{"id":"https://openalex.org/W4251325808","doi":"https://doi.org/10.1109/rcar.2017.8311907","title":"A comparison study on the adaptive scale estimation of correlation filter-based visual tracking methods","display_name":"A comparison study on the adaptive scale estimation of correlation filter-based visual tracking methods","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W4251325808","doi":"https://doi.org/10.1109/rcar.2017.8311907"},"language":"en","primary_location":{"id":"doi:10.1109/rcar.2017.8311907","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rcar.2017.8311907","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Real-time Computing and Robotics (RCAR)","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/A5067027823","display_name":"Zichun Wang","orcid":"https://orcid.org/0009-0003-1085-1474"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Z. L. Wang","raw_affiliation_strings":["Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090504502","display_name":"B. G. Cai","orcid":"https://orcid.org/0009-0002-3735-3187"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"B. G. Cai","raw_affiliation_strings":["Beijing Jiaotong University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University, Beijing, China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083827199","display_name":"Yanxia Wang","orcid":"https://orcid.org/0009-0006-1627-3259"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Y. L. Wang","raw_affiliation_strings":["CSR Qindao Sifang Co. Ltd., Qindao, China"],"affiliations":[{"raw_affiliation_string":"CSR Qindao Sifang Co. Ltd., Qindao, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024610771","display_name":"Guangzhe Lv","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"G. Y. Lv","raw_affiliation_strings":["CSR Qindao Sifang Co. Ltd., Qindao, China"],"affiliations":[{"raw_affiliation_string":"CSR Qindao Sifang Co. Ltd., Qindao, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113244847","display_name":"Rongmin Shan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"R. C. Shan","raw_affiliation_strings":["CSR Qindao Sifang Co. Ltd., Qindao, China"],"affiliations":[{"raw_affiliation_string":"CSR Qindao Sifang Co. Ltd., Qindao, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040272347","display_name":"Min-Jie Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"M. Zhang","raw_affiliation_strings":["CSR Qindao Sifang Co. Ltd., Qindao, China"],"affiliations":[{"raw_affiliation_string":"CSR Qindao Sifang Co. Ltd., Qindao, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5067027823"],"corresponding_institution_ids":["https://openalex.org/I21193070"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.32647292,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"36","issue":null,"first_page":"471","last_page":"476"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9997000098228455,"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":0.9997000098228455,"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":0.9872999787330627,"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/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.9825999736785889,"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/discriminative-model","display_name":"Discriminative model","score":0.818253219127655},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.744025707244873},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7051842212677002},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.6906802654266357},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.6441031098365784},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6018027067184448},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5951433181762695},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5417149662971497},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5404982566833496},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.4737832546234131},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40547263622283936},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.3243695795536041},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16046199202537537}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.818253219127655},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.744025707244873},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7051842212677002},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.6906802654266357},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.6441031098365784},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6018027067184448},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5951433181762695},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5417149662971497},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5404982566833496},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.4737832546234131},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40547263622283936},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.3243695795536041},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16046199202537537},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/rcar.2017.8311907","is_oa":false,"landing_page_url":"https://doi.org/10.1109/rcar.2017.8311907","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Real-time Computing and Robotics (RCAR)","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":19,"referenced_works":["https://openalex.org/W161114242","https://openalex.org/W194055484","https://openalex.org/W818325216","https://openalex.org/W1964846093","https://openalex.org/W1997121481","https://openalex.org/W2001785244","https://openalex.org/W2016075127","https://openalex.org/W2038943746","https://openalex.org/W2044986361","https://openalex.org/W2047237558","https://openalex.org/W2109579504","https://openalex.org/W2126302311","https://openalex.org/W2149829493","https://openalex.org/W2154889144","https://openalex.org/W2520438127","https://openalex.org/W2520477759","https://openalex.org/W6607940241","https://openalex.org/W6662317391","https://openalex.org/W6727158897"],"related_works":["https://openalex.org/W2012200063","https://openalex.org/W4285271403","https://openalex.org/W2542007731","https://openalex.org/W2968379562","https://openalex.org/W2091015105","https://openalex.org/W4388689193","https://openalex.org/W2110899030","https://openalex.org/W29633852","https://openalex.org/W2985362983","https://openalex.org/W4327670844"],"abstract_inverted_index":{"Recently,":[0],"discriminative":[1],"correlation":[2,60,120],"filter":[3,61],"(DCF)":[4],"based":[5,62],"visual":[6,42,63,101],"tracker":[7],"shows":[8],"the":[9,27,88,95,113,117],"advantages":[10],"of":[11,33,55,119],"being":[12],"computationally":[13],"efficient":[14],"and":[15,45,71],"excellent":[16],"performance,":[17],"which":[18],"make":[19],"them":[20],"especially":[21],"suitable":[22],"for":[23,51],"real-time":[24],"application.":[25],"On":[26],"other":[28,98],"hand,":[29],"accurate":[30],"scale":[31,57,89],"estimation":[32,58,90],"a":[34,37,48,84],"target":[35],"plays":[36],"very":[38],"important":[39],"role":[40],"in":[41,59,68,100],"object":[43],"tracking":[44,64],"is":[46],"obviously":[47],"challenging":[49],"task":[50],"tracking.":[52],"The":[53,79],"approaches":[54],"adaptive":[56],"methods":[65],"are":[66,74],"summarized":[67],"this":[69],"paper,":[70],"their":[72],"performances":[73],"analyzed":[75],"by":[76],"experimental":[77],"comparison.":[78],"works":[80],"here":[81],"can":[82,109],"provide":[83],"better":[85],"understanding":[86],"on":[87],"problem.":[91],"Furthermore,":[92],"maybe":[93],"with":[94],"same":[96],"strategy,":[97],"factors":[99],"tracking,":[102],"such":[103],"as":[104],"appearance":[105],"variation":[106],"et":[107],"al,":[108],"be":[110],"integrated":[111],"into":[112],"framework":[114],"to":[115],"improve":[116],"performance":[118],"filter-based":[121],"method.":[122]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}