{"id":"https://openalex.org/W2895976745","doi":"https://doi.org/10.1109/icme.2018.8486439","title":"Robust Object Tracking Via Part-Based Correlation Particle Filter","display_name":"Robust Object Tracking Via Part-Based Correlation Particle Filter","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2895976745","doi":"https://doi.org/10.1109/icme.2018.8486439","mag":"2895976745"},"language":"en","primary_location":{"id":"doi:10.1109/icme.2018.8486439","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2018.8486439","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Multimedia and Expo (ICME)","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/A5100387149","display_name":"Ning Wang","orcid":"https://orcid.org/0000-0002-4937-6784"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Ning Wang","raw_affiliation_strings":["EElS Department, University of Science and Technology of China"],"affiliations":[{"raw_affiliation_string":"EElS Department, University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046805800","display_name":"Wengang Zhou","orcid":"https://orcid.org/0000-0003-1690-9836"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wengang Zhou","raw_affiliation_strings":["EElS Department, University of Science and Technology of China"],"affiliations":[{"raw_affiliation_string":"EElS Department, University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078141810","display_name":"Houqiang Li","orcid":"https://orcid.org/0000-0003-2188-3028"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Houqiang Li","raw_affiliation_strings":["EElS Department, University of Science and Technology of China"],"affiliations":[{"raw_affiliation_string":"EElS Department, University of Science and Technology of China","institution_ids":["https://openalex.org/I126520041"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100387149"],"corresponding_institution_ids":["https://openalex.org/I126520041"],"apc_list":null,"apc_paid":null,"fwci":0.3191,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.63191821,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","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/T10331","display_name":"Video Surveillance and Tracking Methods","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/T10812","display_name":"Human Pose and Action Recognition","score":0.9760000109672546,"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/T11019","display_name":"Image Enhancement Techniques","score":0.9564999938011169,"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/particle-filter","display_name":"Particle filter","score":0.8206814527511597},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.7062050700187683},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6833819150924683},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6801836490631104},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6535966396331787},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6038885116577148},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.561614453792572},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.463432639837265},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4484090507030487},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.44669365882873535},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4421250522136688},{"id":"https://openalex.org/keywords/rotation","display_name":"Rotation (mathematics)","score":0.4364132881164551},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.41921624541282654},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3631848990917206},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.3385026156902313},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12268796563148499},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07351064682006836}],"concepts":[{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.8206814527511597},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.7062050700187683},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6833819150924683},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6801836490631104},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6535966396331787},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6038885116577148},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.561614453792572},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.463432639837265},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4484090507030487},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.44669365882873535},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4421250522136688},{"id":"https://openalex.org/C74050887","wikidata":"https://www.wikidata.org/wiki/Q848368","display_name":"Rotation (mathematics)","level":2,"score":0.4364132881164551},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.41921624541282654},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3631848990917206},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.3385026156902313},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12268796563148499},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07351064682006836},{"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},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme.2018.8486439","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2018.8486439","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7900000214576721,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W29474918","https://openalex.org/W182940129","https://openalex.org/W818325216","https://openalex.org/W1857884451","https://openalex.org/W1908905119","https://openalex.org/W1915785815","https://openalex.org/W1937954682","https://openalex.org/W1955741794","https://openalex.org/W1964846093","https://openalex.org/W1997121481","https://openalex.org/W2051832123","https://openalex.org/W2089961441","https://openalex.org/W2154889144","https://openalex.org/W2158592639","https://openalex.org/W2160337655","https://openalex.org/W2161969291","https://openalex.org/W2165037244","https://openalex.org/W2214352687","https://openalex.org/W2244956674","https://openalex.org/W2380373457","https://openalex.org/W2469582947","https://openalex.org/W2470394683","https://openalex.org/W2473868734","https://openalex.org/W2474516676","https://openalex.org/W2518013266","https://openalex.org/W2557641257","https://openalex.org/W2577770985","https://openalex.org/W2604793351","https://openalex.org/W2742165450","https://openalex.org/W2751826409","https://openalex.org/W2792121015","https://openalex.org/W2798842862","https://openalex.org/W2964111344","https://openalex.org/W3102624093","https://openalex.org/W6601205835","https://openalex.org/W6607635097","https://openalex.org/W6623108133","https://openalex.org/W6649598916","https://openalex.org/W6684332838","https://openalex.org/W6709919914","https://openalex.org/W6720586528","https://openalex.org/W6726293469","https://openalex.org/W6731979120","https://openalex.org/W6748931871","https://openalex.org/W6750359169"],"related_works":["https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W1482209366","https://openalex.org/W2012200063","https://openalex.org/W2100525497","https://openalex.org/W2965594636"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,23,46],"part-based":[4],"correlation":[5,20],"particle":[6,24,47],"filter":[7,25],"framework":[8],"is":[9],"proposed":[10],"for":[11],"robust":[12],"visual":[13],"tracking.":[14],"Through":[15],"managing":[16],"target":[17,31],"parts":[18,37],"by":[19,90],"filters":[21],"in":[22],"framework,":[26],"we":[27,44,93],"comprehensively":[28],"model":[29,87],"the":[30,58,69,79,95,107],"appearance":[32,51],"using":[33],"plentiful":[34],"overlapped":[35],"local":[36,73,84],"with":[38,50,78,136],"different":[39],"positions":[40],"and":[41,52,71,86,99,138],"sizes.":[42],"Further,":[43],"propose":[45],"re-sampling":[48],"mechanism":[49],"geometry":[53],"reliability":[54],"consideration":[55],"to":[56,65,76,104],"resam-ple":[57],"redundant":[59],"particles,":[60],"which":[61],"guides":[62],"our":[63,118,127],"tracker":[64,85],"focus":[66],"more":[67],"on":[68,112,132],"discriminative":[70],"reliable":[72],"parts.":[74],"Finally,":[75],"cope":[77],"limited":[80],"search":[81],"range":[82],"of":[83],"corruption":[88],"caused":[89],"unreliable":[91],"samples,":[92],"introduce":[94],"top-down":[96],"coarse-to-fine":[97],"localization":[98],"bottom-up":[100],"adaptive":[101],"update":[102],"strategies":[103],"further":[105],"boost":[106],"performance.":[108],"Extensive":[109],"experimental":[110],"results":[111],"three":[113],"challenging":[114],"datasets":[115],"demonstrate":[116],"that":[117],"tracking":[119,133],"algorithm":[120],"performs":[121],"favorably":[122],"against":[123],"state-of-the-art":[124],"methods.":[125],"Specifically,":[126],"approach":[128],"exhibits":[129],"superior":[130],"performance":[131],"nonrigid":[134],"objects":[135],"rotation":[137],"large":[139],"deformation.":[140]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2026-03-25T13:04:00.132906","created_date":"2025-10-10T00:00:00"}
