{"id":"https://openalex.org/W2885173385","doi":"https://doi.org/10.1109/ccnc.2019.8651791","title":"Kerman: A Hybrid Lightweight Tracking Algorithm to Enable Smart Surveillance as an Edge Service","display_name":"Kerman: A Hybrid Lightweight Tracking Algorithm to Enable Smart Surveillance as an Edge Service","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2885173385","doi":"https://doi.org/10.1109/ccnc.2019.8651791","mag":"2885173385"},"language":"en","primary_location":{"id":"doi:10.1109/ccnc.2019.8651791","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccnc.2019.8651791","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 16th IEEE Annual Consumer Communications &amp; Networking Conference (CCNC)","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/A5027086599","display_name":"Seyed Yahya Nikouei","orcid":"https://orcid.org/0000-0002-9672-872X"},"institutions":[{"id":"https://openalex.org/I123946342","display_name":"Binghamton University","ror":"https://ror.org/008rmbt77","country_code":"US","type":"education","lineage":["https://openalex.org/I123946342"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Seyed Yahya Nikouei","raw_affiliation_strings":["Dept. of Electrical and Computing Engineering, Binghamton University, SUNY, Binghamton, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Electrical and Computing Engineering, Binghamton University, SUNY, Binghamton, NY, USA","institution_ids":["https://openalex.org/I123946342"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100402109","display_name":"Yu Chen","orcid":"https://orcid.org/0000-0003-1880-0586"},"institutions":[{"id":"https://openalex.org/I123946342","display_name":"Binghamton University","ror":"https://ror.org/008rmbt77","country_code":"US","type":"education","lineage":["https://openalex.org/I123946342"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yu Chen","raw_affiliation_strings":["Dept. of Electrical and Computing Engineering, Binghamton University, SUNY, Binghamton, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Dept. of Electrical and Computing Engineering, Binghamton University, SUNY, Binghamton, NY, USA","institution_ids":["https://openalex.org/I123946342"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101040138","display_name":"Sejun Song","orcid":null},"institutions":[{"id":"https://openalex.org/I75421653","display_name":"University of Missouri\u2013Kansas City","ror":"https://ror.org/01w0d5g70","country_code":"US","type":"education","lineage":["https://openalex.org/I75421653"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sejun Song","raw_affiliation_strings":["School of Computing and Engineering, University of Missouri-Kansas City, Kansas City, MO, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computing and Engineering, University of Missouri-Kansas City, Kansas City, MO, USA","institution_ids":["https://openalex.org/I75421653"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078326978","display_name":"Timothy R. Faughnan","orcid":null},"institutions":[{"id":"https://openalex.org/I123946342","display_name":"Binghamton University","ror":"https://ror.org/008rmbt77","country_code":"US","type":"education","lineage":["https://openalex.org/I123946342"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Timothy R. Faughnan","raw_affiliation_strings":["New York State University Police, Binghamton University, SUNY, Binghamton, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"New York State University Police, Binghamton University, SUNY, Binghamton, NY, USA","institution_ids":["https://openalex.org/I123946342"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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/T11019","display_name":"Image Enhancement Techniques","score":0.984000027179718,"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9702000021934509,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/computer-science","display_name":"Computer science","score":0.8483561277389526},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.668786883354187},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.6070818901062012},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.6049667596817017},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.5822015404701233},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5313770174980164},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5110979676246643},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.5099636316299438},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.47375208139419556},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.39789891242980957},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3811633586883545},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3543796241283417},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3503100275993347},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.092068612575531}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8483561277389526},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.668786883354187},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.6070818901062012},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.6049667596817017},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.5822015404701233},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5313770174980164},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5110979676246643},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.5099636316299438},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.47375208139419556},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.39789891242980957},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3811633586883545},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3543796241283417},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3503100275993347},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.092068612575531}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccnc.2019.8651791","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccnc.2019.8651791","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 16th IEEE Annual Consumer Communications &amp; Networking Conference (CCNC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6399999856948853,"id":"https://metadata.un.org/sdg/8","display_name":"Decent work and economic growth"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W1833143043","https://openalex.org/W1857884451","https://openalex.org/W1892578678","https://openalex.org/W1964846093","https://openalex.org/W1966729752","https://openalex.org/W2000326692","https://openalex.org/W2007964100","https://openalex.org/W2035866593","https://openalex.org/W2076269884","https://openalex.org/W2087475313","https://openalex.org/W2116610325","https://openalex.org/W2118572719","https://openalex.org/W2127782573","https://openalex.org/W2134653274","https://openalex.org/W2140235142","https://openalex.org/W2154889144","https://openalex.org/W2158592639","https://openalex.org/W2167089254","https://openalex.org/W2189025296","https://openalex.org/W2279098554","https://openalex.org/W2328151479","https://openalex.org/W2416799949","https://openalex.org/W2512201415","https://openalex.org/W2528462506","https://openalex.org/W2560182676","https://openalex.org/W2605173812","https://openalex.org/W2612445135","https://openalex.org/W2769358479","https://openalex.org/W2790257945","https://openalex.org/W2799246510","https://openalex.org/W2901796758","https://openalex.org/W2963705844","https://openalex.org/W2964129362","https://openalex.org/W4297775537","https://openalex.org/W6737664043","https://openalex.org/W6745765596","https://openalex.org/W6746347231","https://openalex.org/W6750931767"],"related_works":["https://openalex.org/W2979760315","https://openalex.org/W4324372666","https://openalex.org/W4225706866","https://openalex.org/W4322761281","https://openalex.org/W4238233472","https://openalex.org/W4313339048","https://openalex.org/W2956163139","https://openalex.org/W4313463218","https://openalex.org/W4386004629","https://openalex.org/W2942586735"],"abstract_inverted_index":{"Edge":[0,76],"computing":[1,5,69],"pushes":[2],"the":[3,17,79,169,176],"cloud":[4],"boundaries":[6],"beyond":[7],"uncertain":[8],"network":[9],"resource":[10,186],"by":[11,51,96,189],"leveraging":[12],"computational":[13,81],"processes":[14],"close":[15],"to":[16,66,75,78,88,174],"source":[18],"and":[19,24,49,56,70,156],"target":[20],"of":[21,148,178],"data.":[22],"Time-sensitive":[23],"data-intensive":[25,71],"video":[26,41,161],"surveillance":[27,42,91,160],"applications":[28],"benefit":[29],"from":[30,73],"on-site":[31],"or":[32],"near-site":[33],"data":[34],"mining.":[35],"In":[36,83],"recent":[37],"years,":[38],"many":[39],"smart":[40],"approaches":[43],"are":[44,166],"proposed":[45,120,139],"for":[46,121,135],"object":[47,123,177],"detection":[48],"tracking":[50,101],"using":[52,158],"Artificial":[53],"Intelligence":[54],"(AI)":[55],"Machine":[57],"Learning":[58],"(ML)":[59],"algorithms.":[60],"However,":[61],"it":[62],"is":[63,109,126,172],"still":[64],"hard":[65],"migrate":[67],"those":[68],"tasks":[72],"Cloud":[74],"due":[77],"high":[80,136],"requirement.":[82],"this":[84],"paper,":[85],"we":[86],"envision":[87],"achieve":[89],"intelligent":[90],"as":[92,153],"an":[93],"edge":[94,154,190],"service":[95],"proposing":[97],"a":[98,110,129,146,181,185],"hybrid":[99,114],"lightweight":[100,130],"algorithm":[102,119,141,171],"named":[103],"Kerman":[104,108,140,170],"(Kernelized":[105],"Kalman":[106],"filter).":[107],"decision":[111],"tree":[112],"based":[113],"Kernelized":[115],"Correlation":[116],"Filter":[117],"(KCF)":[118],"human":[122],"tracking,":[124],"which":[125],"coupled":[127],"with":[128,180],"Convolutional":[131],"Neural":[132],"Network":[133],"(L-CNN)":[134],"performance.":[137],"The":[138,163],"has":[142],"been":[143],"implemented":[144],"on":[145],"couple":[147],"single":[149],"board":[150],"computers":[151],"(SBC)":[152],"devices":[155],"validated":[157],"real-world":[159],"streams.":[162],"experimental":[164],"results":[165],"promising":[167],"that":[168],"able":[173],"track":[175],"interest":[179],"decent":[182],"accuracy":[183],"at":[184],"consumption":[187],"affordable":[188],"devices.":[191]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":12},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
