{"id":"https://openalex.org/W2117082993","doi":"https://doi.org/10.1109/iccv.2011.6126397","title":"Action recognition in videos acquired by a moving camera using motion decomposition of Lagrangian particle trajectories","display_name":"Action recognition in videos acquired by a moving camera using motion decomposition of Lagrangian particle trajectories","publication_year":2011,"publication_date":"2011-11-01","ids":{"openalex":"https://openalex.org/W2117082993","doi":"https://doi.org/10.1109/iccv.2011.6126397","mag":"2117082993"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2011.6126397","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2011.6126397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 International Conference on Computer Vision","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://stars.library.ucf.edu/scopus2010/2181","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028418236","display_name":"Shandong Wu","orcid":"https://orcid.org/0000-0002-0770-2203"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shandong Wu","raw_affiliation_strings":["Computer Vision Laboratory, University of Central Florida, USA","Computer vision Lab, University of Central Florida, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Vision Laboratory, University of Central Florida, USA","institution_ids":["https://openalex.org/I106165777"]},{"raw_affiliation_string":"Computer vision Lab, University of Central Florida, USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047906325","display_name":"Omar Oreifej","orcid":null},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Omar Oreifej","raw_affiliation_strings":["Computer Vision Laboratory, University of Central Florida, USA","Computer vision Lab, University of Central Florida, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Vision Laboratory, University of Central Florida, USA","institution_ids":["https://openalex.org/I106165777"]},{"raw_affiliation_string":"Computer vision Lab, University of Central Florida, USA","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080823547","display_name":"Mubarak Shah","orcid":"https://orcid.org/0000-0001-6172-5572"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mubarak Shah","raw_affiliation_strings":["Computer Vision Laboratory, University of Central Florida, USA","Computer vision Lab, University of Central Florida, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Vision Laboratory, University of Central Florida, USA","institution_ids":["https://openalex.org/I106165777"]},{"raw_affiliation_string":"Computer vision Lab, University of Central Florida, USA","institution_ids":["https://openalex.org/I106165777"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I106165777"],"apc_list":null,"apc_paid":null,"fwci":16.645,"has_fulltext":false,"cited_by_count":169,"citation_normalized_percentile":{"value":0.99350531,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1419","last_page":"1426"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":1.0,"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/T10812","display_name":"Human Pose and Action Recognition","score":1.0,"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":0.9994000196456909,"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":0.9983999729156494,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8446716070175171},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.8255701065063477},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6975069046020508},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.6042828559875488},{"id":"https://openalex.org/keywords/motion-compensation","display_name":"Motion compensation","score":0.5421846508979797},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.4987351894378662},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4902980625629425},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.429558128118515},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.42257606983184814},{"id":"https://openalex.org/keywords/match-moving","display_name":"Match moving","score":0.41679269075393677},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.3164965510368347},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.30727338790893555},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.2928928732872009},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09981867671012878}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8446716070175171},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.8255701065063477},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6975069046020508},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.6042828559875488},{"id":"https://openalex.org/C128840427","wikidata":"https://www.wikidata.org/wiki/Q1302174","display_name":"Motion compensation","level":2,"score":0.5421846508979797},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.4987351894378662},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4902980625629425},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.429558128118515},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.42257606983184814},{"id":"https://openalex.org/C95020103","wikidata":"https://www.wikidata.org/wiki/Q1813492","display_name":"Match moving","level":3,"score":0.41679269075393677},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.3164965510368347},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.30727338790893555},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2928928732872009},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09981867671012878},{"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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iccv.2011.6126397","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2011.6126397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 International Conference on Computer Vision","raw_type":"proceedings-article"},{"id":"pmh:oai:stars.library.ucf.edu:scopus2010-3180","is_oa":true,"landing_page_url":"https://stars.library.ucf.edu/scopus2010/2181","pdf_url":null,"source":{"id":"https://openalex.org/S4210172555","display_name":"Journal of International Crisis and Risk Communication Research","issn_l":"2576-0017","issn":["2576-0017","2576-0025"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Scopus Export 2010-2014","raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:stars.library.ucf.edu:scopus2010-3180","is_oa":true,"landing_page_url":"https://stars.library.ucf.edu/scopus2010/2181","pdf_url":null,"source":{"id":"https://openalex.org/S4210172555","display_name":"Journal of International Crisis and Risk Communication Research","issn_l":"2576-0017","issn":["2576-0017","2576-0025"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Scopus Export 2010-2014","raw_type":"text"},"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.5899999737739563}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W65124300","https://openalex.org/W79405465","https://openalex.org/W1736339626","https://openalex.org/W1973166425","https://openalex.org/W1974318954","https://openalex.org/W1980111975","https://openalex.org/W1993229407","https://openalex.org/W1993962865","https://openalex.org/W1995903777","https://openalex.org/W2003217181","https://openalex.org/W2003543060","https://openalex.org/W2010399676","https://openalex.org/W2014884175","https://openalex.org/W2021733262","https://openalex.org/W2026140901","https://openalex.org/W2034328688","https://openalex.org/W2041390734","https://openalex.org/W2088775700","https://openalex.org/W2089093274","https://openalex.org/W2104652184","https://openalex.org/W2109240917","https://openalex.org/W2116931983","https://openalex.org/W2121153043","https://openalex.org/W2125854396","https://openalex.org/W2129560725","https://openalex.org/W2130103520","https://openalex.org/W2142194269","https://openalex.org/W2153754923","https://openalex.org/W2161612652","https://openalex.org/W2163680646","https://openalex.org/W2165715280","https://openalex.org/W2166294429","https://openalex.org/W2172207578","https://openalex.org/W2533739470","https://openalex.org/W2536706996","https://openalex.org/W2951443864","https://openalex.org/W4240800952","https://openalex.org/W4249279051","https://openalex.org/W6603183647","https://openalex.org/W6640723650","https://openalex.org/W6645375654","https://openalex.org/W6675804051","https://openalex.org/W6677870410","https://openalex.org/W6683492740"],"related_works":["https://openalex.org/W1579157894","https://openalex.org/W1967654336","https://openalex.org/W2060632806","https://openalex.org/W2030154815","https://openalex.org/W2148922502","https://openalex.org/W1530267862","https://openalex.org/W2995690499","https://openalex.org/W1494405360","https://openalex.org/W2051121715","https://openalex.org/W2032827369"],"abstract_inverted_index":{"Recognition":[0],"of":[1,99,114,122,171,179],"human":[2,192],"actions":[3,193],"in":[4,41,50,120],"a":[5,9,59,71,97,115,140,168,183],"video":[6],"acquired":[7],"by":[8,103],"moving":[10,21,60,136],"camera":[11,61],"typically":[12],"requires":[13],"standard":[14,79],"preprocessing":[15],"steps":[16],"such":[17],"as":[18],"motion":[19,31,164,197],"compensation,":[20],"object":[22,25,37,127,163],"detection":[23,38,128],"and":[24,52,81,125,156,189,207,214,216],"tracking.":[26],"The":[27],"errors":[28],"from":[29,58],"the":[30,36,46,78,84,111,135,151,161,177,180,191,195],"compensation":[32],"step":[33],"propagate":[34],"to":[35,133,187],"stage,":[39,48],"resulting":[40,49],"miss-detections,":[42],"which":[43,74,95,175],"further":[44],"complicates":[45],"tracking":[47],"cluttered":[51],"incorrect":[53],"tracks.":[54],"Therefore,":[55],"action":[56],"recognition":[57],"is":[62,89,118,129,185],"considered":[63],"very":[64],"challenging.":[65],"In":[66,131],"this":[67],"paper,":[68],"we":[69,138,149,166],"propose":[70,139],"novel":[72,141],"approach":[73,88,142],"does":[75],"not":[76],"follow":[77],"steps,":[80],"accordingly":[82],"avoids":[83],"aforementioned":[85],"difficulties.":[86],"Our":[87],"based":[90,143],"on":[91,144,203],"Lagrangian":[92],"particle":[93],"trajectories":[94,101,152],"are":[96],"set":[98,170],"dense":[100],"obtained":[102,160,217],"advecting":[104],"optical":[105],"flow":[106],"over":[107],"time,":[108],"thus":[109],"capturing":[110],"ensemble":[112],"motions":[113],"scene.":[116],"This":[117],"done":[119],"frames":[121],"unaligned":[123],"video,":[124],"no":[126],"required.":[130],"order":[132],"handle":[134],"camera,":[137],"low":[145],"rank":[146],"optimization,":[147],"where":[148],"decompose":[150],"into":[153],"their":[154],"camera-induced":[155],"object-induced":[157],"components.":[158],"Having":[159],"relevant":[162],"trajectories,":[165],"compute":[167],"compact":[169],"chaotic":[172],"invariant":[173],"features":[174],"captures":[176],"characteristics":[178],"trajectories.":[181],"Consequently,":[182],"SVM":[184],"employed":[186],"learn":[188],"recognize":[190],"using":[194],"computed":[196],"features.":[198],"We":[199],"performed":[200],"intensive":[201],"experiments":[202],"multiple":[204],"benchmark":[205],"datasets":[206,211],"two":[208],"new":[209],"aerial":[210],"called":[212],"ARG":[213],"APHill,":[215],"promising":[218],"results.":[219]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":10},{"year":2018,"cited_by_count":11},{"year":2017,"cited_by_count":8},{"year":2016,"cited_by_count":16},{"year":2015,"cited_by_count":25},{"year":2014,"cited_by_count":31},{"year":2013,"cited_by_count":27},{"year":2012,"cited_by_count":11}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}