{"id":"https://openalex.org/W2142125366","doi":"https://doi.org/10.1109/iccv.2011.6126365","title":"Gaussian process regression flow for analysis of motion trajectories","display_name":"Gaussian process regression flow for analysis of motion trajectories","publication_year":2011,"publication_date":"2011-11-01","ids":{"openalex":"https://openalex.org/W2142125366","doi":"https://doi.org/10.1109/iccv.2011.6126365","mag":"2142125366"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2011.6126365","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2011.6126365","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":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100655396","display_name":"Kihwan Kim","orcid":"https://orcid.org/0000-0003-0257-1707"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kihwan Kim","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA","[Georgia Institute of Technology, Atlanta, USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"[Georgia Institute of Technology, Atlanta, USA]","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077348778","display_name":"Dongryeol Lee","orcid":null},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Dongryeol Lee","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA","[Georgia Institute of Technology, Atlanta, USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"[Georgia Institute of Technology, Atlanta, USA]","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5070348998","display_name":"Irfan Essa","orcid":"https://orcid.org/0000-0002-6236-2969"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Irfan Essa","raw_affiliation_strings":["Georgia Institute of Technology, Atlanta, GA, USA","[Georgia Institute of Technology, Atlanta, USA]"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"[Georgia Institute of Technology, Atlanta, USA]","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":null,"apc_paid":null,"fwci":6.4747,"has_fulltext":false,"cited_by_count":174,"citation_normalized_percentile":{"value":0.97592027,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1164","last_page":"1171"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9997000098228455,"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":0.9997000098228455,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9927999973297119,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9865999817848206,"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/trajectory","display_name":"Trajectory","score":0.6818872690200806},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6698616743087769},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.6382830142974854},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6364601254463196},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6030292510986328},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.564087450504303},{"id":"https://openalex.org/keywords/acceleration","display_name":"Acceleration","score":0.5572214126586914},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5276773571968079},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4576604962348938},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4374432861804962},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.4360724687576294},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4277946949005127},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4226493835449219},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.41650086641311646},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23333781957626343}],"concepts":[{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6818872690200806},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6698616743087769},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.6382830142974854},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6364601254463196},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6030292510986328},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.564087450504303},{"id":"https://openalex.org/C117896860","wikidata":"https://www.wikidata.org/wiki/Q11376","display_name":"Acceleration","level":2,"score":0.5572214126586914},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5276773571968079},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4576604962348938},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4374432861804962},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.4360724687576294},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4277946949005127},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4226493835449219},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.41650086641311646},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23333781957626343},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","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},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv.2011.6126365","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2011.6126365","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:CiteSeerX.psu:10.1.1.364.4109","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.364.4109","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cc.gatech.edu/~irfan/p/2011-Kim-GPRFAMT.pdf","raw_type":"text"},{"id":"pmh:oai:smartech.gatech.edu:1853/42261","is_oa":false,"landing_page_url":"http://hdl.handle.net/1853/42261","pdf_url":null,"source":{"id":"https://openalex.org/S4377196313","display_name":"SMARTech Repository (Georgia Institute of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I130701444","host_organization_name":"Georgia Institute of Technology","host_organization_lineage":["https://openalex.org/I130701444"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Proceedings"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.41999998688697815}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1482815597","https://openalex.org/W1502922572","https://openalex.org/W1534304300","https://openalex.org/W1560013842","https://openalex.org/W1965520710","https://openalex.org/W1966406756","https://openalex.org/W1989037929","https://openalex.org/W1996081046","https://openalex.org/W2008400752","https://openalex.org/W2031352624","https://openalex.org/W2037629065","https://openalex.org/W2040321327","https://openalex.org/W2063686375","https://openalex.org/W2097412577","https://openalex.org/W2122075562","https://openalex.org/W2122646361","https://openalex.org/W2124609748","https://openalex.org/W2147880780","https://openalex.org/W2148238513","https://openalex.org/W2151263703","https://openalex.org/W2497516627","https://openalex.org/W3029645440","https://openalex.org/W4242702158","https://openalex.org/W4293775970","https://openalex.org/W6628681060","https://openalex.org/W6629804754","https://openalex.org/W6641900180","https://openalex.org/W6682028543"],"related_works":["https://openalex.org/W4323768008","https://openalex.org/W3131574667","https://openalex.org/W4248382324","https://openalex.org/W1989791859","https://openalex.org/W4360995134","https://openalex.org/W2039473718","https://openalex.org/W2387529410","https://openalex.org/W2390829436","https://openalex.org/W3023605104","https://openalex.org/W1971289376"],"abstract_inverted_index":{"Recognition":[0],"of":[1,5,16,47,65,90,134,142],"motions":[2,66,92],"and":[3,14,78,96,110,118,136],"activities":[4],"objects":[6],"in":[7,114],"videos":[8],"requires":[9],"effective":[10],"representations":[11],"for":[12,61,73,108],"analysis":[13],"matching":[15,30,89],"motion":[17,31,112],"trajectories.":[18,32,84],"In":[19],"this":[20],"paper,":[21],"we":[22,55],"introduce":[23,56],"a":[24,35,38,44,57,101,140],"new":[25],"representation":[26,71,86],"specifically":[27],"aimed":[28],"at":[29],"We":[33,103,124],"model":[34],"trajectory":[36],"as":[37],"continuous":[39],"dense":[40],"flow":[41],"field":[42],"from":[43,67,82,139],"sparse":[45],"set":[46],"vector":[48],"sequences":[49],"using":[50],"Gaussian":[51],"Process":[52],"Regression.":[53],"Furthermore,":[54],"random":[58],"sampling":[59],"strategy":[60],"learning":[62],"stable":[63],"classes":[64],"limited":[68],"data.":[69],"Our":[70],"allows":[72],"incrementally":[74],"predicting":[75,111],"possible":[76],"paths":[77],"detecting":[79],"anomalous":[80],"events":[81],"online":[83],"This":[85],"also":[87],"supports":[88],"complex":[91],"with":[93,146],"acceleration":[94],"changes":[95],"pauses":[97],"or":[98],"stops":[99],"within":[100],"trajectory.":[102],"use":[104],"the":[105],"proposed":[106],"approach":[107,128],"classifying":[109],"trajectories":[113,138],"traffic":[115],"monitoring":[116],"domains":[117],"test":[119],"on":[120,131],"several":[121],"data":[122,144],"sets.":[123],"show":[125],"that":[126],"our":[127],"works":[129],"well":[130],"various":[132],"types":[133],"complete":[135],"incomplete":[137],"variety":[141],"video":[143],"sets":[145],"different":[147],"frame":[148],"rates.":[149]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":19},{"year":2018,"cited_by_count":28},{"year":2017,"cited_by_count":15},{"year":2016,"cited_by_count":21},{"year":2015,"cited_by_count":22},{"year":2014,"cited_by_count":12},{"year":2013,"cited_by_count":7},{"year":2012,"cited_by_count":5}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
