{"id":"https://openalex.org/W1989815277","doi":"https://doi.org/10.1109/apsipa.2013.6694177","title":"Visual tracking using the joint inference of target state and segment-based appearance models","display_name":"Visual tracking using the joint inference of target state and segment-based appearance models","publication_year":2013,"publication_date":"2013-10-01","ids":{"openalex":"https://openalex.org/W1989815277","doi":"https://doi.org/10.1109/apsipa.2013.6694177","mag":"1989815277"},"language":"en","primary_location":{"id":"doi:10.1109/apsipa.2013.6694177","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipa.2013.6694177","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference","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/A5021486262","display_name":"Junha Roh","orcid":null},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Junha Roh","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea","Dept. of Electr. & Comput. Eng., Seoul Nat. Univ., Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Seoul Nat. Univ., Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021207493","display_name":"Dong Woo Park","orcid":"https://orcid.org/0000-0002-7507-1175"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dong Woo Park","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea","Dept. of Electr. & Comput. Eng., Seoul Nat. Univ., Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Seoul Nat. Univ., Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045083125","display_name":"Junseok Kwon","orcid":"https://orcid.org/0000-0001-9526-7549"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Junseok Kwon","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea","Dept. of Electr. & Comput. Eng., Seoul Nat. Univ., Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Seoul Nat. Univ., Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046504049","display_name":"Kyoung Mu Lee","orcid":"https://orcid.org/0000-0001-7210-1036"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Kyoung Mu Lee","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea","Dept. of Electr. & Comput. Eng., Seoul Nat. Univ., Seoul, South Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Seoul National University, Seoul, Korea","institution_ids":["https://openalex.org/I139264467"]},{"raw_affiliation_string":"Dept. of Electr. & Comput. Eng., Seoul Nat. Univ., Seoul, South Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139264467"],"apc_list":null,"apc_paid":null,"fwci":0.2079,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.40872263,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"4"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9998999834060669,"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":0.9998999834060669,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.978600025177002,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9778000116348267,"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/discriminative-model","display_name":"Discriminative model","score":0.7843229174613953},{"id":"https://openalex.org/keywords/active-appearance-model","display_name":"Active appearance model","score":0.7345992922782898},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6615240573883057},{"id":"https://openalex.org/keywords/bittorrent-tracker","display_name":"BitTorrent tracker","score":0.6255665421485901},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6120651364326477},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.6058172583580017},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.5905892252922058},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.5699105858802795},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5430821776390076},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.5066707730293274},{"id":"https://openalex.org/keywords/markov-chain-monte-carlo","display_name":"Markov chain Monte Carlo","score":0.49740031361579895},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.41845810413360596},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3925034999847412},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3846890926361084},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2710801959037781},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10386055707931519}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7843229174613953},{"id":"https://openalex.org/C83248878","wikidata":"https://www.wikidata.org/wiki/Q344000","display_name":"Active appearance model","level":3,"score":0.7345992922782898},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6615240573883057},{"id":"https://openalex.org/C57501372","wikidata":"https://www.wikidata.org/wiki/Q2021268","display_name":"BitTorrent tracker","level":3,"score":0.6255665421485901},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6120651364326477},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6058172583580017},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.5905892252922058},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.5699105858802795},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5430821776390076},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.5066707730293274},{"id":"https://openalex.org/C111350023","wikidata":"https://www.wikidata.org/wiki/Q1191869","display_name":"Markov chain Monte Carlo","level":3,"score":0.49740031361579895},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.41845810413360596},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3925034999847412},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3846890926361084},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2710801959037781},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10386055707931519},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C157286648","wikidata":"https://www.wikidata.org/wiki/Q846780","display_name":"Kalman filter","level":2,"score":0.0},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/apsipa.2013.6694177","is_oa":false,"landing_page_url":"https://doi.org/10.1109/apsipa.2013.6694177","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.720.3438","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.720.3438","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://cv.snu.ac.kr/publication/conf/2013/Segment_APSIPA2013.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7699999809265137,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1501586228","https://openalex.org/W1995266040","https://openalex.org/W2072348815","https://openalex.org/W2098854771","https://openalex.org/W2102674365","https://openalex.org/W2103846358","https://openalex.org/W2109026901","https://openalex.org/W2110671801","https://openalex.org/W2126108553","https://openalex.org/W2156547441","https://openalex.org/W2158917775","https://openalex.org/W2167089254","https://openalex.org/W2168802423","https://openalex.org/W2258435667","https://openalex.org/W2294602567","https://openalex.org/W4231340930","https://openalex.org/W6641498600","https://openalex.org/W6676190106","https://openalex.org/W6676243939","https://openalex.org/W6678718671","https://openalex.org/W6684274140","https://openalex.org/W6684760091","https://openalex.org/W6692149689","https://openalex.org/W6697111280"],"related_works":["https://openalex.org/W2126907425","https://openalex.org/W2208639223","https://openalex.org/W2114656557","https://openalex.org/W2195963939","https://openalex.org/W1499764293","https://openalex.org/W2514372983","https://openalex.org/W1497303808","https://openalex.org/W2075503097","https://openalex.org/W2062103941","https://openalex.org/W4384788979"],"abstract_inverted_index":{"In":[0],"this":[1,68],"paper,":[2],"a":[3],"robust":[4],"visual":[5],"tracking":[6,12],"method":[7,138],"is":[8],"proposed":[9,137],"by":[10,84],"casting":[11],"as":[13,32],"an":[14,95,127],"estimation":[15],"problem":[16],"of":[17,21,100,110,133],"the":[18,33,43,86,101,107,131,152],"joint":[19,102],"space":[20],"non-rigid":[22,49,71],"appearance":[23,34,50,72,113],"model":[24,35,114],"and":[25,56,97,106,122,151,160],"state.":[26],"Conventional":[27],"trackers":[28,46,147],"which":[29,93],"use":[30,48],"templates":[31],"do":[36],"not":[37],"handle":[38],"ambiguous":[39],"samples":[40],"effectively.":[41],"On":[42],"other":[44,145],"hand,":[45],"that":[47],"models":[51,73,80,124],"have":[52],"low":[53],"discriminative":[54],"power":[55],"lack":[57],"methods":[58,61],"for":[59],"restoring":[60],"from":[62,78],"inaccurately":[63],"labeled":[64],"data.":[65],"To":[66],"address":[67],"problem,":[69],"multiple":[70,116,123],"are":[74,81],"proposed.":[75],"The":[76,136],"probabilities":[77],"these":[79],"effectively":[82],"marginalized":[83],"using":[85],"particle":[87],"Markov":[88],"chain":[89],"Monte":[90],"Carlo":[91],"framework":[92],"provides":[94],"exact":[96],"efficient":[98],"approximation":[99],"density":[103],"through":[104],"marginalization":[105],"theoretical":[108],"evidences":[109],"convergence.":[111],"An":[112],"combines":[115],"classification":[117],"results":[118],"with":[119,143],"different":[120],"features":[121],"can":[125],"infer":[126],"accurate":[128],"solution":[129],"despite":[130],"failure":[132],"several":[134],"models.":[135],"exhibits":[139],"high":[140],"accuracy":[141],"compared":[142],"nine":[144],"state-of-the-art":[146],"in":[148],"various":[149],"sequences":[150],"result":[153],"was":[154],"analyzed":[155,157],"both":[156,158],"qualitatively":[159],"quantitatively.":[161]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
