{"id":"https://openalex.org/W2801120851","doi":"https://doi.org/10.1109/icassp.2018.8461946","title":"GM-PHD Filter Based Online Multiple Human Tracking Using Deep Discriminative Correlation Matching","display_name":"GM-PHD Filter Based Online Multiple Human Tracking Using Deep Discriminative Correlation Matching","publication_year":2018,"publication_date":"2018-04-01","ids":{"openalex":"https://openalex.org/W2801120851","doi":"https://doi.org/10.1109/icassp.2018.8461946","mag":"2801120851"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2018.8461946","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2018.8461946","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5012939991","display_name":"Zeyu Fu","orcid":"https://orcid.org/0000-0002-2076-7597"},"institutions":[{"id":"https://openalex.org/I84884186","display_name":"Newcastle University","ror":"https://ror.org/01kj2bm70","country_code":"GB","type":"education","lineage":["https://openalex.org/I84884186"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Zeyu Fu","raw_affiliation_strings":["Intelligent Sensing and Communications Research Group, Newcastle University, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Sensing and Communications Research Group, Newcastle University, UK","institution_ids":["https://openalex.org/I84884186"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061082888","display_name":"Federico Angelini","orcid":"https://orcid.org/0000-0001-8333-656X"},"institutions":[{"id":"https://openalex.org/I84884186","display_name":"Newcastle University","ror":"https://ror.org/01kj2bm70","country_code":"GB","type":"education","lineage":["https://openalex.org/I84884186"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Federico Angelini","raw_affiliation_strings":["Intelligent Sensing and Communications Research Group, Newcastle University, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Sensing and Communications Research Group, Newcastle University, UK","institution_ids":["https://openalex.org/I84884186"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053121936","display_name":"Syed Mohsen Naqvi","orcid":"https://orcid.org/0000-0002-1547-0908"},"institutions":[{"id":"https://openalex.org/I84884186","display_name":"Newcastle University","ror":"https://ror.org/01kj2bm70","country_code":"GB","type":"education","lineage":["https://openalex.org/I84884186"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Syed Mohsen Naqvi","raw_affiliation_strings":["Intelligent Sensing and Communications Research Group, Newcastle University, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Sensing and Communications Research Group, Newcastle University, UK","institution_ids":["https://openalex.org/I84884186"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083892296","display_name":"Jonathon A. Chambers","orcid":"https://orcid.org/0000-0002-5820-6509"},"institutions":[{"id":"https://openalex.org/I84884186","display_name":"Newcastle University","ror":"https://ror.org/01kj2bm70","country_code":"GB","type":"education","lineage":["https://openalex.org/I84884186"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Jonathon A. Chambers","raw_affiliation_strings":["Intelligent Sensing and Communications Research Group, Newcastle University, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intelligent Sensing and Communications Research Group, Newcastle University, UK","institution_ids":["https://openalex.org/I84884186"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I84884186"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4299","last_page":"4303"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9908000230789185,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.9843999743461609,"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/discriminative-model","display_name":"Discriminative model","score":0.9077165722846985},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7474390268325806},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7329334020614624},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6861823797225952},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6657710075378418},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6196717619895935},{"id":"https://openalex.org/keywords/correlation","display_name":"Correlation","score":0.5281534194946289},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.513683021068573},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5069789886474609},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.4823410212993622},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.4283669590950012},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4148474633693695},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23635181784629822},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.10654506087303162}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.9077165722846985},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7474390268325806},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7329334020614624},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6861823797225952},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6657710075378418},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6196717619895935},{"id":"https://openalex.org/C117220453","wikidata":"https://www.wikidata.org/wiki/Q5172842","display_name":"Correlation","level":2,"score":0.5281534194946289},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.513683021068573},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5069789886474609},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.4823410212993622},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.4283669590950012},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4148474633693695},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23635181784629822},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.10654506087303162},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/icassp.2018.8461946","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2018.8461946","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7799999713897705,"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W2014787937","https://openalex.org/W2016135469","https://openalex.org/W2087003958","https://openalex.org/W2124781496","https://openalex.org/W2137585588","https://openalex.org/W2163605009","https://openalex.org/W2167536584","https://openalex.org/W2214352687","https://openalex.org/W2222512263","https://openalex.org/W2226404513","https://openalex.org/W2244956674","https://openalex.org/W2291627510","https://openalex.org/W2406082581","https://openalex.org/W2468912036","https://openalex.org/W2507495164","https://openalex.org/W2520433280","https://openalex.org/W2603203130","https://openalex.org/W2604583387","https://openalex.org/W2739374836","https://openalex.org/W2758721842","https://openalex.org/W2765741142","https://openalex.org/W2766984662","https://openalex.org/W2780882127","https://openalex.org/W2794143688","https://openalex.org/W6684191040","https://openalex.org/W6713598112","https://openalex.org/W6725491545","https://openalex.org/W6726951882","https://openalex.org/W6741923308","https://openalex.org/W6745462756","https://openalex.org/W6745633015","https://openalex.org/W6747295166"],"related_works":["https://openalex.org/W2468279273","https://openalex.org/W2965546495","https://openalex.org/W2354198838","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W1989130879","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W1487808658"],"abstract_inverted_index":{"In":[0,23],"this":[1,24],"paper,":[2],"we":[3,27,87],"propose":[4],"deep":[5],"discriminative":[6],"correlation":[7,99],"matching":[8,25,100],"within":[9],"the":[10,30,46,58,63,66,75,95,105,112,118],"Gaussian":[11],"Mixture":[12],"Probability":[13],"Hypothesis":[14],"Density":[15],"(GM-PHD)":[16],"filter":[17],"for":[18],"online":[19],"multiple":[20],"human":[21],"tracking.":[22],"scheme,":[26],"mainly":[28],"exploit":[29],"Convolutional":[31],"Neural":[32],"Network":[33],"(CNN)":[34],"based":[35],"Discriminative":[36],"Correlation":[37],"Filter":[38],"(DCF)":[39],"as":[40,125],"a":[41,89],"target-specific":[42],"classifier":[43],"to":[44,73,83,102],"discriminate":[45],"desired":[47],"target":[48,76],"from":[49,62],"background":[50],"and":[51,81,98],"remaining":[52],"targets.":[53],"DCFs":[54],"are":[55,71],"learned":[56],"through":[57],"extracted":[59],"features":[60],"obtained":[61],"outputs":[64],"of":[65,121],"last":[67],"convolutional":[68],"layers":[69],"which":[70],"capable":[72],"encode":[74],"appearances":[77],"with":[78,127],"better":[79],"discriminativity":[80],"robustness":[82],"appearance":[84],"changes.":[85],"Moreover,":[86],"present":[88],"hybrid":[90],"likelihood":[91],"function":[92],"that":[93],"fuses":[94],"spatio-temporal":[96],"relation":[97],"score":[101],"collaboratively":[103],"enhance":[104],"PHD":[106],"association":[107],"step.":[108],"Experimental":[109],"results":[110],"on":[111],"MOT17":[113],"Challenge":[114],"benchmark":[115],"[1]":[116],"confirm":[117],"improved":[119],"performance":[120],"our":[122],"proposed":[123],"method":[124],"compared":[126],"other":[128],"state-of-the-art":[129],"techniques.":[130]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":5},{"year":2018,"cited_by_count":2}],"updated_date":"2026-07-15T18:14:33.161393","created_date":"2025-10-10T00:00:00"}