{"id":"https://openalex.org/W2037865596","doi":"https://doi.org/10.1109/cvpr.2008.4587718","title":"Trajectory analysis and semantic region modeling using a nonparametric Bayesian model","display_name":"Trajectory analysis and semantic region modeling using a nonparametric Bayesian model","publication_year":2008,"publication_date":"2008-06-01","ids":{"openalex":"https://openalex.org/W2037865596","doi":"https://doi.org/10.1109/cvpr.2008.4587718","mag":"2037865596"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2008.4587718","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2008.4587718","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/1721.1/40808","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100444820","display_name":"Xiaogang Wang","orcid":"https://orcid.org/0000-0002-7929-5889"},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaogang Wang","raw_affiliation_strings":["CS and AI Laboratory, MIT, Cambridge, MA, USA","CS & AI Lab., MIT, Cambridge, MA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CS and AI Laboratory, MIT, Cambridge, MA, USA","institution_ids":[]},{"raw_affiliation_string":"CS & AI Lab., MIT, Cambridge, MA","institution_ids":["https://openalex.org/I63966007"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039601592","display_name":"Keng Teck","orcid":null},"institutions":[{"id":"https://openalex.org/I28490864","display_name":"DSO National Laboratories","ror":"https://ror.org/03e05fb06","country_code":"SG","type":"nonprofit","lineage":["https://openalex.org/I28490864"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Keng Teck Ma","raw_affiliation_strings":["DSO National Laboratories, Singapore","DSO National Laboratories, 20 Science Park Drive Singapore 118230"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DSO National Laboratories, Singapore","institution_ids":["https://openalex.org/I28490864"]},{"raw_affiliation_string":"DSO National Laboratories, 20 Science Park Drive Singapore 118230","institution_ids":["https://openalex.org/I28490864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113443005","display_name":"Gee-Wah Ng","orcid":null},"institutions":[{"id":"https://openalex.org/I28490864","display_name":"DSO National Laboratories","ror":"https://ror.org/03e05fb06","country_code":"SG","type":"nonprofit","lineage":["https://openalex.org/I28490864"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Gee-Wah Ng","raw_affiliation_strings":["DSO National Laboratories, Singapore","DSO National Laboratories, 20 Science Park Drive Singapore 118230"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"DSO National Laboratories, Singapore","institution_ids":["https://openalex.org/I28490864"]},{"raw_affiliation_string":"DSO National Laboratories, 20 Science Park Drive Singapore 118230","institution_ids":["https://openalex.org/I28490864"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053439821","display_name":"W. Eric L. Grimson","orcid":null},"institutions":[{"id":"https://openalex.org/I63966007","display_name":"Massachusetts Institute of Technology","ror":"https://ror.org/042nb2s44","country_code":"US","type":"education","lineage":["https://openalex.org/I63966007"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"W. Eric L. Grimson","raw_affiliation_strings":["CS and AI Laboratory, MIT, Cambridge, MA, USA","CS and AI Lab, MIT, 77 Massachusetts Ave., Cambridge, 02139, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"CS and AI Laboratory, MIT, Cambridge, MA, USA","institution_ids":[]},{"raw_affiliation_string":"CS and AI Lab, MIT, 77 Massachusetts Ave., Cambridge, 02139, USA","institution_ids":["https://openalex.org/I63966007"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":171,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9991000294685364,"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/T11106","display_name":"Data Management and Algorithms","score":0.9879999756813049,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T11980","display_name":"Human Mobility and Location-Based Analysis","score":0.9728999733924866,"subfield":{"id":"https://openalex.org/subfields/3313","display_name":"Transportation"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6927024126052856},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6417026519775391},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5733305811882019},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5623903274536133},{"id":"https://openalex.org/keywords/nonparametric-statistics","display_name":"Nonparametric statistics","score":0.5583356618881226},{"id":"https://openalex.org/keywords/semantic-analysis","display_name":"Semantic analysis (machine learning)","score":0.4860685169696808},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3331296145915985},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.25360262393951416},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.185115247964859}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6927024126052856},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6417026519775391},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5733305811882019},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5623903274536133},{"id":"https://openalex.org/C102366305","wikidata":"https://www.wikidata.org/wiki/Q1097688","display_name":"Nonparametric statistics","level":2,"score":0.5583356618881226},{"id":"https://openalex.org/C2777946921","wikidata":"https://www.wikidata.org/wiki/Q7449044","display_name":"Semantic analysis (machine learning)","level":2,"score":0.4860685169696808},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3331296145915985},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.25360262393951416},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.185115247964859},{"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}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/cvpr.2008.4587718","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2008.4587718","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.407.9889","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.407.9889","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://mplab.ucsd.edu/wp-content/uploads/cvpr2008/conference/data/papers/378.pdf","raw_type":"text"},{"id":"pmh:oai:dspace.mit.edu:1721.1/40808","is_oa":true,"landing_page_url":"http://hdl.handle.net/1721.1/40808","pdf_url":null,"source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:dspace.mit.edu:1721.1/40808","is_oa":true,"landing_page_url":"http://hdl.handle.net/1721.1/40808","pdf_url":null,"source":{"id":"https://openalex.org/S4306400425","display_name":"DSpace@MIT (Massachusetts Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I63966007","host_organization_name":"Massachusetts Institute of Technology","host_organization_lineage":["https://openalex.org/I63966007"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc","license_id":"https://openalex.org/licenses/cc-by-nc","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.5600000023841858,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1484830317","https://openalex.org/W1502917505","https://openalex.org/W1880262756","https://openalex.org/W1978799052","https://openalex.org/W2008810234","https://openalex.org/W2069429561","https://openalex.org/W2097241944","https://openalex.org/W2109389234","https://openalex.org/W2111918405","https://openalex.org/W2141966200","https://openalex.org/W2151967501","https://openalex.org/W2158266063","https://openalex.org/W2159669057","https://openalex.org/W2164223054","https://openalex.org/W2166583862","https://openalex.org/W4241521373","https://openalex.org/W6629027181","https://openalex.org/W6629740540","https://openalex.org/W6680773757","https://openalex.org/W6682569104","https://openalex.org/W6683941694"],"related_works":["https://openalex.org/W4243114048","https://openalex.org/W4237896776","https://openalex.org/W4231665652","https://openalex.org/W2000242494","https://openalex.org/W4296826658","https://openalex.org/W2059078372","https://openalex.org/W4235488275","https://openalex.org/W2903379275","https://openalex.org/W4366961134","https://openalex.org/W2579156435"],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,40,47,158,166],"novel":[3],"nonparametric":[4],"Bayesian":[5],"model,":[6],"dual":[7],"hierarchical":[8,89],"Dirichlet":[9,90],"processes":[10,91],"(Dual-HDP),":[11],"for":[12],"trajectory":[13,41],"analysis":[14],"and":[15,34,104,115,125,145,161],"semantic":[16,65],"region":[17],"modeling":[18],"in":[19,22,46,79],"surveillance":[20],"settings,":[21,133],"an":[23,37],"unsupervised":[24],"way.":[25],"In":[26],"our":[27,131],"approach,":[28],"trajectories":[29,56],"are":[30,42,50,57,68,82,148],"treated":[31,43],"as":[32,44,59],"documents":[33,101],"observations":[35,137,144],"of":[36,70,109,122,138],"object":[38],"on":[39,150],"words":[45,99,114],"document.":[48],"Trajectories":[49],"clustered":[51],"into":[52,102],"different":[53],"activities.":[54],"Abnormal":[55],"detected":[58],"samples":[60],"with":[61],"low":[62],"likelihoods.":[63],"The":[64],"regions,":[66],"which":[67],"intersections":[69],"paths":[71],"commonly":[72],"taken":[73],"by":[74],"objects,":[75,139],"related":[76],"to":[77],"activities":[78],"the":[80,87,107,120],"scene":[81],"also":[83],"modeled.":[84],"Dual-HDP":[85,111,141],"advances":[86],"existing":[88],"(HDP)":[92],"language":[93],"model.":[94],"HDP":[95,134],"only":[96,135],"clusters":[97,127,136,142],"co-occurring":[98],"from":[100,128,157,165],"topics":[103,124],"automatically":[105],"decides":[106],"number":[108],"topics.":[110],"co-clusters":[112],"both":[113,119,143],"documents.":[116],"It":[117],"learns":[118],"numbers":[121],"word":[123],"document":[126],"data.":[129],"Under":[130],"problem":[132],"while":[140],"trajectories.":[146],"Experiments":[147],"evaluated":[149],"two":[151],"data":[152],"sets,":[153],"radar":[154],"tracks":[155,163],"collected":[156,164],"maritime":[159],"port":[160],"visual":[162],"parking":[167],"lot.":[168]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":13},{"year":2017,"cited_by_count":15},{"year":2016,"cited_by_count":11},{"year":2015,"cited_by_count":13},{"year":2014,"cited_by_count":15},{"year":2013,"cited_by_count":14},{"year":2012,"cited_by_count":17}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
