{"id":"https://openalex.org/W4405867970","doi":"https://doi.org/10.1145/3696409.3700168","title":"Moving Object Tracking based on Kernel and Random-coupled Neural Network","display_name":"Moving Object Tracking based on Kernel and Random-coupled Neural Network","publication_year":2024,"publication_date":"2024-12-03","ids":{"openalex":"https://openalex.org/W4405867970","doi":"https://doi.org/10.1145/3696409.3700168"},"language":"en","primary_location":{"id":"doi:10.1145/3696409.3700168","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3696409.3700168","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th ACM International Conference on Multimedia in Asia","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/A5011784152","display_name":"Yonglin Chen","orcid":"https://orcid.org/0009-0008-7419-4481"},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yiran Chen","raw_affiliation_strings":["Chengdu University of Technology, Chengdu, CN"],"affiliations":[{"raw_affiliation_string":"Chengdu University of Technology, Chengdu, CN","institution_ids":["https://openalex.org/I31595395"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100449229","display_name":"Haoran Liu","orcid":"https://orcid.org/0000-0003-0729-4526"},"institutions":[{"id":"https://openalex.org/I146620803","display_name":"Wenzhou University","ror":"https://ror.org/020hxh324","country_code":"CN","type":"education","lineage":["https://openalex.org/I146620803"]},{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoran Liu","raw_affiliation_strings":["Chengdu University of Technology, Chengdu, CN","Wenzhou University of Technology, Chengdu, China"],"affiliations":[{"raw_affiliation_string":"Chengdu University of Technology, Chengdu, CN","institution_ids":["https://openalex.org/I31595395"]},{"raw_affiliation_string":"Wenzhou University of Technology, Chengdu, China","institution_ids":["https://openalex.org/I146620803"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100674094","display_name":"Mingzhe Liu","orcid":"https://orcid.org/0000-0001-7054-997X"},"institutions":[{"id":"https://openalex.org/I146620803","display_name":"Wenzhou University","ror":"https://ror.org/020hxh324","country_code":"CN","type":"education","lineage":["https://openalex.org/I146620803"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingzhe Liu","raw_affiliation_strings":["Wenzhou University of Technology, Wenzhou, CN"],"affiliations":[{"raw_affiliation_string":"Wenzhou University of Technology, Wenzhou, CN","institution_ids":["https://openalex.org/I146620803"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100317726","display_name":"Yanhua Liu","orcid":"https://orcid.org/0000-0003-4667-2083"},"institutions":[{"id":"https://openalex.org/I31595395","display_name":"Chengdu University of Technology","ror":"https://ror.org/05pejbw21","country_code":"CN","type":"education","lineage":["https://openalex.org/I31595395"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanhua Liu","raw_affiliation_strings":["Chengdu University of Technology, Chengdu, CN"],"affiliations":[{"raw_affiliation_string":"Chengdu University of Technology, Chengdu, CN","institution_ids":["https://openalex.org/I31595395"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022594144","display_name":"Ruili Wang","orcid":"https://orcid.org/0000-0003-2899-9816"},"institutions":[{"id":"https://openalex.org/I51158804","display_name":"Massey University","ror":"https://ror.org/052czxv31","country_code":"NZ","type":"education","lineage":["https://openalex.org/I51158804"]}],"countries":["NZ"],"is_corresponding":false,"raw_author_name":"Ruili Wang","raw_affiliation_strings":["Massey University, Palmerston North, NZ"],"affiliations":[{"raw_affiliation_string":"Massey University, Palmerston North, NZ","institution_ids":["https://openalex.org/I51158804"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007295699","display_name":"Peng Li","orcid":"https://orcid.org/0000-0001-7424-6618"},"institutions":[{"id":"https://openalex.org/I4210165845","display_name":"Southwestern Institute of Physics","ror":"https://ror.org/05vrdx898","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210165845"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Li","raw_affiliation_strings":["Southwestern Institute of Physics, Chengdu, CN"],"affiliations":[{"raw_affiliation_string":"Southwestern Institute of Physics, Chengdu, CN","institution_ids":["https://openalex.org/I4210165845"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5011784152"],"corresponding_institution_ids":["https://openalex.org/I31595395"],"apc_list":null,"apc_paid":null,"fwci":0.4986,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.67699007,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9901000261306763,"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"}},{"id":"https://openalex.org/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.9865999817848206,"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/computer-science","display_name":"Computer science","score":0.7207342386245728},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6565464735031128},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6472355127334595},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.6085752248764038},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5674738883972168},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5194103717803955},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.49168115854263306},{"id":"https://openalex.org/keywords/video-tracking","display_name":"Video tracking","score":0.4386468827724457},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34928733110427856},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1297963559627533}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7207342386245728},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6565464735031128},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6472355127334595},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.6085752248764038},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5674738883972168},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5194103717803955},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.49168115854263306},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.4386468827724457},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34928733110427856},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1297963559627533},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3696409.3700168","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3696409.3700168","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 6th ACM International Conference on Multimedia in Asia","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":46,"referenced_works":["https://openalex.org/W1988689205","https://openalex.org/W2024657922","https://openalex.org/W2032843526","https://openalex.org/W2067191022","https://openalex.org/W2132103241","https://openalex.org/W2139047213","https://openalex.org/W2139292592","https://openalex.org/W2150000644","https://openalex.org/W2603203130","https://openalex.org/W2950703532","https://openalex.org/W3009115175","https://openalex.org/W3016499729","https://openalex.org/W3023256365","https://openalex.org/W3098744844","https://openalex.org/W3123357455","https://openalex.org/W3142772534","https://openalex.org/W3145360097","https://openalex.org/W3200100517","https://openalex.org/W4220869748","https://openalex.org/W4236965008","https://openalex.org/W4249502209","https://openalex.org/W4255760437","https://openalex.org/W4281757902","https://openalex.org/W4296549969","https://openalex.org/W4298205916","https://openalex.org/W4304585001","https://openalex.org/W4309488443","https://openalex.org/W4324290686","https://openalex.org/W4360616069","https://openalex.org/W4362496618","https://openalex.org/W4362500576","https://openalex.org/W4366735407","https://openalex.org/W4367665672","https://openalex.org/W4376869165","https://openalex.org/W4379117336","https://openalex.org/W4383109197","https://openalex.org/W4386065453","https://openalex.org/W4386075542","https://openalex.org/W4386776471","https://openalex.org/W4387334093","https://openalex.org/W4388624454","https://openalex.org/W4388823657","https://openalex.org/W4403939985","https://openalex.org/W6650574990","https://openalex.org/W6673240527","https://openalex.org/W6678037562"],"related_works":["https://openalex.org/W2084086966","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":{"Moving":[0],"object":[1,109,181],"tracking":[2,20,42,53,110,182],"on":[3,68],"cost-effective":[4],"hardware":[5],"is":[6,193],"a":[7,63,72],"crucial":[8],"need":[9],"in":[10,50,120,133],"numerous":[11],"research":[12],"and":[13,122,131,136,143,161,169,187],"industrial":[14],"applications.":[15],"However,":[16],"current":[17],"deep":[18,91],"learning-based":[19],"algorithms":[21],"usually":[22],"prioritize":[23],"exceptional":[24],"performance":[25,104,157],"at":[26,195],"the":[27,35,129,134,150],"expense":[28],"of":[29,37,125,152,167],"increased":[30],"computational":[31,57,170],"load.":[32],"Due":[33],"to":[34,106,128,179],"unavailability":[36],"expensive":[38],"GPUs":[39],"for":[40,177],"many":[41],"tasks,":[43],"these":[44],"popular":[45],"trackers":[46],"often":[47],"fall":[48],"short":[49],"providing":[51],"robust":[52],"capabilities":[54],"with":[55],"affordable":[56],"resources.":[58],"This":[59,76],"study":[60],"introduces":[61],"RCNNshift,":[62,153],"kernel-based":[64,108,160],"tracker":[65],"that":[66],"relies":[67],"feature":[69,99,116],"extraction":[70],"from":[71],"random-coupled":[73],"neural":[74,80,92],"network.":[75],"visual":[77],"cortex":[78],"inspired":[79],"model":[81],"can":[82],"extract":[83],"image":[84],"features":[85],"without":[86],"requiring":[87],"cumbersome":[88],"pre-training":[89],"or":[90],"connections.":[93],"By":[94],"utilizing":[95],"an":[96,174],"enhanced":[97],"one-dimensional":[98],"representation,":[100],"RCNNshift":[101,173],"demonstrates":[102],"superior":[103,156],"compared":[105,127],"other":[107],"methods,":[111],"even":[112],"those":[113],"employing":[114],"higher-dimensional":[115],"spaces.":[117],"Its":[118,165],"improvement":[119],"precision":[121],"success":[123],"plots":[124],"OPE,":[126],"Meanshift":[130],"Camshift":[132],"HSV":[135],"RGB":[137],"color":[138],"spaces,":[139],"exceeds":[140],"over":[141,158],"160%":[142],"190%":[144],"respectively.":[145],"Comparative":[146],"experiments":[147],"have":[148],"validated":[149],"robustness":[151,168],"showcasing":[154],"its":[155],"various":[159],"particle":[162],"filter":[163],"trackers.":[164],"combination":[166],"efficiency":[171],"makes":[172],"ideal":[175],"choice":[176],"mid":[178],"low-end":[180],"tasks":[183],"such":[184],"as":[185],"surveillance":[186],"underwater":[188],"tracking.":[189],"The":[190],"source":[191],"code":[192],"available":[194],"https://github.com/HaoranLiu507/RCNNshift.":[196]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}