{"id":"https://openalex.org/W2511087420","doi":"https://doi.org/10.1109/icip.2016.7532891","title":"Weighted regularized ASM for face alignment","display_name":"Weighted regularized ASM for face alignment","publication_year":2016,"publication_date":"2016-08-17","ids":{"openalex":"https://openalex.org/W2511087420","doi":"https://doi.org/10.1109/icip.2016.7532891","mag":"2511087420"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2016.7532891","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7532891","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Image Processing (ICIP)","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/A5007621420","display_name":"Guillermo Ru\u00edz","orcid":"https://orcid.org/0000-0001-7422-7011"},"institutions":[{"id":"https://openalex.org/I170486558","display_name":"Pompeu Fabra University","ror":"https://ror.org/04n0g0b29","country_code":"ES","type":"education","lineage":["https://openalex.org/I170486558"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Guillermo Ruiz","raw_affiliation_strings":["Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain","institution_ids":["https://openalex.org/I170486558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009789112","display_name":"Eduard Ramon","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eduard Ramon","raw_affiliation_strings":["Crisalix S.A., Lausanne, Switzerland"],"affiliations":[{"raw_affiliation_string":"Crisalix S.A., Lausanne, Switzerland","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109292246","display_name":"Jaime Garc\u00eda","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jaime Garcia","raw_affiliation_strings":["Crisalix S.A., Lausanne, Switzerland"],"affiliations":[{"raw_affiliation_string":"Crisalix S.A., Lausanne, Switzerland","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021143022","display_name":"Miguel \u00c1. Gonz\u00e1lez Ballester","orcid":"https://orcid.org/0000-0002-9227-6826"},"institutions":[{"id":"https://openalex.org/I170486558","display_name":"Pompeu Fabra University","ror":"https://ror.org/04n0g0b29","country_code":"ES","type":"education","lineage":["https://openalex.org/I170486558"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Miguel A. Gonzalez Ballester","raw_affiliation_strings":["Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain","institution_ids":["https://openalex.org/I170486558"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5019420087","display_name":"Federico M. Sukno","orcid":"https://orcid.org/0000-0002-2029-1576"},"institutions":[{"id":"https://openalex.org/I170486558","display_name":"Pompeu Fabra University","ror":"https://ror.org/04n0g0b29","country_code":"ES","type":"education","lineage":["https://openalex.org/I170486558"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Federico M. Sukno","raw_affiliation_strings":["Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain"],"affiliations":[{"raw_affiliation_string":"Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain","institution_ids":["https://openalex.org/I170486558"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5007621420"],"corresponding_institution_ids":["https://openalex.org/I170486558"],"apc_list":null,"apc_paid":null,"fwci":0.334,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.65913706,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"2906","last_page":"2910"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9983000159263611,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9909999966621399,"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/prior-probability","display_name":"Prior probability","score":0.7834624648094177},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7166967391967773},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.7061637043952942},{"id":"https://openalex.org/keywords/projection","display_name":"Projection (relational algebra)","score":0.6969313025474548},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6196805238723755},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.5712401866912842},{"id":"https://openalex.org/keywords/active-shape-model","display_name":"Active shape model","score":0.4546322226524353},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.41059035062789917},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.40636128187179565},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.34307432174682617},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.18494883179664612}],"concepts":[{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.7834624648094177},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7166967391967773},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.7061637043952942},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.6969313025474548},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6196805238723755},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.5712401866912842},{"id":"https://openalex.org/C129641003","wikidata":"https://www.wikidata.org/wiki/Q267189","display_name":"Active shape model","level":3,"score":0.4546322226524353},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.41059035062789917},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.40636128187179565},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.34307432174682617},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.18494883179664612},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.0},{"id":"https://openalex.org/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2016.7532891","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2016.7532891","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6700000166893005,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1549638","https://openalex.org/W1524698129","https://openalex.org/W1560460813","https://openalex.org/W1769974409","https://openalex.org/W1851901876","https://openalex.org/W2003931381","https://openalex.org/W2014322185","https://openalex.org/W2038952578","https://openalex.org/W2041142434","https://openalex.org/W2068420994","https://openalex.org/W2110579044","https://openalex.org/W2145922550","https://openalex.org/W2151219244","https://openalex.org/W6639182124"],"related_works":["https://openalex.org/W1990603712","https://openalex.org/W2250899144","https://openalex.org/W3016245616","https://openalex.org/W2152616541","https://openalex.org/W2182986921","https://openalex.org/W2487311051","https://openalex.org/W3146012968","https://openalex.org/W2165902556","https://openalex.org/W2147093015","https://openalex.org/W2156025712"],"abstract_inverted_index":{"Active":[0],"Shape":[1],"Models":[2],"are":[3,58,87],"a":[4,62],"powerful":[5],"and":[6,86],"well":[7],"known":[8],"method":[9],"to":[10,20,35,48,73,90],"perform":[11],"face":[12],"alignment.":[13],"In":[14],"some":[15],"applications":[16],"it":[17,45],"is":[18,46,111],"common":[19],"have":[21],"shape":[22,84],"information":[23],"available":[24],"beforehand,":[25],"such":[26],"as":[27],"previously":[28],"detected":[29],"landmarks.":[30],"Introducing":[31],"this":[32,50,100],"prior":[33],"knowledge":[34],"the":[36,54,67,78,82,91,108],"statistical":[37,55,92],"model":[38,56],"may":[39],"result":[40],"of":[41,107],"great":[42],"advantage":[43],"but":[44],"challenging":[47],"maintain":[49],"priors":[51],"unchanged":[52],"once":[53],"constraints":[57,85],"applied.":[59],"We":[60],"propose":[61],"new":[63],"weighted-regularized":[64],"projection":[65,101],"into":[66],"parameter":[68],"space":[69],"which":[70],"allows":[71],"us":[72],"obtain":[74],"shapes":[75],"that":[76],"at":[77],"same":[79],"time":[80],"fulfill":[81],"imposed":[83],"plausible":[88],"according":[89],"model.":[93],"The":[94],"performed":[95],"experiments":[96],"show":[97],"how":[98],"using":[99],"better":[102],"performance":[103],"than":[104],"competing":[105],"state":[106],"art":[109],"methods":[110],"achieved.":[112]},"counts_by_year":[{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}