{"id":"https://openalex.org/W1976629543","doi":"https://doi.org/10.1109/chinasip.2013.6625381","title":"Trajectory-based human activity recognition with hierarchical dirichlet process hidden Markov models","display_name":"Trajectory-based human activity recognition with hierarchical dirichlet process hidden Markov models","publication_year":2013,"publication_date":"2013-07-01","ids":{"openalex":"https://openalex.org/W1976629543","doi":"https://doi.org/10.1109/chinasip.2013.6625381","mag":"1976629543"},"language":"en","primary_location":{"id":"doi:10.1109/chinasip.2013.6625381","is_oa":false,"landing_page_url":"https://doi.org/10.1109/chinasip.2013.6625381","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE China Summit and International Conference on Signal and Information Processing","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/A5019829348","display_name":"Qing-Bin Gao","orcid":null},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qingbin Gao","raw_affiliation_strings":["Department of Computer Science and Technology, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5047846625","display_name":"Shiliang Sun","orcid":"https://orcid.org/0000-0001-7069-3752"},"institutions":[{"id":"https://openalex.org/I66867065","display_name":"East China Normal University","ror":"https://ror.org/02n96ep67","country_code":"CN","type":"education","lineage":["https://openalex.org/I66867065"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shiliang Sun","raw_affiliation_strings":["Department of Computer Science and Technology, East China Normal University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, East China Normal University, Shanghai, China","institution_ids":["https://openalex.org/I66867065"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5019829348"],"corresponding_institution_ids":["https://openalex.org/I66867065"],"apc_list":null,"apc_paid":null,"fwci":4.809,"has_fulltext":false,"cited_by_count":18,"citation_normalized_percentile":{"value":0.94691287,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"456","last_page":"460"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9965000152587891,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9965000152587891,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9959999918937683,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9950000047683716,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.9237548112869263},{"id":"https://openalex.org/keywords/hierarchical-dirichlet-process","display_name":"Hierarchical Dirichlet process","score":0.9012638330459595},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7394718527793884},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.599369466304779},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5836771130561829},{"id":"https://openalex.org/keywords/gibbs-sampling","display_name":"Gibbs sampling","score":0.5658133029937744},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5218141078948975},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5012497901916504},{"id":"https://openalex.org/keywords/dirichlet-distribution","display_name":"Dirichlet distribution","score":0.4680079519748688},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4677923619747162},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.45326918363571167},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.4482094943523407},{"id":"https://openalex.org/keywords/dirichlet-process","display_name":"Dirichlet process","score":0.42704737186431885},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34737884998321533},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.33082473278045654},{"id":"https://openalex.org/keywords/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.3045882284641266},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1672775149345398},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.16633832454681396},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.07165583968162537},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.06813651323318481}],"concepts":[{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.9237548112869263},{"id":"https://openalex.org/C141318989","wikidata":"https://www.wikidata.org/wiki/Q5753066","display_name":"Hierarchical Dirichlet process","level":4,"score":0.9012638330459595},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7394718527793884},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.599369466304779},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5836771130561829},{"id":"https://openalex.org/C158424031","wikidata":"https://www.wikidata.org/wiki/Q1191905","display_name":"Gibbs sampling","level":3,"score":0.5658133029937744},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5218141078948975},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5012497901916504},{"id":"https://openalex.org/C169214877","wikidata":"https://www.wikidata.org/wiki/Q981016","display_name":"Dirichlet distribution","level":3,"score":0.4680079519748688},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4677923619747162},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.45326918363571167},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.4482094943523407},{"id":"https://openalex.org/C2781280628","wikidata":"https://www.wikidata.org/wiki/Q5280766","display_name":"Dirichlet process","level":3,"score":0.42704737186431885},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34737884998321533},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.33082473278045654},{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.3045882284641266},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1672775149345398},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.16633832454681396},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.07165583968162537},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.06813651323318481},{"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/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C182310444","wikidata":"https://www.wikidata.org/wiki/Q1332643","display_name":"Boundary value problem","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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":1,"locations":[{"id":"doi:10.1109/chinasip.2013.6625381","is_oa":false,"landing_page_url":"https://doi.org/10.1109/chinasip.2013.6625381","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE China Summit and International Conference on Signal and Information Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5199999809265137,"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1663973292","https://openalex.org/W2011760672","https://openalex.org/W2036502167","https://openalex.org/W2088173430","https://openalex.org/W2155763684","https://openalex.org/W2158266063","https://openalex.org/W2169895393","https://openalex.org/W2435507717","https://openalex.org/W3104490327","https://openalex.org/W6672826685"],"related_works":["https://openalex.org/W2939843948","https://openalex.org/W2950322393","https://openalex.org/W1636225463","https://openalex.org/W2416695473","https://openalex.org/W2352674739","https://openalex.org/W2053306114","https://openalex.org/W1980961028","https://openalex.org/W2055315888","https://openalex.org/W1529005389","https://openalex.org/W2498662104"],"abstract_inverted_index":{"Trajectory-based":[0],"human":[1,7,60],"activity":[2],"recognition":[3],"aims":[4],"at":[5],"understanding":[6],"behaviors":[8],"in":[9,44,46],"video":[10],"sequences.":[11],"Some":[12],"existing":[13],"approaches":[14],"to":[15,33,42,99],"this":[16,38,51],"problem,":[17],"e.g.,":[18],"hidden":[19,68],"Markov":[20,69],"models":[21,70],"(HMM),":[22],"have":[23],"a":[24,55,74],"severe":[25],"limitation,":[26],"namely":[27],"the":[28,64,85,115],"number":[29,39,86],"of":[30,87,104,117],"motions":[31,88],"has":[32],"be":[34,90],"preset.":[35],"In":[36],"fact,":[37],"is":[40,96],"difficult":[41],"define":[43],"advance":[45],"real":[47,111],"practice.":[48],"To":[49],"overcome":[50],"shortcoming,":[52],"we":[53],"propose":[54],"new":[56],"method":[57],"for":[58,78],"modeling":[59],"trajectories":[61],"based":[62],"on":[63,107],"hierarchical":[65],"Dirichlet":[66],"process":[67],"(HDP-HMM),":[71],"and":[72,95,110],"adopt":[73],"Gibbs":[75],"sampling":[76],"algorithm":[77],"model":[79],"training.":[80],"Using":[81],"our":[82,118],"proposed":[83],"technique,":[84],"can":[89],"inferred":[91],"automatically":[92],"from":[93],"data":[94,112],"also":[97],"allowed":[98],"vary":[100],"among":[101],"different":[102],"classes":[103],"activities.":[105],"Experiments":[106],"both":[108],"synthetic":[109],"sets":[113],"demonstrate":[114],"effectiveness":[116],"approach.":[119]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}