{"id":"https://openalex.org/W2145005716","doi":"https://doi.org/10.1142/s021800141455009x","title":"A MULTILEVEL MODELING APPROACH FOR ONLINE LEARNING AND CLASSIFICATION OF COMPLEX TRAJECTORIES FOR VIDEO SURVEILLANCE","display_name":"A MULTILEVEL MODELING APPROACH FOR ONLINE LEARNING AND CLASSIFICATION OF COMPLEX TRAJECTORIES FOR VIDEO SURVEILLANCE","publication_year":2014,"publication_date":"2014-07-07","ids":{"openalex":"https://openalex.org/W2145005716","doi":"https://doi.org/10.1142/s021800141455009x","mag":"2145005716"},"language":"en","primary_location":{"id":"doi:10.1142/s021800141455009x","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s021800141455009x","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-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/A5030844960","display_name":"Giancarlo Iannizzotto","orcid":"https://orcid.org/0000-0003-1275-7433"},"institutions":[{"id":"https://openalex.org/I112862951","display_name":"University of Messina","ror":"https://ror.org/05ctdxz19","country_code":"IT","type":"education","lineage":["https://openalex.org/I112862951"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"GIANCARLO IANNIZZOTTO","raw_affiliation_strings":["Department of Cognitive Sciences, Education and Cultural Studies, University of Messina, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Cognitive Sciences, Education and Cultural Studies, University of Messina, Italy","institution_ids":["https://openalex.org/I112862951"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012216263","display_name":"Lucia Lo Bello","orcid":"https://orcid.org/0000-0002-0604-9783"},"institutions":[{"id":"https://openalex.org/I39063666","display_name":"University of Catania","ror":"https://ror.org/03a64bh57","country_code":"IT","type":"education","lineage":["https://openalex.org/I39063666"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"LUCIA LO BELLO","raw_affiliation_strings":["Department of Electrical, Electronic and Computer Engineering, University of Catania, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical, Electronic and Computer Engineering, University of Catania, Italy","institution_ids":["https://openalex.org/I39063666"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8284,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.81947124,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"28","issue":"06","first_page":"1455009","last_page":"1455009"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.988099992275238,"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":0.988099992275238,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9873999953269958,"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":0.9873999953269958,"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":0.793267548084259},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7102606296539307},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6408617496490479},{"id":"https://openalex.org/keywords/mixture-model","display_name":"Mixture model","score":0.6187435388565063},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5051339268684387},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.4785205125808716},{"id":"https://openalex.org/keywords/novelty-detection","display_name":"Novelty detection","score":0.469951868057251},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4176270067691803},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4155861437320709},{"id":"https://openalex.org/keywords/novelty","display_name":"Novelty","score":0.4079475998878479},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3473755717277527}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.793267548084259},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7102606296539307},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6408617496490479},{"id":"https://openalex.org/C61224824","wikidata":"https://www.wikidata.org/wiki/Q2260434","display_name":"Mixture model","level":2,"score":0.6187435388565063},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5051339268684387},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.4785205125808716},{"id":"https://openalex.org/C2778924833","wikidata":"https://www.wikidata.org/wiki/Q7064603","display_name":"Novelty detection","level":3,"score":0.469951868057251},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4176270067691803},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4155861437320709},{"id":"https://openalex.org/C2778738651","wikidata":"https://www.wikidata.org/wiki/Q16546687","display_name":"Novelty","level":2,"score":0.4079475998878479},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3473755717277527},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C27206212","wikidata":"https://www.wikidata.org/wiki/Q34178","display_name":"Theology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s021800141455009x","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s021800141455009x","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.5400000214576721}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W34992941","https://openalex.org/W1486632395","https://openalex.org/W1967140145","https://openalex.org/W1968476015","https://openalex.org/W1994302122","https://openalex.org/W2004149082","https://openalex.org/W2015245929","https://openalex.org/W2015876616","https://openalex.org/W2066521378","https://openalex.org/W2092272787","https://openalex.org/W2110934250","https://openalex.org/W2118439990","https://openalex.org/W2133235827","https://openalex.org/W2135979612","https://openalex.org/W2138732321","https://openalex.org/W2142412278","https://openalex.org/W2148301747","https://openalex.org/W2154590984","https://openalex.org/W2160555827","https://openalex.org/W2435507717"],"related_works":["https://openalex.org/W2064636555","https://openalex.org/W2585503716","https://openalex.org/W1939982668","https://openalex.org/W2105014086","https://openalex.org/W2076090200","https://openalex.org/W4312933423","https://openalex.org/W3025682415","https://openalex.org/W1532481220","https://openalex.org/W2081173909","https://openalex.org/W4382317424"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"the":[3,88,111,119,132,173,182,191,209],"Multilevel":[4],"Gaussian":[5],"Mixture":[6],"Model":[7],"(ML_GMM),":[8],"a":[9,63,73,85,92,149,203],"novel":[10],"algorithm":[11],"for":[12,22,154],"online,":[13],"unsupervised":[14,108],"modeling":[15],"of":[16,44,65,87,131,140,157,190,205],"complex":[17,160],"motion":[18],"trajectories":[19,52,161],"which":[20],"allows":[21,172],"fast":[23],"and":[24,67,100,114,159,162],"reliable":[25,164],"abnormal":[26,101],"trajectory":[27,102],"detection":[28],"in":[29,106,148,179,185,208],"video":[30],"surveillance.":[31],"The":[32,98,129],"presented":[33],"approach":[34],"does":[35],"not":[36],"directly":[37],"deal":[38],"with":[39,181],"target":[40],"tracking":[41],"or":[42,50,94,168],"attribution":[43],"an":[45,61,80,107],"observation":[46],"to":[47,54,124,176,187,193],"either":[48],"one":[49],"another":[51],"belonging":[53],"different":[55],"targets.":[56],"Instead,":[57],"it":[58,82,171],"receives":[59],"as":[60,70,91,143,145,166],"input":[62,89],"sequence":[64],"observations":[66],"considers":[68],"them":[69],"produced":[71],"by":[72],"reliable,":[74],"yet":[75],"possibly":[76],"noisy,":[77],"tracker.":[78],"As":[79],"output,":[81],"then":[83],"produces":[84],"labeling":[86,165],"sequence,":[90],"\"normal\"":[93],"\"abnormal\"":[95],"whole":[96],"trajectory.":[97],"normal":[99,167],"domains":[103],"are":[104],"learned":[105],"fashion":[109],"during":[110],"training":[112],"phase":[113],"can":[115],"be":[116,177],"updated":[117],"while":[118],"classifier":[120],"is":[121,134,138],"running,":[122],"thanks":[123],"its":[125],"reduced":[126],"computational":[127],"complexity.":[128],"novelty":[130],"contribution":[133],"twofold.":[135],"First,":[136],"ML_GMM":[137,201],"capable":[139],"representing":[141],"short-term,":[142],"well":[144],"long-term,":[146],"transitions":[147],"consistent":[150],"way,":[151],"thus":[152],"allowing":[153],"accurate":[155],"representation":[156],"long":[158],"their":[163],"abnormal.":[169],"Second,":[170],"learning":[174],"process":[175],"run":[178],"parallel":[180],"discrimination":[183],"process,":[184],"order":[186],"support":[188],"adaptability":[189],"model":[192],"evolving":[194],"operating":[195],"conditions.":[196],"Experimental":[197],"results":[198],"show":[199],"that":[200],"outperforms":[202],"number":[204],"comparable":[206],"approaches":[207],"literature.":[210]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}