{"id":"https://openalex.org/W4366721344","doi":"https://doi.org/10.1109/iccicc57084.2022.10101537","title":"Learning Smooth Target-Aware Spatially Regularized Correlation Filters for UAV Tracking","display_name":"Learning Smooth Target-Aware Spatially Regularized Correlation Filters for UAV Tracking","publication_year":2022,"publication_date":"2022-12-08","ids":{"openalex":"https://openalex.org/W4366721344","doi":"https://doi.org/10.1109/iccicc57084.2022.10101537"},"language":"en","primary_location":{"id":"doi:10.1109/iccicc57084.2022.10101537","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iccicc57084.2022.10101537","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 21st International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","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/A5100448958","display_name":"Feng Li","orcid":"https://orcid.org/0000-0003-0469-0363"},"institutions":[{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Feng Li","raw_affiliation_strings":["Shenzhen Institute of Advanced Technology, Sangfor Technologies Inc.,Chinese Academy of Sciences,Shenzhen,China","Chinese Academy of Sciences, Shenzhen Institute of Advanced Technology, Sangfor Technologies Inc., Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Institute of Advanced Technology, Sangfor Technologies Inc.,Chinese Academy of Sciences,Shenzhen,China","institution_ids":["https://openalex.org/I4210145761"]},{"raw_affiliation_string":"Chinese Academy of Sciences, Shenzhen Institute of Advanced Technology, Sangfor Technologies Inc., Shenzhen, China","institution_ids":["https://openalex.org/I4210145761"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091556887","display_name":"Guopu Zhu","orcid":"https://orcid.org/0000-0001-7956-5343"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Guopu Zhu","raw_affiliation_strings":["School of Cyberspace Security, Harbin Institute of Technology,Harbin,China","School of Cyberspace Security, Harbin Institute of Technology, Harbin, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Cyberspace Security, Harbin Institute of Technology,Harbin,China","institution_ids":["https://openalex.org/I204983213"]},{"raw_affiliation_string":"School of Cyberspace Security, Harbin Institute of Technology, Harbin, China","institution_ids":["https://openalex.org/I204983213"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070202014","display_name":"Bozhong Liu","orcid":"https://orcid.org/0000-0003-2839-1499"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bozhong Liu","raw_affiliation_strings":["Sangfor Technologies Inc.,Shenzhen,China","Sangfor Technologies Inc., Shenzhen, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sangfor Technologies Inc.,Shenzhen,China","institution_ids":[]},{"raw_affiliation_string":"Sangfor Technologies Inc., Shenzhen, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008386708","display_name":"Sam Kwong","orcid":"https://orcid.org/0000-0001-7484-7261"},"institutions":[{"id":"https://openalex.org/I168719708","display_name":"City University of Hong Kong","ror":"https://ror.org/03q8dnn23","country_code":"HK","type":"education","lineage":["https://openalex.org/I168719708"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Sam Kwong","raw_affiliation_strings":["City University of Hong Kong,Department of Computer Science,Hong Kong,China","Department of Computer Science, City University of Hong Kong, Hong Kong, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"City University of Hong Kong,Department of Computer Science,Hong Kong,China","institution_ids":["https://openalex.org/I168719708"]},{"raw_affiliation_string":"Department of Computer Science, City University of Hong Kong, Hong Kong, China","institution_ids":["https://openalex.org/I168719708"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16897224,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"19","issue":null,"first_page":"160","last_page":"167"},"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9700000286102295,"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":0.9488999843597412,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/regularization","display_name":"Regularization (linguistics)","score":0.7050136923789978},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6149263978004456},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5985081195831299},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5560603737831116},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5450156331062317},{"id":"https://openalex.org/keywords/bittorrent-tracker","display_name":"BitTorrent tracker","score":0.5269482731819153},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.512864351272583},{"id":"https://openalex.org/keywords/spatial-filter","display_name":"Spatial filter","score":0.506705105304718},{"id":"https://openalex.org/keywords/spatial-correlation","display_name":"Spatial correlation","score":0.4981110095977783},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4859984815120697},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.41594961285591125},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34755444526672363},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3374212086200714},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.32297998666763306},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.1386619210243225}],"concepts":[{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.7050136923789978},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6149263978004456},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5985081195831299},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5560603737831116},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5450156331062317},{"id":"https://openalex.org/C57501372","wikidata":"https://www.wikidata.org/wiki/Q2021268","display_name":"BitTorrent tracker","level":3,"score":0.5269482731819153},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.512864351272583},{"id":"https://openalex.org/C121475858","wikidata":"https://www.wikidata.org/wiki/Q2735911","display_name":"Spatial filter","level":2,"score":0.506705105304718},{"id":"https://openalex.org/C150060386","wikidata":"https://www.wikidata.org/wiki/Q7574054","display_name":"Spatial correlation","level":2,"score":0.4981110095977783},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4859984815120697},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.41594961285591125},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34755444526672363},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3374212086200714},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.32297998666763306},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.1386619210243225},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iccicc57084.2022.10101537","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iccicc57084.2022.10101537","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE 21st International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2761270783","display_name":null,"funder_award_id":"62172402,61872350","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3171208677","display_name":null,"funder_award_id":"FRFCU5710011322","funder_id":"https://openalex.org/F4320335787","funder_display_name":"Fundamental Research Funds for the Central Universities"},{"id":"https://openalex.org/G4169049969","display_name":null,"funder_award_id":"2022YFB3102900","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"},{"id":"https://openalex.org/G8274296919","display_name":null,"funder_award_id":"9042816,9042958","funder_id":"https://openalex.org/F4320321019","funder_display_name":"University Grants Committee"}],"funders":[{"id":"https://openalex.org/F4320306709","display_name":"Glaucoma Research Foundation","ror":"https://ror.org/05ez53b31"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320321019","display_name":"University Grants Committee","ror":"https://ror.org/00djwmt25"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null},{"id":"https://openalex.org/F4320335787","display_name":"Fundamental Research Funds for the Central Universities","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1908905119","https://openalex.org/W1955741794","https://openalex.org/W1964846093","https://openalex.org/W2001281158","https://openalex.org/W2044986361","https://openalex.org/W2131046249","https://openalex.org/W2149829493","https://openalex.org/W2154889144","https://openalex.org/W2161969291","https://openalex.org/W2518876086","https://openalex.org/W2552808051","https://openalex.org/W2555231364","https://openalex.org/W2557641257","https://openalex.org/W2558899534","https://openalex.org/W2599547527","https://openalex.org/W2604701225","https://openalex.org/W2739789140","https://openalex.org/W2912465472","https://openalex.org/W2963074722","https://openalex.org/W2963099472","https://openalex.org/W2964069521","https://openalex.org/W2964111344","https://openalex.org/W3024883262","https://openalex.org/W3095342686","https://openalex.org/W3169294567","https://openalex.org/W6730584787"],"related_works":["https://openalex.org/W2086677144","https://openalex.org/W4312791623","https://openalex.org/W4389910871","https://openalex.org/W1988032185","https://openalex.org/W2898021863","https://openalex.org/W4320029439","https://openalex.org/W2042639947","https://openalex.org/W2521335480","https://openalex.org/W3121692546","https://openalex.org/W2611370603"],"abstract_inverted_index":{"Spatially":[0,71],"regularized":[1],"correlation":[2],"filters":[3],"(SRCF)":[4],"have":[5],"recently":[6],"received":[7],"increasing":[8],"interest":[9],"for":[10,30,77,99,118,160],"Unmanned":[11],"Aerial":[12],"Vehicle":[13],"(UAV)":[14],"tracking":[15,146],"due":[16],"to":[17],"their":[18],"promising":[19],"results.":[20],"While":[21],"the":[22,31,42,60,84,95,101,104,115,121,145,184],"choice":[23],"of":[24,33,156,192],"spatial":[25,52,87,109,122,132],"weight":[26,53,88,123,133],"matrices":[27,54,124,134],"is":[28],"vital":[29],"success":[32],"SRCF":[34],"methods,":[35],"they":[36],"are":[37,112],"generally":[38],"learned":[39,140],"only":[40,182],"with":[41],"training":[43],"samples":[44],"in":[45,50,55,90,164],"current":[46],"frame,":[47],"which":[48,165],"results":[49],"time-discontinuous":[51],"neighboring":[56],"frames,":[57],"thus":[58],"degrading":[59],"CF":[61,116,126,201],"models.":[62,127],"In":[63,128,148],"this":[64,129],"paper,":[65],"we":[66,81,150],"propose":[67],"a":[68,169],"Smooth":[69],"Target-Aware":[70],"Regularized":[72],"Correlation":[73],"Filter":[74],"(STASRCF)":[75],"framework":[76,117],"UAV":[78,175],"tracking.":[79],"Specifically,":[80],"first":[82],"obtain":[83],"initial":[85],"target-aware":[86],"matrix":[89],"each":[91,166],"frame":[92],"by":[93,187],"employing":[94],"image":[96],"segmentation":[97],"techniques":[98],"separating":[100],"target":[102],"from":[103],"background,":[105],"then":[106],"multiple":[107,174],"adaptive":[108],"regularization":[110],"terms":[111],"integrated":[113],"into":[114],"jointly":[119],"updating":[120],"and":[125,135],"way,":[130],"time-continuous":[131],"robust":[136],"CFs":[137],"can":[138,180],"be":[139],"during":[141],"tracking,":[142],"thereby":[143],"benefiting":[144],"performance.":[147],"addition,":[149],"suggest":[151],"an":[152,188],"Alternating":[153],"Direction":[154],"Method":[155],"Multipliers":[157],"(ADMM)":[158],"method":[159],"solving":[161],"STASRCF":[162,179],"efficiently,":[163],"sub-problem":[167],"has":[168],"closed-form":[170],"solution.":[171],"Experiments":[172],"on":[173],"datasets":[176],"show":[177],"that":[178],"not":[181],"surpass":[183],"baseline":[185],"CSR-DCF":[186],"average":[189],"AUC":[190],"gain":[191],"1.9%,":[193],"but":[194],"also":[195],"perform":[196],"favorably":[197],"against":[198],"other":[199],"state-of-the-art":[200],"trackers.":[202]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}