{"id":"https://openalex.org/W1925384340","doi":"https://doi.org/10.1109/cvpr.2015.7299048","title":"Face alignment using cascade Gaussian process regression trees","display_name":"Face alignment using cascade Gaussian process regression trees","publication_year":2015,"publication_date":"2015-06-01","ids":{"openalex":"https://openalex.org/W1925384340","doi":"https://doi.org/10.1109/cvpr.2015.7299048","mag":"1925384340"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2015.7299048","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7299048","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","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/A5100422970","display_name":"Dong\u2010Hoon Lee","orcid":"https://orcid.org/0000-0002-5013-4440"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Donghoon Lee","raw_affiliation_strings":["Korea Advanced institute of Science and Technology, Yuseong-gu, Daejeon, Korea","Korea Advanced Institute of Science and Technology, 291, Daehak-ro, Yuseong-gu, Daejeon, Korea"],"affiliations":[{"raw_affiliation_string":"Korea Advanced institute of Science and Technology, Yuseong-gu, Daejeon, Korea","institution_ids":["https://openalex.org/I157485424"]},{"raw_affiliation_string":"Korea Advanced Institute of Science and Technology, 291, Daehak-ro, Yuseong-gu, Daejeon, Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010227336","display_name":"Hyunsin Park","orcid":"https://orcid.org/0000-0003-3556-5792"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyunsin Park","raw_affiliation_strings":["Korea Advanced institute of Science and Technology, Yuseong-gu, Daejeon, Korea","Korea Advanced Institute of Science and Technology, 291, Daehak-ro, Yuseong-gu, Daejeon, Korea"],"affiliations":[{"raw_affiliation_string":"Korea Advanced institute of Science and Technology, Yuseong-gu, Daejeon, Korea","institution_ids":["https://openalex.org/I157485424"]},{"raw_affiliation_string":"Korea Advanced Institute of Science and Technology, 291, Daehak-ro, Yuseong-gu, Daejeon, Korea","institution_ids":["https://openalex.org/I157485424"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073287748","display_name":"Chang D. Yoo","orcid":"https://orcid.org/0000-0002-0756-7179"},"institutions":[{"id":"https://openalex.org/I157485424","display_name":"Korea Advanced Institute of Science and Technology","ror":"https://ror.org/05apxxy63","country_code":"KR","type":"education","lineage":["https://openalex.org/I157485424"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Chang D. Yoo","raw_affiliation_strings":["Korea Advanced institute of Science and Technology, Yuseong-gu, Daejeon, Korea","Korea Advanced Institute of Science and Technology, 291, Daehak-ro, Yuseong-gu, Daejeon, Korea"],"affiliations":[{"raw_affiliation_string":"Korea Advanced institute of Science and Technology, Yuseong-gu, Daejeon, Korea","institution_ids":["https://openalex.org/I157485424"]},{"raw_affiliation_string":"Korea Advanced Institute of Science and Technology, 291, Daehak-ro, Yuseong-gu, Daejeon, Korea","institution_ids":["https://openalex.org/I157485424"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100422970"],"corresponding_institution_ids":["https://openalex.org/I157485424"],"apc_list":null,"apc_paid":null,"fwci":11.6052,"has_fulltext":false,"cited_by_count":119,"citation_normalized_percentile":{"value":0.98980413,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"4204","last_page":"4212"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9991000294685364,"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":0.9991000294685364,"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/T11448","display_name":"Face recognition and analysis","score":0.996999979019165,"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":0.9932000041007996,"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/cascade","display_name":"Cascade","score":0.718659520149231},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.6683374047279358},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6612253189086914},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6452847123146057},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6234270334243774},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.6121158599853516},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5722062587738037},{"id":"https://openalex.org/keywords/kriging","display_name":"Kriging","score":0.5692332983016968},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5190882682800293},{"id":"https://openalex.org/keywords/gaussian-filter","display_name":"Gaussian filter","score":0.45672234892845154},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.45509737730026245},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.4156973361968994},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.31931373476982117},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.29704421758651733},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.0993351936340332}],"concepts":[{"id":"https://openalex.org/C34146451","wikidata":"https://www.wikidata.org/wiki/Q5048094","display_name":"Cascade","level":2,"score":0.718659520149231},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.6683374047279358},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6612253189086914},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6452847123146057},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6234270334243774},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.6121158599853516},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5722062587738037},{"id":"https://openalex.org/C81692654","wikidata":"https://www.wikidata.org/wiki/Q225926","display_name":"Kriging","level":2,"score":0.5692332983016968},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5190882682800293},{"id":"https://openalex.org/C65892221","wikidata":"https://www.wikidata.org/wiki/Q1113935","display_name":"Gaussian filter","level":3,"score":0.45672234892845154},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.45509737730026245},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.4156973361968994},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.31931373476982117},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.29704421758651733},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0993351936340332},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cvpr.2015.7299048","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2015.7299048","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.964.6546","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.964.6546","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cv-foundation.org/openaccess/content_cvpr_2015/papers/Lee_Face_Alignment_Using_2015_CVPR_paper.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1516082955","https://openalex.org/W1527240141","https://openalex.org/W1678356000","https://openalex.org/W1746819321","https://openalex.org/W1796263212","https://openalex.org/W1990937109","https://openalex.org/W1995266040","https://openalex.org/W1998294030","https://openalex.org/W2008932806","https://openalex.org/W2032558548","https://openalex.org/W2040726420","https://openalex.org/W2047028564","https://openalex.org/W2047508432","https://openalex.org/W2058961190","https://openalex.org/W2066454034","https://openalex.org/W2087681821","https://openalex.org/W2111372597","https://openalex.org/W2115136130","https://openalex.org/W2136000821","https://openalex.org/W2156531583","https://openalex.org/W2157285372","https://openalex.org/W2160126058","https://openalex.org/W3097096317","https://openalex.org/W4211049957","https://openalex.org/W4255455317","https://openalex.org/W4297796757","https://openalex.org/W6630870171","https://openalex.org/W6631618440","https://openalex.org/W6638488279","https://openalex.org/W6662335928"],"related_works":["https://openalex.org/W566010457","https://openalex.org/W2600092203","https://openalex.org/W4300066510","https://openalex.org/W4311388919","https://openalex.org/W2056958800","https://openalex.org/W2803685231","https://openalex.org/W4293503520","https://openalex.org/W3134152097","https://openalex.org/W2966696655","https://openalex.org/W4205181450"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"a":[5,26,33,37,41],"face":[6,125],"alignment":[7,126],"method":[8],"that":[9,128],"uses":[10],"cascade":[11,27,84],"Gaussian":[12,20,34,101],"process":[13,21,35],"regression":[14,22,85],"trees":[15,23,57,86],"(cGPRT)":[16],"constructed":[17],"by":[18,40],"combining":[19],"(GPRT)":[24],"in":[25,63,78],"stage-wise":[28],"manner.":[29],"Here,":[30],"GPRT":[31,94],"is":[32],"with":[36,89,121],"kernel":[38,46],"defined":[39],"set":[42],"of":[43,56,73,100],"trees.":[44],"The":[45],"measures":[47],"the":[48,54,59,64,71,79,83,122,141,148],"similarity":[49],"between":[50],"two":[51,60],"inputs":[52,61],"as":[53,82],"number":[55],"where":[58],"fall":[62],"same":[65,80],"leaves.":[66],"Without":[67],"increasing":[68],"prediction":[69,72],"time,":[70],"cGPRT":[74,133],"can":[75],"be":[76],"performed":[77,138],"framework":[81],"(CRT)":[87],"but":[88],"better":[90],"generalization.":[91],"Features":[92],"for":[93],"are":[95,147],"designed":[96],"using":[97,134],"shape-indexed":[98,135],"difference":[99],"(DoG)":[102],"filter":[103],"responses":[104],"sampled":[105],"from":[106],"local":[107],"retinal":[108],"patterns":[109],"to":[110,114],"increase":[111],"stability":[112],"and":[113,143],"attain":[115],"robustness":[116],"against":[117],"geometric":[118],"variances.":[119],"Compared":[120],"previous":[123],"CRT-based":[124],"methods":[127],"have":[129],"shown":[130],"state-of-the-art":[131],"performances,":[132],"DoG":[136],"features":[137],"best":[139],"on":[140],"HELEN":[142],"300-W":[144],"datasets":[145],"which":[146],"most":[149],"challenging":[150],"dataset":[151],"today.":[152]},"counts_by_year":[{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":11},{"year":2020,"cited_by_count":14},{"year":2019,"cited_by_count":20},{"year":2018,"cited_by_count":16},{"year":2017,"cited_by_count":27},{"year":2016,"cited_by_count":17},{"year":2015,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
