{"id":"https://openalex.org/W2150095155","doi":"https://doi.org/10.1109/cvpr.2003.1211504","title":"Finding and tracking people from the bottom up","display_name":"Finding and tracking people from the bottom up","publication_year":2003,"publication_date":"2003-11-20","ids":{"openalex":"https://openalex.org/W2150095155","doi":"https://doi.org/10.1109/cvpr.2003.1211504","mag":"2150095155"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2003.1211504","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2003.1211504","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. 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/A5004353237","display_name":"Deva Ramanan","orcid":"https://orcid.org/0009-0008-9180-8983"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"D. Ramanan","raw_affiliation_strings":["Computer Science Division, University of California Berkeley, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science Division, University of California Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010851725","display_name":"David Forsyth","orcid":"https://orcid.org/0000-0002-2278-0752"},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"D.A. Forsyth","raw_affiliation_strings":["Computer Science Division, University of California Berkeley, Berkeley, CA, USA"],"affiliations":[{"raw_affiliation_string":"Computer Science Division, University of California Berkeley, Berkeley, CA, USA","institution_ids":["https://openalex.org/I95457486"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5004353237"],"corresponding_institution_ids":["https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":22.0868,"has_fulltext":false,"cited_by_count":269,"citation_normalized_percentile":{"value":0.99684226,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"2","issue":null,"first_page":"II","last_page":"467"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9997000098228455,"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":0.9997000098228455,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9995999932289124,"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":0.9980999827384949,"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/computer-science","display_name":"Computer science","score":0.7684624791145325},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.7573612332344055},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7426809668540955},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7361252307891846},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.6997890472412109},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.6728445291519165},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5984453558921814},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5844138264656067},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5324581265449524},{"id":"https://openalex.org/keywords/track","display_name":"Track (disk drive)","score":0.449621319770813},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.412799209356308},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.2015548050403595}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7684624791145325},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.7573612332344055},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7426809668540955},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7361252307891846},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.6997890472412109},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.6728445291519165},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5984453558921814},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5844138264656067},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5324581265449524},{"id":"https://openalex.org/C89992363","wikidata":"https://www.wikidata.org/wiki/Q5961558","display_name":"Track (disk drive)","level":2,"score":0.449621319770813},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.412799209356308},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.2015548050403595},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cvpr.2003.1211504","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2003.1211504","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2003 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2003. Proceedings.","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.12.6221","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.12.6221","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.berkeley.edu/~ramanan/papers/trackingpeople.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.412.1614","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.412.1614","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://luthuli.cs.uiuc.edu/~daf/courses/AppCV/Papers-3/cvpr-final.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1551519658","https://openalex.org/W1563292672","https://openalex.org/W1568122762","https://openalex.org/W1576452626","https://openalex.org/W1601941589","https://openalex.org/W1643263348","https://openalex.org/W1676612073","https://openalex.org/W2030989822","https://openalex.org/W2067191022","https://openalex.org/W2097041931","https://openalex.org/W2109799729","https://openalex.org/W2118025528","https://openalex.org/W2126559756","https://openalex.org/W2135997060","https://openalex.org/W2141294180","https://openalex.org/W2144124341","https://openalex.org/W4307347247","https://openalex.org/W6633013131","https://openalex.org/W6636836683","https://openalex.org/W6680187402"],"related_works":["https://openalex.org/W3204184292","https://openalex.org/W3176564347","https://openalex.org/W1985458517","https://openalex.org/W2355833770","https://openalex.org/W3031039437","https://openalex.org/W3095877357","https://openalex.org/W183202219","https://openalex.org/W2072565696","https://openalex.org/W10861731","https://openalex.org/W2810129309"],"abstract_inverted_index":{"We":[0,104],"describe":[1],"a":[2,44,79,113],"tracker":[3,74,131],"that":[4,41,129],"can":[5,25,109,132],"track":[6,140],"moving":[7],"people":[8,16],"in":[9,69],"long":[10],"sequences":[11],"without":[12],"manual":[13],"initialization.":[14],"Moving":[15],"are":[17,92,102,152],"modeled":[18],"with":[19],"the":[20,47,50,73,157,161,164],"assumption":[21],"that,":[22],"while":[23],"configuration":[24,162],"vary":[26],"quite":[27],"substantially":[28],"from":[29],"frame":[30],"to":[31,38,65,84],"frame,":[32],"appearance":[33,48],"does":[34,75],"not.":[35],"This":[36],"leads":[37],"an":[39,118],"algorithm":[40,108],"firstly":[42],"builds":[43],"model":[45,64,80],"of":[46,49,52,81,88,125,163,176],"body":[51,58,165],"each":[53,70],"individual":[54],"by":[55],"clustering":[56],"candidate":[57],"segments,":[59],"and":[60,99,139,168],"then":[61],"uses":[62],"this":[63,130],"find":[66],"all":[67],"individuals":[68,151],"frame.":[71],"Unusually,":[72],"not":[76,171],"rely":[77],"on":[78,117,123,173],"human":[82,95,177],"dynamics":[83],"identify":[85,138,160],"possible":[86],"instances":[87],"people;":[89],"such":[90],"models":[91,175],"unreliable,":[93],"because":[94],"motion":[96],"is":[97,170],"fast":[98],"large":[100],"accelerations":[101],"common.":[103],"show":[105],"our":[106],"tracking":[107],"be":[110],"interpreted":[111],"as":[112],"loopy":[114],"inference":[115],"procedure":[116],"underlying":[119],"Bayes":[120],"net.":[121],"Experiments":[122],"video":[124],"real":[126],"scenes":[127],"demonstrate":[128],"(a)":[133],"count":[134],"distinct":[135],"individuals;":[136],"(b)":[137],"them;":[141],"(c)":[142],"recover":[143],"when":[144],"it":[145],"loses":[146],"track,":[147],"for":[148],"example,":[149],"if":[150],"occluded":[153],"or":[154],"briefly":[155],"leave":[156],"view;":[158],"(d)":[159],"largely":[166],"correctly;":[167],"(e)":[169],"dependent":[172],"particular":[174],"motion.":[178]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":6},{"year":2014,"cited_by_count":10},{"year":2013,"cited_by_count":13},{"year":2012,"cited_by_count":13}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
