{"id":"https://openalex.org/W2908440540","doi":"https://doi.org/10.1109/access.2018.2890664","title":"Optimizing Multi-Granularity Region Similarity for Person Re-Identification","display_name":"Optimizing Multi-Granularity Region Similarity for Person Re-Identification","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2908440540","doi":"https://doi.org/10.1109/access.2018.2890664","mag":"2908440540"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2890664","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2890664","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08598715.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08598715.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073015477","display_name":"Cuiqun Chen","orcid":"https://orcid.org/0000-0002-4133-0028"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Cuiqun Chen","raw_affiliation_strings":["School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073550769","display_name":"Meibin Qi","orcid":"https://orcid.org/0000-0001-9074-211X"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meibin Qi","raw_affiliation_strings":["School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115666606","display_name":"Ning Yang","orcid":"https://orcid.org/0000-0002-8987-0787"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ning Yang","raw_affiliation_strings":["School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100717585","display_name":"Wei Li","orcid":"https://orcid.org/0000-0003-1390-6904"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei Li","raw_affiliation_strings":["School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002727597","display_name":"Jianguo Jiang","orcid":"https://orcid.org/0000-0002-9349-6337"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianguo Jiang","raw_affiliation_strings":["School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Information Engineering, Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5073015477"],"corresponding_institution_ids":["https://openalex.org/I16365422"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.7086,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.73832343,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"7","issue":null,"first_page":"8847","last_page":"8857"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":1.0,"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":1.0,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.995199978351593,"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":0.9909999966621399,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.8254513740539551},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7856848835945129},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.6516995429992676},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.624065101146698},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5764068961143494},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5644921660423279},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.534269392490387},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5235597491264343},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.49823617935180664},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.49528732895851135},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.48270320892333984},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.43268200755119324},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2854583263397217},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.2138403356075287},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1074134111404419}],"concepts":[{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.8254513740539551},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7856848835945129},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.6516995429992676},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.624065101146698},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5764068961143494},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5644921660423279},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.534269392490387},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5235597491264343},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.49823617935180664},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.49528732895851135},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.48270320892333984},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.43268200755119324},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2854583263397217},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2138403356075287},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1074134111404419},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","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},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2890664","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2890664","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08598715.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:e7a30b9a5de7417cb7559bb03db74778","is_oa":true,"landing_page_url":"https://doaj.org/article/e7a30b9a5de7417cb7559bb03db74778","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 8847-8857 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2890664","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2890664","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08598715.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6299999952316284,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G2619284878","display_name":null,"funder_award_id":"61876056","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6064834736","display_name":null,"funder_award_id":"61771180","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2908440540.pdf","grobid_xml":"https://content.openalex.org/works/W2908440540.grobid-xml"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W46454230","https://openalex.org/W71666767","https://openalex.org/W140822990","https://openalex.org/W1518138188","https://openalex.org/W1602182271","https://openalex.org/W1927348918","https://openalex.org/W1928419358","https://openalex.org/W1949591461","https://openalex.org/W1962025484","https://openalex.org/W1979260620","https://openalex.org/W1979838576","https://openalex.org/W1982925187","https://openalex.org/W2014764728","https://openalex.org/W2046835352","https://openalex.org/W2047632871","https://openalex.org/W2062677035","https://openalex.org/W2068042582","https://openalex.org/W2079023123","https://openalex.org/W2079972027","https://openalex.org/W2126791727","https://openalex.org/W2151873133","https://openalex.org/W2220271458","https://openalex.org/W2300840837","https://openalex.org/W2316109659","https://openalex.org/W2342611082","https://openalex.org/W2361187101","https://openalex.org/W2433217581","https://openalex.org/W2467139031","https://openalex.org/W2471048925","https://openalex.org/W2475284720","https://openalex.org/W2483081449","https://openalex.org/W2497344197","https://openalex.org/W2598136829","https://openalex.org/W2604211872","https://openalex.org/W2615877184","https://openalex.org/W2724213014","https://openalex.org/W2736410039","https://openalex.org/W2745337109","https://openalex.org/W2752903123","https://openalex.org/W2755066373","https://openalex.org/W2769346661","https://openalex.org/W2770076563","https://openalex.org/W2963438548","https://openalex.org/W2963854696","https://openalex.org/W3102668440","https://openalex.org/W6602873311","https://openalex.org/W6636160605","https://openalex.org/W6662292890","https://openalex.org/W6682521945","https://openalex.org/W6718067072","https://openalex.org/W6730348099","https://openalex.org/W6735168867","https://openalex.org/W6995748166"],"related_works":["https://openalex.org/W2931688134","https://openalex.org/W2377919138","https://openalex.org/W2378857091","https://openalex.org/W103652678","https://openalex.org/W4226090359","https://openalex.org/W2059697060","https://openalex.org/W936373746","https://openalex.org/W2975817033","https://openalex.org/W4256502920","https://openalex.org/W4382701072"],"abstract_inverted_index":{"Person":[0],"re-identification":[1],"(re-id)":[2],"is":[3,143],"one":[4],"of":[5,52,68,109,118,123],"the":[6,41,50,53,58,66,78,96,100,105,110,114,119,125,131,136,139,146,167,173,185],"hottest":[7],"research":[8],"topics":[9],"due":[10],"to":[11,34,77],"its":[12],"great":[13],"value":[14],"in":[15,40],"video":[16],"analysis":[17],"applications,":[18],"such":[19],"as":[20,30],"indoor":[21],"security":[22],"and":[23,37,99,113,160],"road":[24],"surveillance.":[25],"It":[26],"has":[27,165],"been":[28],"verified":[29],"beneficial":[31],"for":[32],"re-id":[33],"joint":[35],"global":[36,54,106],"local":[38,115,132,140],"features":[39,51],"recent":[42],"literature.":[43],"However,":[44],"most":[45],"existing":[46],"methods":[47],"usually":[48],"extract":[49,104],"region":[55,98,112],"or":[56,75],"divide":[57],"whole":[59],"image":[60],"into":[61],"several":[62],"parts":[63,133],"without":[64],"considering":[65],"alignment":[67],"different":[69],"parts,":[70,141],"which":[71,142],"are":[72,157],"not":[73],"discriminating":[74],"robust":[76],"complex":[79],"scenarios.":[80],"In":[81],"this":[82],"paper,":[83],"we":[84,129],"propose":[85],"a":[86,179,189],"novel":[87],"method":[88,164,177],"that":[89,162],"optimizes":[90],"multi-granularity":[91],"similarity":[92,137],"fusion":[93],"based":[94],"on":[95,153,172],"coarse":[97,111],"fine":[101,120],"region.":[102,121],"We":[103],"feature":[107,116],"representations":[108,117],"Instead":[122],"using":[124],"pose":[126],"estimation":[127],"method,":[128],"align":[130],"by":[134,145,188],"calculating":[135],"between":[138],"optimized":[144],"refined":[147],"longest":[148],"path.":[149],"The":[150],"extensive":[151],"experiments":[152],"four":[154],"challenging":[155],"datasets":[156],"carried":[158],"out":[159],"indicate":[161],"our":[163,176],"achieved":[166],"state-of-the-art":[168,186],"performances.":[169],"For":[170],"instance,":[171],"VIPeR":[174],"dataset,":[175],"achieves":[178],"67.25%":[180],"rank-1":[181],"matching":[182],"rate,":[183],"outperforming":[184],"approaches":[187],"large":[190],"margin.":[191]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}