{"id":"https://openalex.org/W2903020151","doi":"https://doi.org/10.1145/3282286.3282301","title":"An Improved Method for Person Re-identification","display_name":"An Improved Method for Person Re-identification","publication_year":2018,"publication_date":"2018-10-06","ids":{"openalex":"https://openalex.org/W2903020151","doi":"https://doi.org/10.1145/3282286.3282301","mag":"2903020151"},"language":"en","primary_location":{"id":"doi:10.1145/3282286.3282301","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3282286.3282301","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Conference on Graphics and Signal Processing","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/A5100731365","display_name":"Han Jiang","orcid":"https://orcid.org/0000-0003-3690-0492"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han Jiang","raw_affiliation_strings":["School of optoelectronic science and engineering of UESTC, Chengdu"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of optoelectronic science and engineering of UESTC, Chengdu","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109374848","display_name":"Xinmei Yang","orcid":"https://orcid.org/0000-0003-3537-4582"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xinmei Yang","raw_affiliation_strings":["School of optoelectronic science and engineering of UESTC, Chengdu"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of optoelectronic science and engineering of UESTC, Chengdu","institution_ids":["https://openalex.org/I150229711"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102794340","display_name":"Yaobin Li","orcid":"https://orcid.org/0000-0003-3916-4208"},"institutions":[{"id":"https://openalex.org/I150229711","display_name":"University of Electronic Science and Technology of China","ror":"https://ror.org/04qr3zq92","country_code":"CN","type":"education","lineage":["https://openalex.org/I150229711"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaobin Li","raw_affiliation_strings":["School of optoelectronic science and engineering of UESTC, Chengdu"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of optoelectronic science and engineering of UESTC, Chengdu","institution_ids":["https://openalex.org/I150229711"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I150229711"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"46","last_page":"50"},"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9979000091552734,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9977999925613403,"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/jaccard-index","display_name":"Jaccard index","score":0.7575765252113342},{"id":"https://openalex.org/keywords/reciprocal","display_name":"Reciprocal","score":0.7019351720809937},{"id":"https://openalex.org/keywords/decorrelation","display_name":"Decorrelation","score":0.7004932165145874},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.6119229197502136},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6056933403015137},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.5869589447975159},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5527806878089905},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5089595317840576},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.4773435890674591},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.46660420298576355},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4220791161060333},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.41007161140441895},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3386209011077881},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3223559856414795},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.08788114786148071}],"concepts":[{"id":"https://openalex.org/C203519979","wikidata":"https://www.wikidata.org/wiki/Q865360","display_name":"Jaccard index","level":3,"score":0.7575765252113342},{"id":"https://openalex.org/C2777742833","wikidata":"https://www.wikidata.org/wiki/Q1964083","display_name":"Reciprocal","level":2,"score":0.7019351720809937},{"id":"https://openalex.org/C177860922","wikidata":"https://www.wikidata.org/wiki/Q788608","display_name":"Decorrelation","level":2,"score":0.7004932165145874},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.6119229197502136},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6056933403015137},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.5869589447975159},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5527806878089905},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5089595317840576},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.4773435890674591},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.46660420298576355},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4220791161060333},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.41007161140441895},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3386209011077881},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3223559856414795},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.08788114786148071},{"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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3282286.3282301","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3282286.3282301","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2nd International Conference on Graphics and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1616262590","https://openalex.org/W1949591461","https://openalex.org/W1962025484","https://openalex.org/W1979260620","https://openalex.org/W2014602333","https://openalex.org/W2046835352","https://openalex.org/W2048110836","https://openalex.org/W2050461393","https://openalex.org/W2065296697","https://openalex.org/W2076188996","https://openalex.org/W2100398441","https://openalex.org/W2149991777","https://openalex.org/W2167215970","https://openalex.org/W2204750386","https://openalex.org/W2259687230","https://openalex.org/W2294543795","https://openalex.org/W2300840837","https://openalex.org/W2342611082","https://openalex.org/W2400247096","https://openalex.org/W2433217581","https://openalex.org/W2467139031","https://openalex.org/W2475284720","https://openalex.org/W2510970676","https://openalex.org/W2584637367","https://openalex.org/W2593329034","https://openalex.org/W2950248853","https://openalex.org/W2952956153","https://openalex.org/W2964130064","https://openalex.org/W3100555577","https://openalex.org/W3102431071","https://openalex.org/W4244531973"],"related_works":["https://openalex.org/W4254879869","https://openalex.org/W3022576529","https://openalex.org/W1604939135","https://openalex.org/W2628526247","https://openalex.org/W2596401011","https://openalex.org/W2767543488","https://openalex.org/W2901968357","https://openalex.org/W4231537015","https://openalex.org/W2020613036","https://openalex.org/W2137791473"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,37,46,65,78,89,110,123,147],"new":[4],"method":[5,80,137],"which":[6,44,63,113],"combine":[7,109],"Singular":[8,53],"Vector":[9,54],"Decomposition":[10,55],"with":[11,68],"k-reciprocal":[12,79,104,111,119],"encoding":[13,117],"for":[14,168,171],"the":[15,23,33,50,69,97,103,133,150],"application":[16],"of":[17],"person":[18],"re-identification(re-ID).":[19],"When":[20],"we":[21,76,108],"use":[22],"Euclidean":[24],"distance":[25,128,131],"to":[26,58,81,95,158,164,177,183],"retrieve":[27],"person,":[28],"it":[29,145],"is":[30,56,86,92,114,156,162,175,181],"observed":[31],"that":[32],"weight":[34],"vectors":[35],"in":[36,60,102],"fully":[38],"connected":[39],"layer":[40],"are":[41,101],"usually":[42],"correlated,":[43],"makes":[45],"large":[47],"impact":[48],"on":[49,88,141,166],"retrieval":[51],"result.":[52],"adopted":[57],"decorrelation":[59],"this":[61],"article,":[62],"has":[64,138],"better":[66],"performance":[67],"restraint":[70],"and":[71,129,143,160,179],"relaxation":[72],"iteration":[73],"training.":[74],"Meanwhile,":[75],"add":[77],"above":[82],"result,":[83],"our":[84],"hypothesis":[85],"based":[87],"gallery":[90],"image":[91],"more":[93],"likely":[94],"match":[96],"probe":[98],"when":[99],"they":[100],"nearest":[105,120],"neighbors.":[106],"So":[107],"feature":[112],"calculated":[115],"by":[116],"its":[118],"neighbors":[121],"into":[122],"single":[124],"vector":[125],"under":[126],"Jaccard":[127],"original":[130],"as":[132],"final":[134],"distance.":[135],"Our":[136],"been":[139],"experimented":[140],"Market-1501":[142,167],"CUHK03,":[144],"achieves":[146],"great":[148],"performance,":[149],"results":[151],"show":[152],"that,":[153],"rank-1":[154,173],"accuracy":[155,174],"improved":[157,163,176,182],"82.69%":[159],"mAP":[161,180],"70.60%":[165],"CaffeNet,":[169],"while":[170],"ResNet-50,":[172],"82.63%":[178],"73.32%.":[184]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}