{"id":"https://openalex.org/W4402595220","doi":"https://doi.org/10.1109/avss61716.2024.10672577","title":"Noise-robust person re-identification through nearest-neighbor sample filtering","display_name":"Noise-robust person re-identification through nearest-neighbor sample filtering","publication_year":2024,"publication_date":"2024-07-15","ids":{"openalex":"https://openalex.org/W4402595220","doi":"https://doi.org/10.1109/avss61716.2024.10672577"},"language":"en","primary_location":{"id":"doi:10.1109/avss61716.2024.10672577","is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss61716.2024.10672577","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)","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/A5019538628","display_name":"George Galanakis","orcid":"https://orcid.org/0000-0002-6261-6252"},"institutions":[{"id":"https://openalex.org/I142617266","display_name":"University of Crete","ror":"https://ror.org/00dr28g20","country_code":"GR","type":"education","lineage":["https://openalex.org/I142617266"]}],"countries":["GR"],"is_corresponding":true,"raw_author_name":"George Galanakis","raw_affiliation_strings":["University of Crete,Computer Science Department,Greece"],"affiliations":[{"raw_affiliation_string":"University of Crete,Computer Science Department,Greece","institution_ids":["https://openalex.org/I142617266"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089987396","display_name":"Xenophon Zabulis","orcid":"https://orcid.org/0000-0002-1520-4327"},"institutions":[{"id":"https://openalex.org/I4210121775","display_name":"FORTH Institute of Computer Science","ror":"https://ror.org/02tf48g55","country_code":"GR","type":"facility","lineage":["https://openalex.org/I4210121775","https://openalex.org/I8901234"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Xenophon Zabulis","raw_affiliation_strings":["Institute of Computer Science, FORTH,Greece"],"affiliations":[{"raw_affiliation_string":"Institute of Computer Science, FORTH,Greece","institution_ids":["https://openalex.org/I4210121775"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5023467254","display_name":"Antonis Argyros","orcid":"https://orcid.org/0000-0001-8230-3192"},"institutions":[{"id":"https://openalex.org/I142617266","display_name":"University of Crete","ror":"https://ror.org/00dr28g20","country_code":"GR","type":"education","lineage":["https://openalex.org/I142617266"]}],"countries":["GR"],"is_corresponding":false,"raw_author_name":"Antonis A. Argyros","raw_affiliation_strings":["University of Crete,Computer Science Department,Greece"],"affiliations":[{"raw_affiliation_string":"University of Crete,Computer Science Department,Greece","institution_ids":["https://openalex.org/I142617266"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5019538628"],"corresponding_institution_ids":["https://openalex.org/I142617266"],"apc_list":null,"apc_paid":null,"fwci":0.52,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.65755849,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":95,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9929999709129333,"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":0.9929999709129333,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9889000058174133,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/T11448","display_name":"Face recognition and analysis","score":0.9578999876976013,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.6754004955291748},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6182273030281067},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5817391872406006},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.48319780826568604},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4718090295791626},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4506049156188965},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.4475013315677643},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.32810357213020325},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.08921602368354797}],"concepts":[{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.6754004955291748},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6182273030281067},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5817391872406006},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.48319780826568604},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4718090295791626},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4506049156188965},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.4475013315677643},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32810357213020325},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.08921602368354797},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/avss61716.2024.10672577","is_oa":false,"landing_page_url":"https://doi.org/10.1109/avss61716.2024.10672577","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Advanced Video and Signal Based Surveillance (AVSS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334322","display_name":"HORIZON EUROPE Framework Programme","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W2204750386","https://openalex.org/W2584637367","https://openalex.org/W2585635281","https://openalex.org/W2946574625","https://openalex.org/W2978968642","https://openalex.org/W2991234496","https://openalex.org/W2998702515","https://openalex.org/W3003755145","https://openalex.org/W3109225549","https://openalex.org/W3138516171","https://openalex.org/W3173874704","https://openalex.org/W3175272368","https://openalex.org/W3175445198","https://openalex.org/W3175847745","https://openalex.org/W3184115764","https://openalex.org/W4200316912","https://openalex.org/W4212867385","https://openalex.org/W4312337588","https://openalex.org/W4319299883","https://openalex.org/W4319299941","https://openalex.org/W4382460786","https://openalex.org/W4386076618","https://openalex.org/W4391467966","https://openalex.org/W4392402482","https://openalex.org/W6735531217","https://openalex.org/W6751420435","https://openalex.org/W6751647823","https://openalex.org/W6758632346","https://openalex.org/W6772136174","https://openalex.org/W6782340949","https://openalex.org/W6785486228","https://openalex.org/W6787405277","https://openalex.org/W6789476682","https://openalex.org/W6846267422","https://openalex.org/W6855522637"],"related_works":["https://openalex.org/W2898732673","https://openalex.org/W2410053581","https://openalex.org/W2383658677","https://openalex.org/W3123203398","https://openalex.org/W2785302227","https://openalex.org/W1185300216","https://openalex.org/W1972473893","https://openalex.org/W2466435674","https://openalex.org/W2765200542","https://openalex.org/W2954163146"],"abstract_inverted_index":{"Person":[0],"re-identification":[1,112],"is":[2,106,117],"an":[3,41],"important":[4],"component":[5],"of":[6,12,31,45,96,122],"vision-based":[7],"surveillance":[8],"systems.":[9],"The":[10,78],"robustness":[11],"these":[13],"components":[14],"depends":[15],"heavily":[16],"on":[17,67,71,83,91],"mechanisms":[18],"that":[19,43,82,105],"safeguard":[20],"them":[21,56,59],"from":[22,60],"noisy":[23,51],"observations":[24,52],"which":[25],"may":[26],"affect":[27],"negatively":[28],"the":[29,32,46,94,97,110,120,123],"quality":[30],"required":[33],"training":[34],"data.":[35],"In":[36,129],"this":[37],"work":[38],"we":[39],"present":[40],"approach":[42,66,89,133],"capitalizes":[44],"KNN":[47],"algorithm":[48],"for":[49],"identifying":[50],"and":[53,70,75],"either":[54],"relabeling":[55],"or":[57],"excluding":[58],"further":[61],"consideration.":[62],"We":[63],"evaluate":[64],"our":[65,88,115,132],"standard":[68],"datasets":[69],"various":[72],"noise":[73,86,103],"types":[74],"contamination":[76],"levels.":[77],"performed":[79],"experiments":[80],"demonstrate":[81],"two":[84],"classical":[85],"types,":[87],"performs":[90],"par":[92],"to":[93,119],"state":[95,121],"art.":[98],"However,":[99],"in":[100,109,135],"a":[101,126],"third":[102],"type":[104],"especially":[107],"common":[108],"person":[111],"use":[113],"cases,":[114,131],"method":[116],"superior":[118],"art":[124],"by":[125],"great":[127],"margin.":[128],"all":[130],"results":[134],"considerable":[136],"computational":[137],"savings.":[138]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}