{"id":"https://openalex.org/W2114008489","doi":"https://doi.org/10.1109/wacv.2013.6475058","title":"A Bayesian non-parametric viewpoint to visual tracking","display_name":"A Bayesian non-parametric viewpoint to visual tracking","publication_year":2013,"publication_date":"2013-01-01","ids":{"openalex":"https://openalex.org/W2114008489","doi":"https://doi.org/10.1109/wacv.2013.6475058","mag":"2114008489"},"language":"en","primary_location":{"id":"doi:10.1109/wacv.2013.6475058","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv.2013.6475058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE Workshop on Applications of Computer Vision (WACV)","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/A5100364982","display_name":"Yi Wang","orcid":"https://orcid.org/0000-0002-8448-8570"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]},{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Yi Wang","raw_affiliation_strings":["National ICT Australia, Australia","School of CSE, University of New South Wales, Australia"],"affiliations":[{"raw_affiliation_string":"National ICT Australia, Australia","institution_ids":["https://openalex.org/I42894916"]},{"raw_affiliation_string":"School of CSE, University of New South Wales, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100676631","display_name":"Zhidong Li","orcid":"https://orcid.org/0000-0003-3288-5547"},"institutions":[{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]},{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Zhidong Li","raw_affiliation_strings":["National ICT Australia, Australia","School of CSE, University of New South Wales, Australia"],"affiliations":[{"raw_affiliation_string":"National ICT Australia, Australia","institution_ids":["https://openalex.org/I42894916"]},{"raw_affiliation_string":"School of CSE, University of New South Wales, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100714578","display_name":"Yang Wang","orcid":"https://orcid.org/0000-0002-6815-0879"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]},{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yang Wang","raw_affiliation_strings":["National ICT Australia, Australia","School of CSE, University of New South Wales, Australia"],"affiliations":[{"raw_affiliation_string":"National ICT Australia, Australia","institution_ids":["https://openalex.org/I42894916"]},{"raw_affiliation_string":"School of CSE, University of New South Wales, Australia","institution_ids":["https://openalex.org/I31746571"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100400043","display_name":"Fang Chen","orcid":"https://orcid.org/0000-0003-4971-8729"},"institutions":[{"id":"https://openalex.org/I31746571","display_name":"UNSW Sydney","ror":"https://ror.org/03r8z3t63","country_code":"AU","type":"education","lineage":["https://openalex.org/I31746571"]},{"id":"https://openalex.org/I42894916","display_name":"Data61","ror":"https://ror.org/03q397159","country_code":"AU","type":"other","lineage":["https://openalex.org/I1292875679","https://openalex.org/I2801453606","https://openalex.org/I42894916","https://openalex.org/I4387156119"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Fang Chen","raw_affiliation_strings":["National ICT Australia, Australia","School of CSE, University of New South Wales, Australia"],"affiliations":[{"raw_affiliation_string":"National ICT Australia, Australia","institution_ids":["https://openalex.org/I42894916"]},{"raw_affiliation_string":"School of CSE, University of New South Wales, Australia","institution_ids":["https://openalex.org/I31746571"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100364982"],"corresponding_institution_ids":["https://openalex.org/I31746571","https://openalex.org/I42894916"],"apc_list":null,"apc_paid":null,"fwci":0.4809,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.76922533,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"21","issue":null,"first_page":"482","last_page":"488"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11901","display_name":"Bayesian Methods and Mixture Models","score":0.9937000274658203,"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":0.9937000274658203,"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":0.988099992275238,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.939300000667572,"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/posterior-probability","display_name":"Posterior probability","score":0.6878515481948853},{"id":"https://openalex.org/keywords/gibbs-sampling","display_name":"Gibbs sampling","score":0.6348484754562378},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5862082839012146},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.5846313238143921},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5705420970916748},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5598278045654297},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5081734657287598},{"id":"https://openalex.org/keywords/bayesian-inference","display_name":"Bayesian inference","score":0.4894017279148102},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.45462656021118164},{"id":"https://openalex.org/keywords/parametric-model","display_name":"Parametric model","score":0.4523107707500458},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.45163142681121826},{"id":"https://openalex.org/keywords/kullback\u2013leibler-divergence","display_name":"Kullback\u2013Leibler divergence","score":0.450354665517807},{"id":"https://openalex.org/keywords/divergence","display_name":"Divergence (linguistics)","score":0.4325394630432129},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.42493951320648193},{"id":"https://openalex.org/keywords/conjugate-prior","display_name":"Conjugate prior","score":0.4118598401546478},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.37407857179641724},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.2493669092655182},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.22522318363189697}],"concepts":[{"id":"https://openalex.org/C57830394","wikidata":"https://www.wikidata.org/wiki/Q278079","display_name":"Posterior probability","level":3,"score":0.6878515481948853},{"id":"https://openalex.org/C158424031","wikidata":"https://www.wikidata.org/wiki/Q1191905","display_name":"Gibbs sampling","level":3,"score":0.6348484754562378},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5862082839012146},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.5846313238143921},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5705420970916748},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5598278045654297},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5081734657287598},{"id":"https://openalex.org/C160234255","wikidata":"https://www.wikidata.org/wiki/Q812535","display_name":"Bayesian inference","level":3,"score":0.4894017279148102},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.45462656021118164},{"id":"https://openalex.org/C24574437","wikidata":"https://www.wikidata.org/wiki/Q7135228","display_name":"Parametric model","level":3,"score":0.4523107707500458},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.45163142681121826},{"id":"https://openalex.org/C171752962","wikidata":"https://www.wikidata.org/wiki/Q255166","display_name":"Kullback\u2013Leibler divergence","level":2,"score":0.450354665517807},{"id":"https://openalex.org/C207390915","wikidata":"https://www.wikidata.org/wiki/Q1230525","display_name":"Divergence (linguistics)","level":2,"score":0.4325394630432129},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.42493951320648193},{"id":"https://openalex.org/C26004113","wikidata":"https://www.wikidata.org/wiki/Q3711784","display_name":"Conjugate prior","level":4,"score":0.4118598401546478},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.37407857179641724},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2493669092655182},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.22522318363189697},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wacv.2013.6475058","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv.2013.6475058","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE Workshop on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":42,"referenced_works":["https://openalex.org/W1517266559","https://openalex.org/W1965555277","https://openalex.org/W1974600023","https://openalex.org/W1987532879","https://openalex.org/W1995757792","https://openalex.org/W2011510073","https://openalex.org/W2020213096","https://openalex.org/W2020999234","https://openalex.org/W2021179991","https://openalex.org/W2026999222","https://openalex.org/W2033178790","https://openalex.org/W2049633694","https://openalex.org/W2069429561","https://openalex.org/W2098854771","https://openalex.org/W2102625004","https://openalex.org/W2110116545","https://openalex.org/W2115609520","https://openalex.org/W2117287544","https://openalex.org/W2127498532","https://openalex.org/W2131854835","https://openalex.org/W2134176306","https://openalex.org/W2139047213","https://openalex.org/W2147357149","https://openalex.org/W2148180395","https://openalex.org/W2156757627","https://openalex.org/W2158266063","https://openalex.org/W2162876232","https://openalex.org/W2163738067","https://openalex.org/W2167089254","https://openalex.org/W2496034786","https://openalex.org/W4231340930","https://openalex.org/W4231517135","https://openalex.org/W6631033597","https://openalex.org/W6644006693","https://openalex.org/W6649185964","https://openalex.org/W6667932521","https://openalex.org/W6677218472","https://openalex.org/W6677370918","https://openalex.org/W6683603713","https://openalex.org/W6684055098","https://openalex.org/W6684274140","https://openalex.org/W6723243674"],"related_works":["https://openalex.org/W2053989673","https://openalex.org/W2060989303","https://openalex.org/W2101825047","https://openalex.org/W2053405531","https://openalex.org/W2123736748","https://openalex.org/W4231537836","https://openalex.org/W2094015288","https://openalex.org/W2115685217","https://openalex.org/W2335394797","https://openalex.org/W1581986412"],"abstract_inverted_index":{"A":[0],"novel":[1],"bayesian":[2],"non-parametric":[3,25],"method":[4],"for":[5,88],"tracking":[6],"is":[7,16,61,86,96],"proposed":[8],"in":[9],"this":[10,70],"paper.":[11],"The":[12,91],"foreground":[13],"appearance":[14],"distribution":[15],"modeled":[17],"by":[18,51,98],"unbounded":[19],"mixtures":[20],"controlled":[21],"through":[22],"a":[23],"Bayesian":[24],"process.":[26],"Two":[27],"posterior":[28,55],"inference":[29],"strategies":[30],"are":[31],"provided:":[32],"Gibbs":[33],"sampling":[34,43],"and":[35,83],"sequential":[36],"importance":[37],"sampling.":[38],"Both":[39],"of":[40,65,93],"these":[41],"two":[42],"strategy":[44],"benefits":[45],"from":[46],"the":[47,53,58,63,80,99],"conjugate":[48],"prior/posterior":[49],"pairs":[50],"factorizing":[52],"joint":[54],"distributions.":[56],"Once":[57],"mixture":[59,71],"model":[60,72,78],"obtained/updated,":[62],"similarities/probablity":[64],"each":[66],"observations":[67],"assigned":[68],"to":[69],"could":[73],"be":[74],"easily":[75],"calculated.":[76],"In":[77],"matching/verification,":[79],"Kullback-Leibler":[81],"divergence":[82],"texture":[84],"information":[85],"adopted":[87],"verification":[89],"purpose.":[90],"robustness":[92],"our":[94],"methods":[95],"demonstrated":[97],"experiments.":[100]},"counts_by_year":[{"year":2013,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}