth trajectories","publication_year":2011,"publication_date":"2011-06-01","ids":{"openalex":"https://openalex.org/W1972948502","doi":"https://doi.org/10.1109/cvpr.2011.5995736","mag":"1972948502"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2011.5995736","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2011.5995736","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"CVPR 2011","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/A5043410925","display_name":"Ernesto Brau","orcid":"https://orcid.org/0000-0003-0380-8630"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Ernesto Brau","raw_affiliation_strings":["Computer Science, University of Arizona Tucson, USA","Computer Science, University of Arizona"],"affiliations":[{"raw_affiliation_string":"Computer Science, University of Arizona Tucson, USA","institution_ids":["https://openalex.org/I138006243"]},{"raw_affiliation_string":"Computer Science, University of Arizona","institution_ids":["https://openalex.org/I138006243"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054894811","display_name":"Damayanthi Dunatunga","orcid":null},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Damayanthi Dunatunga","raw_affiliation_strings":["Computer Science, University of Arizona Tucson, USA","Plant Sciences, University of Arizona"],"affiliations":[{"raw_affiliation_string":"Computer Science, University of Arizona Tucson, USA","institution_ids":["https://openalex.org/I138006243"]},{"raw_affiliation_string":"Plant Sciences, University of Arizona","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082471157","display_name":"Kobus Barnard","orcid":"https://orcid.org/0000-0002-8568-9518"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kobus Barnard","raw_affiliation_strings":["Plant Sciences, University of Arizona Tucson, USA","Computer Science, University of Arizona"],"affiliations":[{"raw_affiliation_string":"Plant Sciences, University of Arizona Tucson, USA","institution_ids":["https://openalex.org/I138006243"]},{"raw_affiliation_string":"Computer Science, University of Arizona","institution_ids":["https://openalex.org/I138006243"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072830241","display_name":"Tatsuya Tsukamoto","orcid":"https://orcid.org/0000-0001-5306-3791"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tatsuya Tsukamoto","raw_affiliation_strings":["Plant Sciences, University of Arizona Tucson, USA","Plant Sciences, University of Arizona"],"affiliations":[{"raw_affiliation_string":"Plant Sciences, University of Arizona Tucson, USA","institution_ids":["https://openalex.org/I138006243"]},{"raw_affiliation_string":"Plant Sciences, University of Arizona","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106022337","display_name":"Ravi Palanivelu","orcid":null},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ravi Palanivelu","raw_affiliation_strings":["Plant Sciences, University of Arizona Tucson, USA","Plant Sciences, University of Arizona"],"affiliations":[{"raw_affiliation_string":"Plant Sciences, University of Arizona Tucson, USA","institution_ids":["https://openalex.org/I138006243"]},{"raw_affiliation_string":"Plant Sciences, University of Arizona","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004066638","display_name":"Philip Lee","orcid":"https://orcid.org/0000-0002-5783-1599"},"institutions":[{"id":"https://openalex.org/I138006243","display_name":"University of Arizona","ror":"https://ror.org/03m2x1q45","country_code":"US","type":"education","lineage":["https://openalex.org/I138006243"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Philip Lee","raw_affiliation_strings":["Computer Science, University of Arizona Tucson, USA","Computer Science, University of Arizona"],"affiliations":[{"raw_affiliation_string":"Computer Science, University of Arizona Tucson, USA","institution_ids":["https://openalex.org/I138006243"]},{"raw_affiliation_string":"Computer Science, University of Arizona","institution_ids":["https://openalex.org/I138006243"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5043410925"],"corresponding_institution_ids":["https://openalex.org/I138006243"],"apc_list":null,"apc_paid":null,"fwci":3.7733,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.93273168,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"6","issue":null,"first_page":"1137","last_page":"1144"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12417","display_name":"Morphological variations and asymmetry","score":0.9758999943733215,"subfield":{"id":"https://openalex.org/subfields/2608","display_name":"Geometry and Topology"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12417","display_name":"Morphological variations and asymmetry","score":0.9758999943733215,"subfield":{"id":"https://openalex.org/subfields/2608","display_name":"Geometry and Topology"},"field":{"id":"https://openalex.org/fields/26","display_name":"Mathematics"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10895","display_name":"Species Distribution and Climate Change","score":0.9753999710083008,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10199","display_name":"Wildlife Ecology and Conservation","score":0.9592999815940857,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5950040817260742},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5262657403945923},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.46542757749557495},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.4387938976287842},{"id":"https://openalex.org/keywords/smoothing","display_name":"Smoothing","score":0.4213643968105316},{"id":"https://openalex.org/keywords/smoothness","display_name":"Smoothness","score":0.41888123750686646},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4181100130081177},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.4169628620147705},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.41672617197036743},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3069797158241272},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.24260756373405457},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.16093480587005615},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.1305142343044281}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5950040817260742},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5262657403945923},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.46542757749557495},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4387938976287842},{"id":"https://openalex.org/C3770464","wikidata":"https://www.wikidata.org/wiki/Q775963","display_name":"Smoothing","level":2,"score":0.4213643968105316},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.41888123750686646},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4181100130081177},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.4169628620147705},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.41672617197036743},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3069797158241272},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.24260756373405457},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.16093480587005615},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.1305142343044281},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cvpr.2011.5995736","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2011.5995736","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"CVPR 2011","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":30,"referenced_works":["https://openalex.org/W134353426","https://openalex.org/W195465510","https://openalex.org/W1529556955","https://openalex.org/W1601795611","https://openalex.org/W1626341607","https://openalex.org/W1663973292","https://openalex.org/W1746819321","https://openalex.org/W1994005439","https://openalex.org/W2097412577","https://openalex.org/W2100548006","https://openalex.org/W2101733470","https://openalex.org/W2109428210","https://openalex.org/W2113926057","https://openalex.org/W2119883797","https://openalex.org/W2124609748","https://openalex.org/W2127923214","https://openalex.org/W2130416410","https://openalex.org/W2135194391","https://openalex.org/W2141980820","https://openalex.org/W2147855783","https://openalex.org/W2166063021","https://openalex.org/W2169536193","https://openalex.org/W2171166421","https://openalex.org/W3009438726","https://openalex.org/W4211049957","https://openalex.org/W6605442133","https://openalex.org/W6607884611","https://openalex.org/W6636555208","https://openalex.org/W6677707197","https://openalex.org/W6681697924"],"related_works":["https://openalex.org/W1978572805","https://openalex.org/W2383807498","https://openalex.org/W2151689585","https://openalex.org/W1997992934","https://openalex.org/W2380816257","https://openalex.org/W1987225439","https://openalex.org/W4238188170","https://openalex.org/W967181689","https://openalex.org/W2134817643","https://openalex.org/W2363386023"],"abstract_inverted_index":{"We":[0,168,200],"present":[1],"a":[2,128,188,238],"general":[3],"model":[4,51,81],"for":[5,52,74,83,98],"tracking":[6],"smooth":[7,76],"trajectories":[8,29,54,62,211],"of":[9,27,40,66,92,117,174,183,229],"multiple":[10,198],"targets":[11],"in":[12,44,187],"complex":[13],"data":[14,85,123],"sets,":[15],"where":[16],"tracks":[17],"potentially":[18],"cross":[19],"each":[20,191],"other":[21],"many":[22,45],"times.":[23],"As":[24],"the":[25,38,53,84,102,118,147,160],"number":[26,91],"overlapping":[28],"grows,":[30],"exploiting":[31],"smoothness":[32],"becomes":[33],"increasingly":[34],"important":[35,46],"to":[36,145,194,209],"disambiguate":[37],"association":[39,124],"successive":[41],"points.":[42],"However,":[43],"problems":[47],"an":[48,89,231],"effective":[49],"parametric":[50],"does":[55],"not":[56],"exist.":[57],"Hence":[58],"we":[59,110,155],"propose":[60],"modeling":[61],"as":[63,86],"independent":[64],"realizations":[65],"Gaussian":[67],"processes":[68],"with":[69,96,192,197,207],"kernel":[70],"functions":[71],"which":[72,132],"allow":[73],"arbitrary":[75],"motion.":[77],"Our":[78],"generative":[79],"statistical":[80],"accounts":[82],"coming":[87],"from":[88],"unknown":[90],"such":[93],"processes,":[94],"together":[95],"expectations":[97],"noise":[99],"points":[100,105],"and":[101,127,136,138,176,178,214,235],"probability":[103],"that":[104,228],"are":[106,219],"missing.":[107],"For":[108],"inference":[109],"compare":[111,156],"two":[112],"methods:":[113],"A":[114],"modified":[115],"version":[116],"Markov":[119],"chain":[120],"Monte":[121],"Carlo":[122],"(MCMCDA)":[125],"method,":[126],"Gibbs":[129],"sampling":[130],"method":[131],"is":[133],"much":[134],"simpler":[135],"faster,":[137],"gives":[139],"better":[140],"results":[141,158],"by":[142,163],"being":[143],"able":[144],"search":[146],"solution":[148],"space":[149],"more":[150,220],"efficiently.":[151],"In":[152],"both":[153],"cases,":[154],"our":[157,170],"against":[159],"smoothing":[161],"provided":[162],"linear":[164],"dynamical":[165],"systems":[166],"(LDS).":[167],"test":[169],"approach":[171],"on":[172,179,204],"videos":[173],"birds":[175],"fish,":[177],"82":[180],"image":[181,205],"sequences":[182,206],"pollen":[184],"tubes":[185,196],"growing":[186],"petri":[189],"dish,":[190],"up":[193,208],"60":[195],"crossings.":[199],"achieve":[201],"93%":[202],"accuracy":[203,216],"ten":[210,222],"(35":[212],"sequences)":[213],"88%":[215],"when":[217],"there":[218],"than":[221],"(42":[223],"sequences).":[224],"This":[225],"performance":[226],"surpasses":[227],"using":[230],"LDS":[232],"motion":[233],"model,":[234],"far":[236],"exceeds":[237],"simple":[239],"heuristic":[240],"tracker.":[241]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
