{"id":"https://openalex.org/W2779335121","doi":null,"title":"Face recognition enhancement through the use of depth maps and deep learning","display_name":"Face recognition enhancement through the use of depth maps and deep learning","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2779335121","mag":"2779335121"},"language":"en","primary_location":{"id":"pmh:oai:dspace.lboro.ac.uk:2134/26606","doi":null,"is_oa":true,"landing_page_url":"https://dspace.lboro.ac.uk/2134/26606","pdf_url":null,"source":{"id":"https://openalex.org/S4306401023","display_name":"Loughborough University Institutional Repository (Loughborough University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I143804889","host_organization_name":"Loughborough University","host_organization_lineage":["https://openalex.org/I143804889"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Thesis"},"parent_works":[],"lineage":["https://openalex.org/W2779335121"],"child_works_count":0,"type":"dissertation","is_traditional":true,"indexed_in":[],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://dspace.lboro.ac.uk/2134/26606","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5009184855","display_name":"Yaser Saleh","orcid":"https://orcid.org/0000-0002-2257-721X","observed_orcids":["https://orcid.org/0000-0002-2257-721X"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Yaser Saleh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5009184855"],"corresponding_institution_ids":[],"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/T11448","display_name":"Face recognition and analysis","score":0.9702000021934509,"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/T11448","display_name":"Face recognition and analysis","score":0.9702000021934509,"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/T10057","display_name":"Face and Expression Recognition","score":0.027899999171495438,"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/T10828","display_name":"Biometric Identification and Security","score":0.0005000000237487257,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/face-recognition","display_name":"face recognition","score":0.9829999804496765},{"id":"https://openalex.org/keywords/depth-maps","display_name":"depth images","score":0.996999979019165},{"id":"https://openalex.org/keywords/kinect","display_name":"Kinect sensor","score":0.7829999923706055},{"id":"https://openalex.org/keywords/multimodal-fusion","display_name":"multimodal fusion","score":0.7170000076293945},{"id":"https://openalex.org/keywords/low-light-conditions","display_name":"low-light conditions","score":0.6480000019073486},{"id":"https://openalex.org/keywords/pose-variation","display_name":"pose variation","score":0.7649999856948853},{"id":"https://openalex.org/keywords/viewpoint-variation","display_name":"viewpoint variation","score":0.7170000076293945},{"id":"https://openalex.org/keywords/3d-face-reconstruction","display_name":"3D face reconstruction","score":0.9190000295639038},{"id":"https://openalex.org/keywords/vgg16","display_name":"VGG16","score":0.843999981880188},{"id":"https://openalex.org/keywords/vgg19","display_name":"VGG19","score":0.8149999976158142},{"id":"https://openalex.org/keywords/resnet-152","display_name":"ResNet-152","score":0.6399999856948853},{"id":"https://openalex.org/keywords/resnet-50","display_name":"ResNet50","score":0.6809999942779541},{"id":"https://openalex.org/keywords/data-augmentation","display_name":"data augmentation","score":0.6830000281333923},{"id":"https://openalex.org/keywords/eigenfaces","display_name":"eigenfaces","score":0.4880000054836273},{"id":"https://openalex.org/keywords/low-back-pain","display_name":"low back pain","score":0.7979999780654907},{"id":"https://openalex.org/keywords/convolutional-neural-networks","display_name":"convolutional neural networks","score":0.734000027179718}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7870346903800964},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.7413465976715088},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7192305326461792},{"id":"https://openalex.org/C104906051","wikidata":"https://www.wikidata.org/wiki/Q29695","display_name":"Eigenface","level":4,"score":0.7090458869934082},{"id":"https://openalex.org/C88799230","wikidata":"https://www.wikidata.org/wiki/Q3398329","display_name":"Three-dimensional face recognition","level":5,"score":0.6736650466918945},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.577246367931366},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5613139271736145},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5276795029640198},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5249666571617126},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46794289350509644},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.454165518283844},{"id":"https://openalex.org/C14551309","wikidata":"https://www.wikidata.org/wiki/Q4636325","display_name":"3D single-object recognition","level":4,"score":0.42915648221969604},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4243374466896057},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.34631502628326416},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.23861396312713623},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08187982439994812},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"pmh:oai:dspace.lboro.ac.uk:2134/26606","doi":null,"is_oa":true,"landing_page_url":"https://dspace.lboro.ac.uk/2134/26606","pdf_url":null,"source":{"id":"https://openalex.org/S4306401023","display_name":"Loughborough University Institutional Repository (Loughborough University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I143804889","host_organization_name":"Loughborough University","host_organization_lineage":["https://openalex.org/I143804889"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Thesis"},{"id":"pmh:oai:figshare.com:article/9407099","doi":null,"is_oa":true,"landing_page_url":"https://figshare.com/articles/Face_recognition_enhancement_through_the_use_of_depth_maps_and_deep_learning/9407099","pdf_url":null,"source":{"id":"https://openalex.org/S4306402585","display_name":"Loughborough University Research Repository (Loughborough University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I143804889","host_organization_name":"Loughborough University","host_organization_lineage":["https://openalex.org/I143804889"],"host_organization_lineage_names":[],"type":"repository"},"license":"public-domain","license_id":"https://openalex.org/licenses/public-domain","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Thesis"},{"id":"mag:2779335121","doi":null,"is_oa":false,"landing_page_url":"https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.727724","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:dspace.lboro.ac.uk:2134/26606","doi":null,"is_oa":true,"landing_page_url":"https://dspace.lboro.ac.uk/2134/26606","pdf_url":null,"source":{"id":"https://openalex.org/S4306401023","display_name":"Loughborough University Institutional Repository (Loughborough University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I143804889","host_organization_name":"Loughborough University","host_organization_lineage":["https://openalex.org/I143804889"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Thesis"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320341","display_name":"Loughborough University","ror":"https://ror.org/04vg4w365"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2779335121.pdf","grobid_xml":"https://content.openalex.org/works/W2779335121.grobid-xml"},"referenced_works_count":57,"referenced_works":["https://openalex.org/W99485931","https://openalex.org/W101671670","https://openalex.org/W170472577","https://openalex.org/W1487583988","https://openalex.org/W1509966554","https://openalex.org/W1537451167","https://openalex.org/W1545641654","https://openalex.org/W1578352865","https://openalex.org/W1622838444","https://openalex.org/W1686810756","https://openalex.org/W1827297289","https://openalex.org/W1861492603","https://openalex.org/W1921147789","https://openalex.org/W1950843348","https://openalex.org/W1953354605","https://openalex.org/W1970030635","https://openalex.org/W1988730736","https://openalex.org/W1991357295","https://openalex.org/W1995884877","https://openalex.org/W1998808035","https://openalex.org/W2007178811","https://openalex.org/W2019464758","https://openalex.org/W2028592945","https://openalex.org/W2030203266","https://openalex.org/W2041800626","https://openalex.org/W2044373869","https://openalex.org/W2064759377","https://openalex.org/W2068562306","https://openalex.org/W2086915492","https://openalex.org/W2096171208","https://openalex.org/W2096733369","https://openalex.org/W2097117768","https://openalex.org/W2098693229","https://openalex.org/W2105138955","https://openalex.org/W2111440402","https://openalex.org/W2114072031","https://openalex.org/W2115546586","https://openalex.org/W2117539524","https://openalex.org/W2120492695","https://openalex.org/W2121027212","https://openalex.org/W2136565860","https://openalex.org/W2138451337","https://openalex.org/W2140609507","https://openalex.org/W2144354855","https://openalex.org/W2145287260","https://openalex.org/W2145310492","https://openalex.org/W2151047074","https://openalex.org/W2153027217","https://openalex.org/W2160126058","https://openalex.org/W2163267793","https://openalex.org/W2163352848","https://openalex.org/W2165698076","https://openalex.org/W2274287116","https://openalex.org/W2325939864","https://openalex.org/W2612733445","https://openalex.org/W2963173190","https://openalex.org/W2963542991"],"related_works":["https://openalex.org/W2093938144","https://openalex.org/W2596912164","https://openalex.org/W3148458525","https://openalex.org/W7155165528","https://openalex.org/W4392990227","https://openalex.org/W2471692196","https://openalex.org/W2998085809","https://openalex.org/W2035009572","https://openalex.org/W3209753768","https://openalex.org/W4386413525"],"abstract_inverted_index":{"Face":[0],"recognition,":[1,148,164,439],"although":[2],"being":[3],"a":[4,11,111,139,177,232,324,332,378,434],"popular":[5,180,479],"area":[6],"of":[7,20,26,38,52,68,81,101,138,145,179,203,214,224,268,286,289,336,350,377,387,400,414,420,445,468,477,497,504],"research":[8,17,69,150],"for":[9,265,320,326,384],"over":[10],"decade":[12],"has":[13],"still":[14],"many":[15,375],"open":[16],"challenges.":[18],"Some":[19],"these":[21,360],"challenges":[22],"include":[23],"the":[24,36,50,62,78,82,87,115,135,143,210,215,221,225,236,266,284,287,295,301,312,343,351,371,385,388,392,415,426,455,465,472,475,494,502],"recognition":[25,30,45,131,171,183,207,250,271,413,447,462,491],"poorly":[27],"illuminated":[28],"faces,":[29],"under":[31,46,98,257,418],"pose":[32],"variations":[33,419],"and":[34,54,104,118,195,242,294,305,323,402,484,492],"also":[35,430],"challenge":[37],"capturing":[39,405],"sufficient":[40,406],"training":[41,136,367,386,407],"data":[42,92,288,408],"to":[43,76,94,105,128,199,209,245,273,276,373,437,500],"enable":[44],"pose/viewpoint":[47],"changes.":[48],"With":[49,142],"appearance":[51],"cheap":[53],"effective":[55,247,306,466,495],"multimodal":[56],"image":[57,293,380,389],"capture":[58,374],"hardware,":[59],"such":[60,505],"as":[61,89,365,433],"Microsoft":[63],"Kinect":[64,88,226],"device,":[65],"new":[66,107],"possibilities":[67],"have":[70],"been":[71],"uncovered.":[72],"One":[73],"opportunity":[74],"is":[75,188,240,243,272,329,410],"explore":[77],"potential":[79],"use":[80,285,467,476,496],"depth":[83,116,154,216,252,297,451,487],"maps":[84,117,488],"generated":[85,219],"by":[86,133,159,220,300],"an":[90],"additional":[91],"source":[93],"recognize":[95],"human":[96,416],"faces":[97],"low":[99],"levels":[100,444],"scene":[102],"illumination,":[103,160],"generate":[106],"images":[108,122,218,279,361],"through":[109,283],"creating":[110],"3D":[112,307,345,394],"model":[113,346,395],"using":[114,251,303],"visible-spectrum":[119],"/":[120],"RGB":[121,292],"that":[123,190,262,331,347,409,425],"can":[124,161,339,362,429],"then":[125],"be":[126,246,274,340,363,431],"used":[127,168,364,432],"enhance":[129,501],"face":[130,147,163,170,182,206,249,270,278,352,417,438,446,461,490],"accuracy":[132,204,448],"improving":[134],"phase":[137],"classification":[140,327],"task..":[141],"goal":[144,267],"enhancing":[146,269],"this":[149,175,230],"first":[151],"investigated":[152],"how":[153],"maps,":[155],"since":[156],"not":[157],"affected":[158],"improve":[162],"if":[165,353],"algorithms":[166,184,191,463],"traditionally":[167],"in":[169,205,248,255,280,404,412,458,486],"were":[172],"used.":[173],"To":[174,228],"effect":[176],"number":[178,335],"benchmark":[181],"are":[185,197],"tested.":[186],"It":[187],"proved":[189],"based":[192,315,489],"on":[193,316,450],"LBP":[194],"Eigenfaces":[196],"able":[198,275],"provide":[200],"high":[201,212,443],"level":[202],"due":[208],"significantly":[211,442],"resolution":[213],"map":[217,253,298],"latest":[222],"version":[223],"device.":[227],"complement":[229],"work":[231],"novel":[233,435],"algorithm":[234],"named":[235],"Dense":[237],"Feature":[238],"Detector":[239],"presented":[241,264],"proven":[244],"images,":[254,368],"particular":[256],"wellilluminated":[258],"conditions.":[259],"Another":[260],"technique":[261],"was":[263],"reconstruct":[277],"different":[281,382],"angles,":[282],"one":[290],"frontal":[291],"corresponding":[296],"captured":[299,354],"Kinect,":[302],"faster":[304],"object":[308],"reconstruction":[309],"technique.":[310],"Using":[311],"Overfeat":[313],"network":[314],"Convolutional":[317],"Neural":[318],"Networks":[319],"feature":[321],"extraction":[322],"SVM":[325],"it":[328],"shown":[330],"technically":[333],"unlimited":[334],"multiple":[337],"views":[338],"created":[341],"from":[342,381],"proposed":[344,393],"consists":[348],"features":[349],"real":[355,366],"at":[356],"similar":[357],"angles.":[358],"Thus":[359,391],"thus":[369],"removing":[370],"need":[372],"examples":[376],"facial":[379],"viewpoints":[383],"classifier.":[390],"will":[396],"save":[397],"significant":[398],"amount":[399],"time":[401],"effort":[403],"essential":[411],"pose/viewpoint.":[421],"The":[422],"thesis":[423,473],"argues":[424],"same":[427],"approach":[428,436],"which":[440],"promises":[441],"base":[449],"images.":[452],"Finally":[453],"following":[454],"recent":[456],"trends":[457],"replacing":[459],"traditional":[460],"with":[464],"deep":[469],"learning":[470],"networks,":[471,480],"investigates":[474],"four":[478],"VGG-16,":[481],"VGG-19,":[482],"VGG-S":[483],"GoogLeNet":[485],"proposes":[493],"Transfer":[498],"Learning":[499,507],"performance":[503],"Deep":[506],"networks.":[508]},"counts_by_year":[],"updated_date":"2026-11-14T11:04:58.165337","created_date":"2018-01-05T00:00:00"}