{"id":"https://openalex.org/W2769486965","doi":"https://doi.org/10.1109/tgrs.2018.2856370","title":"Tracking in Aerial Hyperspectral Videos Using Deep Kernelized Correlation Filters","display_name":"Tracking in Aerial Hyperspectral Videos Using Deep Kernelized Correlation Filters","publication_year":2018,"publication_date":"2018-08-14","ids":{"openalex":"https://openalex.org/W2769486965","doi":"https://doi.org/10.1109/tgrs.2018.2856370","mag":"2769486965"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2018.2856370","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2018.2856370","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1711.07235","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023591008","display_name":"Burak Uzkent","orcid":"https://orcid.org/0000-0002-0584-5630"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Burak Uzkent","raw_affiliation_strings":["Computer Science Department, Stanford University, Stanford, CA, USA","Computer Science Department, Stanford University, Stanford, CA, USA#TAB#"],"raw_orcid":"https://orcid.org/0000-0002-0584-5630","affiliations":[{"raw_affiliation_string":"Computer Science Department, Stanford University, Stanford, CA, USA","institution_ids":["https://openalex.org/I97018004"]},{"raw_affiliation_string":"Computer Science Department, Stanford University, Stanford, CA, USA#TAB#","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080330227","display_name":"Aneesh Rangnekar","orcid":"https://orcid.org/0000-0002-0079-9495"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Aneesh Rangnekar","raw_affiliation_strings":["Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY, USA","Chester F Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY, USA"],"raw_orcid":"https://orcid.org/0000-0002-0079-9495","affiliations":[{"raw_affiliation_string":"Chester F. Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY, USA","institution_ids":["https://openalex.org/I155173764"]},{"raw_affiliation_string":"Chester F Carlson Center for Imaging Science, Rochester Institute of Technology, Rochester, NY, USA","institution_ids":["https://openalex.org/I155173764"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038859737","display_name":"Matthew J. Hoffman","orcid":"https://orcid.org/0000-0002-9430-005X"},"institutions":[{"id":"https://openalex.org/I155173764","display_name":"Rochester Institute of Technology","ror":"https://ror.org/00v4yb702","country_code":"US","type":"education","lineage":["https://openalex.org/I155173764"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Matthew J. Hoffman","raw_affiliation_strings":["School of Mathematical Sciences, Rochester Institute of Technology, Rochester, NY, USA","School of Mathematical Sciences, Rochester Institute of Technology; Rochester, NY; USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematical Sciences, Rochester Institute of Technology, Rochester, NY, USA","institution_ids":["https://openalex.org/I155173764"]},{"raw_affiliation_string":"School of Mathematical Sciences, Rochester Institute of Technology; Rochester, NY; USA","institution_ids":["https://openalex.org/I155173764"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":2645,"currency":"USD","value_usd":2645},"apc_paid":null,"fwci":0.3863,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.62380613,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":95},"biblio":{"volume":"57","issue":"1","first_page":"449","last_page":"461"},"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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9962999820709229,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/T12389","display_name":"Infrared Target Detection Methodologies","score":0.9958000183105469,"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/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8315472602844238},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7681363821029663},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7406681776046753},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5900430679321289},{"id":"https://openalex.org/keywords/bittorrent-tracker","display_name":"BitTorrent tracker","score":0.5201540589332581},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.49369820952415466},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.45614808797836304},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4423537254333496},{"id":"https://openalex.org/keywords/aerial-image","display_name":"Aerial image","score":0.4382709562778473},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3909544348716736},{"id":"https://openalex.org/keywords/eye-tracking","display_name":"Eye tracking","score":0.26601916551589966},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1526505947113037}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8315472602844238},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7681363821029663},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7406681776046753},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5900430679321289},{"id":"https://openalex.org/C57501372","wikidata":"https://www.wikidata.org/wiki/Q2021268","display_name":"BitTorrent tracker","level":3,"score":0.5201540589332581},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.49369820952415466},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.45614808797836304},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4423537254333496},{"id":"https://openalex.org/C2776429412","wikidata":"https://www.wikidata.org/wiki/Q4688011","display_name":"Aerial image","level":3,"score":0.4382709562778473},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3909544348716736},{"id":"https://openalex.org/C56461940","wikidata":"https://www.wikidata.org/wiki/Q970687","display_name":"Eye tracking","level":2,"score":0.26601916551589966},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1526505947113037},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","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}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/tgrs.2018.2856370","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2018.2856370","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Geoscience and Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:1711.07235","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1711.07235","pdf_url":"https://arxiv.org/pdf/1711.07235","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:2769486965","is_oa":true,"landing_page_url":"https://arxiv.org/pdf/1711.07235v3","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.1711.07235","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.1711.07235","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1711.07235","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1711.07235","pdf_url":"https://arxiv.org/pdf/1711.07235","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6967217344","display_name":null,"funder_award_id":"FA9550-11-1-0348","funder_id":"https://openalex.org/F4320338279","funder_display_name":"Air Force Office of Scientific Research"}],"funders":[{"id":"https://openalex.org/F4320338279","display_name":"Air Force Office of Scientific Research","ror":"https://ror.org/011e9bt93"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2769486965.pdf","grobid_xml":"https://content.openalex.org/works/W2769486965.grobid-xml"},"referenced_works_count":62,"referenced_works":["https://openalex.org/W161114242","https://openalex.org/W818325216","https://openalex.org/W1536680647","https://openalex.org/W1686810756","https://openalex.org/W1887170341","https://openalex.org/W1955514522","https://openalex.org/W1964846093","https://openalex.org/W1981908713","https://openalex.org/W1985943594","https://openalex.org/W2042518080","https://openalex.org/W2066757459","https://openalex.org/W2085261163","https://openalex.org/W2097117768","https://openalex.org/W2104904551","https://openalex.org/W2117343777","https://openalex.org/W2117539524","https://openalex.org/W2124211486","https://openalex.org/W2149077040","https://openalex.org/W2149829493","https://openalex.org/W2151103935","https://openalex.org/W2154889144","https://openalex.org/W2161969291","https://openalex.org/W2167724537","https://openalex.org/W2168356304","https://openalex.org/W2183598498","https://openalex.org/W2211807644","https://openalex.org/W2232829127","https://openalex.org/W2233847161","https://openalex.org/W2244956674","https://openalex.org/W2312470762","https://openalex.org/W2340000481","https://openalex.org/W2343187456","https://openalex.org/W2399469309","https://openalex.org/W2404399450","https://openalex.org/W2407895138","https://openalex.org/W2464535830","https://openalex.org/W2470394683","https://openalex.org/W2515001938","https://openalex.org/W2518876086","https://openalex.org/W2611822628","https://openalex.org/W2735640930","https://openalex.org/W2760340275","https://openalex.org/W2767007666","https://openalex.org/W2949832468","https://openalex.org/W2950094539","https://openalex.org/W2950779027","https://openalex.org/W2951433694","https://openalex.org/W2951548327","https://openalex.org/W2963113244","https://openalex.org/W2963660590","https://openalex.org/W2963840672","https://openalex.org/W2964015640","https://openalex.org/W4243493583","https://openalex.org/W6606595081","https://openalex.org/W6620707391","https://openalex.org/W6623108133","https://openalex.org/W6639390930","https://openalex.org/W6684191040","https://openalex.org/W6703518758","https://openalex.org/W6714138976","https://openalex.org/W6726654379","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2995461960","https://openalex.org/W3097590716","https://openalex.org/W3120898603","https://openalex.org/W1989050655","https://openalex.org/W2104149642","https://openalex.org/W2197185634","https://openalex.org/W2977199512","https://openalex.org/W3020786642","https://openalex.org/W2037706453","https://openalex.org/W3097151791","https://openalex.org/W3030372272","https://openalex.org/W2153563596","https://openalex.org/W588311603","https://openalex.org/W3077479015","https://openalex.org/W2809426059","https://openalex.org/W3095012029","https://openalex.org/W3039821217","https://openalex.org/W3036152936","https://openalex.org/W2896070335","https://openalex.org/W2291068538"],"abstract_inverted_index":{"Hyperspectral":[0],"imaging":[1,164],"holds":[2],"enormous":[3],"potential":[4],"to":[5,32,35,65,80,104,135,184,216],"improve":[6],"the":[7,10,69,74,112,138,162,189,197,201,225],"state":[8],"of":[9,114,200],"art":[11],"in":[12,68,155,188,224],"aerial":[13,41,66,83,209],"vehicle":[14,186,210,220],"tracking":[15,67,223],"with":[16,137,150],"low":[17,93],"spatial":[18],"and":[19,59,165,206,222],"temporal":[20,94],"resolutions.":[21],"Recently,":[22],"adaptive":[23,87],"multimodal":[24,88],"hyperspectral":[25,70,76,89,158],"sensors":[26],"have":[27],"attracted":[28],"growing":[29],"interest":[30],"due":[31],"their":[33],"ability":[34],"record":[36],"extended":[37],"data":[38,180,212],"quickly":[39],"from":[40,50,119],"platforms.":[42],"In":[43,172],"this":[44],"paper,":[45],"we":[46,122,174],"apply":[47],"popular":[48],"concepts":[49],"traditional":[51],"object":[52],"tracking,":[53],"namely,":[54],"kernelized":[55],"correlation":[56,141],"filters":[57],"(KCFs)":[58],"deep":[60,75,115,151],"convolutional":[61,116],"neural":[62],"network":[63],"features":[64,117,152],"domain.":[71],"We":[72,91],"propose":[73],"KCF-based":[77],"tracker":[78,131,146],"(DeepHKCF)":[79],"efficiently":[81],"track":[82],"vehicles":[84],"using":[85,182],"an":[86,124],"sensor.":[90],"address":[92],"resolution":[95],"by":[96,161],"designing":[97],"a":[98,106,156,176,207],"single":[99],"KCF-in-multiple":[100],"regions-of-interest":[101],"(ROIs)":[102],"approach":[103],"cover":[105],"reasonably":[107],"large":[108],"area.":[109],"To":[110],"increase":[111],"speed":[113],"extraction":[118],"multiple":[120],"ROIs,":[121],"design":[123],"effective":[125],"ROI":[126],"mapping":[127],"strategy.":[128],"The":[129,144],"proposed":[130],"also":[132],"provides":[133],"flexibility":[134],"couple":[136],"more":[139],"advanced":[140],"filter":[142],"trackers.":[143],"DeepHKCF":[145],"performs":[147],"exceptionally":[148],"well":[149],"set":[153,181,213],"up":[154],"synthetic":[157],"video":[159],"generated":[160],"digital":[163],"remote":[166],"sensing":[167],"image":[168],"generation":[169],"(DIRSIG)":[170],"software.":[171],"addition,":[173],"generate":[175],"large,":[177],"synthetic,":[178],"single-channel":[179],"DIRSIG":[183,202],"perform":[185],"classification":[187,211],"wide-area":[190],"motion":[191],"imagery":[192],"(WAMI)":[193],"platform.":[194,227],"This":[195],"way,":[196],"high":[198],"fidelity":[199],"software":[203],"is":[204,214],"proven,":[205],"large-scale":[208],"released":[215],"support":[217],"studies":[218],"on":[219],"detection":[221],"WAMI":[226]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-08-26T07:47:46.906454","created_date":"2022-09-21T00:00:00"}