{"id":"https://openalex.org/W2025608598","doi":"https://doi.org/10.1109/icip.2009.5413702","title":"An object tracking method using particle filter and scale space model","display_name":"An object tracking method using particle filter and scale space model","publication_year":2009,"publication_date":"2009-11-01","ids":{"openalex":"https://openalex.org/W2025608598","doi":"https://doi.org/10.1109/icip.2009.5413702","mag":"2025608598"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2009.5413702","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2009.5413702","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 16th IEEE International Conference on Image Processing (ICIP)","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/A5039766146","display_name":"PyeongGang Heo","orcid":"https://orcid.org/0000-0001-9809-3230"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"PyeongGang Heo","raw_affiliation_strings":["Dept. of Electrical Engineering, Korea Advanced Institute of Science and Technology, Korea","[Department of Electrical Engineering, Korea Advanced Institute of Science & Technology, Korea]"],"affiliations":[{"raw_affiliation_string":"Dept. of Electrical Engineering, Korea Advanced Institute of Science and Technology, Korea","institution_ids":["https://openalex.org/I157485424"]},{"raw_affiliation_string":"[Department of Electrical Engineering, Korea Advanced Institute of Science & Technology, Korea]","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100733404","display_name":"Sujin Park","orcid":"https://orcid.org/0000-0003-3350-3723"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Su-Jin Park","raw_affiliation_strings":["EO/IRR&D Center, LIGNex1, Korea","EO/IR R&D Center, LIGNex1, Korea"],"affiliations":[{"raw_affiliation_string":"EO/IRR&D Center, LIGNex1, Korea","institution_ids":[]},{"raw_affiliation_string":"EO/IR R&D Center, LIGNex1, Korea","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010191417","display_name":"Sang-Hung Jin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sang-Hung Jin","raw_affiliation_strings":["EO/IRR&D Center, LIGNex1, Korea","EO/IR R&D Center, LIGNex1, Korea"],"affiliations":[{"raw_affiliation_string":"EO/IRR&D Center, LIGNex1, Korea","institution_ids":[]},{"raw_affiliation_string":"EO/IR R&D Center, LIGNex1, Korea","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5086710838","display_name":"Bo Yeoun Yeou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bo Yeoun Yeou","raw_affiliation_strings":["EO/IRR&D Center, LIGNex1, Korea","EO/IR R&D Center, LIGNex1, Korea"],"affiliations":[{"raw_affiliation_string":"EO/IRR&D Center, LIGNex1, Korea","institution_ids":[]},{"raw_affiliation_string":"EO/IR R&D Center, LIGNex1, Korea","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102949972","display_name":"HyunWook Park","orcid":"https://orcid.org/0000-0002-4757-1922"},"institutions":[{"id":"https://openalex.org/I4210134443","display_name":"Daejeon Institute of Science and Technology","ror":"https://ror.org/032qr1v70","country_code":"KR","type":"education","lineage":["https://openalex.org/I4210134443"]},{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"HyunWook Park","raw_affiliation_strings":["Korea Advanced Institute of Science and Technology, Daejeon, Daejeon, KR","[Department of Electrical Engineering, Korea Advanced Institute of Science & Technology, Korea]"],"affiliations":[{"raw_affiliation_string":"Korea Advanced Institute of Science and Technology, Daejeon, Daejeon, KR","institution_ids":["https://openalex.org/I4210134443","https://openalex.org/I157485424"]},{"raw_affiliation_string":"[Department of Electrical Engineering, Korea Advanced Institute of Science & Technology, Korea]","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5039766146"],"corresponding_institution_ids":["https://openalex.org/I157485424"],"apc_list":null,"apc_paid":null,"fwci":0.3236,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.58268542,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"4081","last_page":"4084"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9994000196456909,"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":0.9994000196456909,"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.8289837837219238},{"id":"https://openalex.org/keywords/particle-filter","display_name":"Particle filter","score":0.7160171866416931},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7069888114929199},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6780057549476624},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.640686571598053},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.6107944846153259},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.547452986240387},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5291804671287537},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.5179754495620728},{"id":"https://openalex.org/keywords/scale-space","display_name":"Scale space","score":0.4997265338897705},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.4856180250644684},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.47118380665779114},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4538823068141937},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4496501088142395},{"id":"https://openalex.org/keywords/active-appearance-model","display_name":"Active appearance model","score":0.4374280273914337},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.30886226892471313},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2813068926334381},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.20217940211296082},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07984927296638489}],"concepts":[{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.8289837837219238},{"id":"https://openalex.org/C52421305","wikidata":"https://www.wikidata.org/wiki/Q1151499","display_name":"Particle filter","level":3,"score":0.7160171866416931},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7069888114929199},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6780057549476624},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.640686571598053},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.6107944846153259},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.547452986240387},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5291804671287537},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.5179754495620728},{"id":"https://openalex.org/C99102927","wikidata":"https://www.wikidata.org/wiki/Q3058184","display_name":"Scale space","level":4,"score":0.4997265338897705},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.4856180250644684},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.47118380665779114},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4538823068141937},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4496501088142395},{"id":"https://openalex.org/C83248878","wikidata":"https://www.wikidata.org/wiki/Q344000","display_name":"Active appearance model","level":3,"score":0.4374280273914337},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.30886226892471313},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2813068926334381},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.20217940211296082},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07984927296638489},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2009.5413702","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2009.5413702","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 16th IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2011635389","https://openalex.org/W2110116545","https://openalex.org/W2110744759","https://openalex.org/W2125907508","https://openalex.org/W2132103241","https://openalex.org/W2134875050","https://openalex.org/W2160337655"],"related_works":["https://openalex.org/W2015530857","https://openalex.org/W2107628111","https://openalex.org/W2394004323","https://openalex.org/W2100525497","https://openalex.org/W2390166912","https://openalex.org/W2132541102","https://openalex.org/W2963010494","https://openalex.org/W2012200063","https://openalex.org/W2107332757","https://openalex.org/W2132182117"],"abstract_inverted_index":{"In":[0,21],"this":[1],"paper,":[2],"we":[3],"propose":[4,93],"and":[5,31,55,100,116],"object":[6,12],"tracking":[7],"algorithm":[8],"to":[9,46,59],"track":[10],"an":[11,94],"on":[13,25,33],"IR":[14],"image":[15],"sequences,":[16],"which":[17,109],"has":[18],"appearance":[19],"changes.":[20],"our":[22],"framework":[23],"based":[24],"particle":[26],"filter,":[27],"histograms":[28],"of":[29,42,51,61,65,97],"intensity":[30,43],"orientation":[32,67],"scale":[34,79],"space":[35],"are":[36,76],"used":[37],"as":[38],"observation":[39],"models.":[40],"Histogram":[41,64],"is":[44],"robust":[45],"shape":[47],"variation":[48],"but":[49],"lack":[50],"distinction":[52],"between":[53],"target":[54,81,111],"similar":[56],"background":[57],"due":[58],"loss":[60],"spatial":[62,70],"information.":[63,71],"gradient":[66],"complements":[68],"the":[69,73,102],"Because":[72],"histogram":[74],"models":[75],"extracted":[77],"from":[78],"space,":[80],"model":[82,87,98],"maintains":[83],"consistency":[84],"with":[85],"initial":[86],"in":[88,108,114],"different":[89],"scales.":[90],"We":[91],"also":[92],"efficient":[95],"method":[96,104],"update":[99],"demonstrate":[101],"proposed":[103],"for":[105],"several":[106],"sequences":[107],"a":[110],"changes":[112],"largely":[113],"size":[115],"appearance.":[117]},"counts_by_year":[{"year":2012,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}