{"id":"https://openalex.org/W2648524575","doi":"https://doi.org/10.1109/icassp.2017.7952462","title":"LPCV: Learning projections from corresponding views for person re-identification","display_name":"LPCV: Learning projections from corresponding views for person re-identification","publication_year":2017,"publication_date":"2017-03-01","ids":{"openalex":"https://openalex.org/W2648524575","doi":"https://doi.org/10.1109/icassp.2017.7952462","mag":"2648524575"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2017.7952462","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2017.7952462","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5100410326","display_name":"Hong Liu","orcid":"https://orcid.org/0000-0002-7498-6541"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Hong Liu","raw_affiliation_strings":["Ministry of Education, Peking University"],"affiliations":[{"raw_affiliation_string":"Ministry of Education, Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109405151","display_name":"Qiao Guan","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiao Guan","raw_affiliation_strings":["Ministry of Education, Peking University"],"affiliations":[{"raw_affiliation_string":"Ministry of Education, Peking University","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100410326"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":0.182,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.55382472,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1777","last_page":"1781"},"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":0.9944999814033508,"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":0.9918000102043152,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.6871237754821777},{"id":"https://openalex.org/keywords/disjoint-sets","display_name":"Disjoint sets","score":0.6772841215133667},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6669521927833557},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6663613319396973},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.646121621131897},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.6269301772117615},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5356848239898682},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5335469841957092},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.4910125732421875},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.471332311630249},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.47112321853637695},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.4144511818885803},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3280203342437744},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1964840590953827},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.09194689989089966}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6871237754821777},{"id":"https://openalex.org/C45340560","wikidata":"https://www.wikidata.org/wiki/Q215382","display_name":"Disjoint sets","level":2,"score":0.6772841215133667},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6669521927833557},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6663613319396973},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.646121621131897},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.6269301772117615},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5356848239898682},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5335469841957092},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.4910125732421875},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.471332311630249},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.47112321853637695},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.4144511818885803},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3280203342437744},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1964840590953827},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.09194689989089966},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"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/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","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},{"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2017.7952462","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2017.7952462","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.75,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W41482161","https://openalex.org/W46454230","https://openalex.org/W140822990","https://openalex.org/W157648163","https://openalex.org/W166429404","https://openalex.org/W1563344580","https://openalex.org/W1927348918","https://openalex.org/W1928419358","https://openalex.org/W1949591461","https://openalex.org/W1962025484","https://openalex.org/W1991452654","https://openalex.org/W2046835352","https://openalex.org/W2048110836","https://openalex.org/W2068042582","https://openalex.org/W2079972027","https://openalex.org/W2109824782","https://openalex.org/W2115669554","https://openalex.org/W2151873133","https://openalex.org/W2167292325","https://openalex.org/W2220271458","https://openalex.org/W2300840837","https://openalex.org/W2474013209","https://openalex.org/W6601733005","https://openalex.org/W6601887387","https://openalex.org/W6606760634","https://openalex.org/W6633869515","https://openalex.org/W6640310490"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W1983936910","https://openalex.org/W156213964","https://openalex.org/W2050960118","https://openalex.org/W1499137908"],"abstract_inverted_index":{"Person":[0],"re-identification":[1],"is":[2],"an":[3,13,47],"important":[4],"topic":[5],"in":[6],"visual":[7],"surveillance,":[8],"which":[9],"aims":[10],"at":[11],"recognizing":[12],"individual":[14],"over":[15],"disjoint":[16],"camera":[17,53,122],"views.":[18,94],"As":[19],"a":[20,35,69,105,118,126],"major":[21],"aspect":[22],"of":[23,60],"person":[24,80,119],"re-identification,":[25],"distance":[26,42],"metric":[27,43],"learning":[28,44],"has":[29],"been":[30],"widely":[31],"studied":[32],"to":[33,72,88,100,116,123],"seek":[34],"discriminative":[36],"matching":[37,157],"metric.":[38],"However,":[39],"most":[40],"existing":[41],"methods":[45],"learn":[46,73,89],"identical":[48],"projection":[49],"matrix":[50],"for":[51,79,92],"all":[52],"views,":[54],"while":[55],"ignoring":[56],"the":[57,85,150,155],"own":[58],"characteristic":[59],"each":[61],"view.":[62],"To":[63],"address":[64],"this":[65,112],"issue,":[66],"we":[67,83,110],"propose":[68],"novel":[70],"method":[71,145],"projections":[74,91,97],"from":[75,120],"corresponding":[76],"views":[77],"(LPCV)":[78],"re-identification.":[81],"First,":[82],"use":[84,111],"labeled":[86],"features":[87,103],"different":[90,93],"Then,":[95],"these":[96],"are":[98],"used":[99],"transform":[101],"tested":[102],"into":[104],"new":[106,113],"feature":[107,114],"space.":[108],"Finally,":[109],"space":[115],"identify":[117],"one":[121],"another":[124],"with":[125],"standard":[127],"nearest-neighbor":[128],"voting":[129],"method.":[130],"Experimental":[131],"results":[132],"on":[133,154],"three":[134],"challenging":[135],"datasets":[136],"VIPeR,":[137],"PRID":[138],"450S":[139],"and":[140],"CUHK01":[141],"demonstrate":[142],"that":[143],"our":[144],"significantly":[146],"performs":[147],"favorably":[148],"against":[149],"state-of-the-art":[151],"methods,":[152],"especially":[153],"rank-1":[156],"rate.":[158]},"counts_by_year":[{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
