{"id":"https://openalex.org/W14462282","doi":null,"title":"Looking at People Using Partial Least Squares","display_name":"Looking at People Using Partial Least Squares","publication_year":2010,"publication_date":"2010-01-01","ids":{"openalex":"https://openalex.org/W14462282","mag":"14462282"},"language":"en","primary_location":{"id":"pmh:oai:drum.lib.umd.edu:1903/10822","doi":null,"is_oa":true,"landing_page_url":"http://hdl.handle.net/1903/10822","pdf_url":"http://hdl.handle.net/1903/10822","source":{"id":"https://openalex.org/S4306401518","display_name":"University Libraries (University of Maryland)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I66946132","host_organization_name":"University of Maryland, College Park","host_organization_lineage":["https://openalex.org/I66946132"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dissertation"},"volume":null,"type":"dissertation","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"http://hdl.handle.net/1903/10822","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044741265","display_name":"William Robson Schwartz","orcid":"https://orcid.org/0000-0003-1449-8834","observed_orcids":["https://orcid.org/0000-0003-1449-8834"]},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"William Robson Schwartz","raw_affiliation_strings":["University of Maryland, College Park"],"raw_orcid":"https://orcid.org/0000-0003-1449-8834","affiliations":[{"raw_affiliation_string":"University of Maryland, College Park","institution_ids":["https://openalex.org/I66946132"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5044741265"],"corresponding_institution_ids":["https://openalex.org/I66946132"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.36469998955726624,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.36469998955726624,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.16990000009536743,"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/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.14560000598430634,"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/partial-least-squares","display_name":"partial least squares","score":0.9459999799728394},{"id":"https://openalex.org/keywords/image-descriptors","display_name":"image descriptors","score":0.8679999709129333},{"id":"https://openalex.org/keywords/human-detection","display_name":"human detection","score":0.8939999938011169},{"id":"https://openalex.org/keywords/partial-occlusion","display_name":"partial occlusion","score":0.9179999828338623},{"id":"https://openalex.org/keywords/face-identification","display_name":"face identification","score":0.9589999914169312},{"id":"https://openalex.org/keywords/appearance-based-recognition","display_name":"appearance-based recognition","score":0.6790000200271606},{"id":"https://openalex.org/keywords/partial-least-squares-regression","display_name":"partial least squares regression","score":0.6819999814033508},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"dimensionality reduction","score":0.7179999947547913},{"id":"https://openalex.org/keywords/latent-variables","display_name":"latent variables","score":0.6629999876022339}],"concepts":[{"id":"https://openalex.org/C22354355","wikidata":"https://www.wikidata.org/wiki/Q422009","display_name":"Partial least squares regression","level":2,"score":0.8367977142333984},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7133329510688782},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6423139572143555},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6132600903511047},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.606153130531311},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.535454511642456},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5344179272651672},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5162796378135681},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.44530150294303894},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.4308997690677643},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3435137867927551},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","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":3,"locations":[{"id":"pmh:oai:drum.lib.umd.edu:1903/10822","doi":null,"is_oa":true,"landing_page_url":"http://hdl.handle.net/1903/10822","pdf_url":"http://hdl.handle.net/1903/10822","source":{"id":"https://openalex.org/S4306401518","display_name":"University Libraries (University of Maryland)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I66946132","host_organization_name":"University of Maryland, College Park","host_organization_lineage":["https://openalex.org/I66946132"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dissertation"},{"id":"pmh:oai:pqdtoai.proquest.com:3426408","doi":null,"is_oa":false,"landing_page_url":"http://pqdtopen.proquest.com/#viewpdf?dispub=3426408","pdf_url":"http://pqdtopen.proquest.com/#viewpdf?dispub=3426408","source":{"id":"https://openalex.org/S7407064308","display_name":"ProQuest Demo Repository","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"thesis"},{"id":"mag:14462282","doi":null,"is_oa":false,"landing_page_url":"https://drum.lib.umd.edu/bitstream/1903/10822/1/Schwartz_umd_0117E_11471.pdf","pdf_url":null,"source":null,"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":null}],"best_oa_location":{"id":"pmh:oai:drum.lib.umd.edu:1903/10822","doi":null,"is_oa":true,"landing_page_url":"http://hdl.handle.net/1903/10822","pdf_url":"http://hdl.handle.net/1903/10822","source":{"id":"https://openalex.org/S4306401518","display_name":"University Libraries (University of Maryland)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I66946132","host_organization_name":"University of Maryland, College Park","host_organization_lineage":["https://openalex.org/I66946132"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Dissertation"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W14462282.pdf","grobid_xml":"https://content.openalex.org/works/W14462282.grobid-xml"},"referenced_works_count":36,"referenced_works":["https://openalex.org/W1213294141","https://openalex.org/W1535298460","https://openalex.org/W1536943225","https://openalex.org/W1564380921","https://openalex.org/W1567019178","https://openalex.org/W1573508639","https://openalex.org/W1989702938","https://openalex.org/W1996765463","https://openalex.org/W2026321378","https://openalex.org/W2029720353","https://openalex.org/W2033419168","https://openalex.org/W2039051707","https://openalex.org/W2044465660","https://openalex.org/W2054891869","https://openalex.org/W2057175746","https://openalex.org/W2096112371","https://openalex.org/W2097698119","https://openalex.org/W2098699644","https://openalex.org/W2104606180","https://openalex.org/W2104679563","https://openalex.org/W2109258005","https://openalex.org/W2117072267","https://openalex.org/W2121899951","https://openalex.org/W2122378993","https://openalex.org/W2134380836","https://openalex.org/W2136353882","https://openalex.org/W2137225583","https://openalex.org/W2137385871","https://openalex.org/W2137659841","https://openalex.org/W2139139790","https://openalex.org/W2150298366","https://openalex.org/W2151103935","https://openalex.org/W2161969291","https://openalex.org/W2170248718","https://openalex.org/W2282794079","https://openalex.org/W2534262995"],"related_works":["https://openalex.org/W2534262995","https://openalex.org/W2122378993","https://openalex.org/W3151521004","https://openalex.org/W2576275366","https://openalex.org/W2028854488","https://openalex.org/W2366600326","https://openalex.org/W2293335733","https://openalex.org/W2555103504","https://openalex.org/W2160536163","https://openalex.org/W2750350980"],"abstract_inverted_index":{"Analysis":[0],"of":[1,6,46,55,84,102,109,113,139,144],"images":[2,36],"involving":[3],"humans":[4],"is":[5,37,99,118,164,180,198],"significant":[7,150],"interest":[8],"in":[9,35,148,152],"computer":[10,153],"vision":[11],"because":[12],"problems":[13],"such":[14],"as":[15,93],"detection,":[16],"modeling,":[17],"recognition,":[18],"and":[19,28,116,171,204],"tracking":[20],"are":[21],"fundamental":[22],"to":[23,120,160,167,182],"model":[24],"interactions":[25],"between":[26,107],"people":[27],"understand":[29],"high-level":[30],"activities.":[31],"Visual":[32],"information":[33,69],"contained":[34],"generally":[38],"represented":[39],"using":[40,146],"descriptors":[41,47,86,145],"(features).":[42],"Many":[43],"general":[44],"classes":[45],"have":[48],"been":[49],"proposed":[50],"focusing":[51],"on":[52,176,194],"different":[53],"characteristics":[54],"images.":[56],"Therefore,":[57],"if":[58],"one":[59,65],"considers":[60],"only":[61],"a":[62,71,81,89,100,124,131,141,158,173,195],"single":[63],"descriptor,":[64],"might":[66],"ignore":[67],"useful":[68],"for":[70,104,200],"given":[72],"task,":[73],"compromising":[74],"performance.":[75],"In":[76],"this":[77],"research":[78],"we":[79,156],"consider":[80],"rich":[82],"set":[83,143],"image":[85],"analyzed":[87],"by":[88,111],"statistical":[90],"technique":[91],"known":[92],"Partial":[94],"Least":[95],"Squares":[96],"(PLS).":[97],"PLS":[98,147,177],"class":[101],"methods":[103],"modeling":[105,203],"relations":[106],"sets":[108],"observations":[110],"means":[112],"latent":[114],"variables":[115],"it":[117],"used":[119],"project":[121],"exemplars":[122],"from":[123],"very":[125],"high":[126],"dimensional":[127,133],"feature":[128],"space":[129],"onto":[130],"low":[132],"subspace.":[134],"We":[135],"demonstrate":[136],"the":[137,185],"effectiveness":[138],"combining":[140],"richer":[142],"two":[149],"tasks":[151],"vision.":[154],"First,":[155],"propose":[157],"method":[159],"detect":[161],"humans,":[162],"which":[163],"then":[165],"extended":[166],"handle":[168],"partial":[169],"occlusion":[170],"finally":[172],"framework":[174,192],"based":[175,193],"regression":[178],"models":[179],"incorporated":[181],"further":[183],"reduce":[184],"computational":[186],"cost.":[187],"Second,":[188],"an":[189],"object":[190],"recognition":[191],"one-against-all":[196],"scheme":[197],"exploited":[199],"appearance-based":[201],"person":[202],"face":[205],"identification.":[206]},"counts_by_year":[],"updated_date":"2026-10-01T08:54:57.152042","created_date":"2016-06-24T00:00:00"}
