{"id":"https://openalex.org/W2110202198","doi":"https://doi.org/10.1109/ijcnn.2008.4634011","title":"A human face recognition approach based on spatially weighted pseudo-Zernike moments","display_name":"A human face recognition approach based on spatially weighted pseudo-Zernike moments","publication_year":2008,"publication_date":"2008-06-01","ids":{"openalex":"https://openalex.org/W2110202198","doi":"https://doi.org/10.1109/ijcnn.2008.4634011","mag":"2110202198"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2008.4634011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2008.4634011","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)","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/A5021383239","display_name":"Rongbing Huang","orcid":"https://orcid.org/0000-0002-3962-2881"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Rongbing Huang","raw_affiliation_strings":["College of Electronic and Information Engineering, South China Univ. of Tech, Guangzhou, China","Coll. of Electron. & Inf. Eng., South China Univ. of Tech., Guangzhou"],"affiliations":[{"raw_affiliation_string":"College of Electronic and Information Engineering, South China Univ. of Tech, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"Coll. of Electron. & Inf. Eng., South China Univ. of Tech., Guangzhou","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100694105","display_name":"Minghui Du","orcid":"https://orcid.org/0000-0001-7288-8174"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minghui Du","raw_affiliation_strings":["Electrical Engineering Department, South China Univ. of Tech, Guangzhou, China","Electr. Eng. Dept., South China Univ. of Technol., Guangzhou"],"affiliations":[{"raw_affiliation_string":"Electrical Engineering Department, South China Univ. of Tech, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"Electr. Eng. Dept., South China Univ. of Technol., Guangzhou","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042839786","display_name":"Dexin Me","orcid":null},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dexin Me","raw_affiliation_strings":["South China University of Technology, Guangzhou, Guangdong, CN","Coll. of Electron. & Inf. Eng., South China Univ. of Tech., Guangzhou"],"affiliations":[{"raw_affiliation_string":"South China University of Technology, Guangzhou, Guangdong, CN","institution_ids":["https://openalex.org/I90610280"]},{"raw_affiliation_string":"Coll. of Electron. & Inf. Eng., South China Univ. of Tech., Guangzhou","institution_ids":["https://openalex.org/I90610280"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5021383239"],"corresponding_institution_ids":["https://openalex.org/I90610280"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.12211946,"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":"1604","last_page":"1608"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9983999729156494,"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/T10057","display_name":"Face and Expression Recognition","score":0.9983999729156494,"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":0.9962000250816345,"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/T13890","display_name":"Remote Sensing and Land Use","score":0.9832000136375427,"subfield":{"id":"https://openalex.org/subfields/1902","display_name":"Atmospheric Science"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/zernike-polynomials","display_name":"Zernike polynomials","score":0.9864989519119263},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7788189053535461},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.7649555802345276},{"id":"https://openalex.org/keywords/facial-recognition-system","display_name":"Facial recognition system","score":0.7483041286468506},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.7202274203300476},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5966484546661377},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5546509027481079},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5240324139595032},{"id":"https://openalex.org/keywords/k-nearest-neighbors-algorithm","display_name":"k-nearest neighbors algorithm","score":0.45772653818130493},{"id":"https://openalex.org/keywords/velocity-moments","display_name":"Velocity Moments","score":0.43924039602279663},{"id":"https://openalex.org/keywords/moment","display_name":"Moment (physics)","score":0.4302656352519989},{"id":"https://openalex.org/keywords/face-detection","display_name":"Face detection","score":0.4177214205265045},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.39482584595680237},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.11788761615753174},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.0847335159778595}],"concepts":[{"id":"https://openalex.org/C92423082","wikidata":"https://www.wikidata.org/wiki/Q132146","display_name":"Zernike polynomials","level":3,"score":0.9864989519119263},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7788189053535461},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.7649555802345276},{"id":"https://openalex.org/C31510193","wikidata":"https://www.wikidata.org/wiki/Q1192553","display_name":"Facial recognition system","level":3,"score":0.7483041286468506},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.7202274203300476},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5966484546661377},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5546509027481079},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5240324139595032},{"id":"https://openalex.org/C113238511","wikidata":"https://www.wikidata.org/wiki/Q1071612","display_name":"k-nearest neighbors algorithm","level":2,"score":0.45772653818130493},{"id":"https://openalex.org/C149539972","wikidata":"https://www.wikidata.org/wiki/Q7919290","display_name":"Velocity Moments","level":4,"score":0.43924039602279663},{"id":"https://openalex.org/C179254644","wikidata":"https://www.wikidata.org/wiki/Q13222844","display_name":"Moment (physics)","level":2,"score":0.4302656352519989},{"id":"https://openalex.org/C4641261","wikidata":"https://www.wikidata.org/wiki/Q11681085","display_name":"Face detection","level":4,"score":0.4177214205265045},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39482584595680237},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.11788761615753174},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0847335159778595},{"id":"https://openalex.org/C165699331","wikidata":"https://www.wikidata.org/wiki/Q461533","display_name":"Wavefront","level":2,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/C36289849","wikidata":"https://www.wikidata.org/wiki/Q34749","display_name":"Social science","level":1,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn.2008.4634011","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2008.4634011","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5799999833106995,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1596564698","https://openalex.org/W1989702938","https://openalex.org/W1995230685","https://openalex.org/W2040179990","https://openalex.org/W2045010718","https://openalex.org/W2051757397","https://openalex.org/W2061403264","https://openalex.org/W2099205439","https://openalex.org/W2102377326","https://openalex.org/W2114150335","https://openalex.org/W2115689562","https://openalex.org/W2121601095","https://openalex.org/W2146880335","https://openalex.org/W2163965432","https://openalex.org/W2230881546","https://openalex.org/W2728930222","https://openalex.org/W3215887389"],"related_works":["https://openalex.org/W2372021815","https://openalex.org/W2360964508","https://openalex.org/W2122970665","https://openalex.org/W2086936614","https://openalex.org/W2168501771","https://openalex.org/W1596812724","https://openalex.org/W4321260167","https://openalex.org/W2765956955","https://openalex.org/W134722258","https://openalex.org/W2169751066"],"abstract_inverted_index":{"A":[0],"new":[1,33],"modified":[2,34],"pseudo-Zernike":[3,9,35],"moments":[4],"feature,":[5],"namely,":[6],"ldquospatial":[7],"weighted":[8,38],"momentsrdquo":[10],"(SWPZM)":[11],"is":[12,37],"proposed":[13],"for":[14,29,67],"face":[15,30,68,80],"recognition":[16,91],"in":[17],"this":[18],"paper.":[19],"Since":[20],"different":[21,26],"facial":[22],"region":[23],"plays":[24],"a":[25,40],"important":[27,55],"role":[28],"recognition,":[31],"the":[32,45,49,53,59,74,94],"feature":[36],"with":[39,93],"weight":[41],"function":[42],"derived":[43],"from":[44],"spatial":[46],"information":[47],"of":[48],"human":[50],"face;":[51],"hence":[52],"most":[54],"regions":[56,64],"such":[57],"as":[58],"eyes,":[60],"nose,":[61],"and":[62,77,89,98],"mouth":[63],"are":[65],"intensified":[66],"discrimination.":[69],"Experimental":[70],"results":[71],"based":[72],"on":[73],"AT&T/ORL,":[75],"Yale,":[76],"their":[78],"combined":[79],"database":[81],"show":[82],"that":[83],"SWPZM":[84],"can":[85],"obtain":[86],"95.7%,":[87],"92.3%,":[88],"92.5%":[90],"rates":[92],"nearest":[95],"neighbor":[96],"rule":[97],"have":[99],"better":[100],"identification":[101],"power":[102],"than":[103],"other":[104],"methods.":[105]},"counts_by_year":[{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}