{"id":"https://openalex.org/W2962681718","doi":"https://doi.org/10.1109/icip.2013.6738672","title":"Painting analysis using wavelets and probabilistic topic models","display_name":"Painting analysis using wavelets and probabilistic topic models","publication_year":2013,"publication_date":"2013-09-01","ids":{"openalex":"https://openalex.org/W2962681718","doi":"https://doi.org/10.1109/icip.2013.6738672","mag":"2962681718"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2013.6738672","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2013.6738672","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Image Processing","raw_type":"proceedings-article"},"type":"preprint","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/A5101522429","display_name":"Tong Wu","orcid":"https://orcid.org/0000-0001-9121-2495"},"institutions":[{"id":"https://openalex.org/I4210096112","display_name":"Rutgers Sexual and Reproductive Health and Rights","ror":"https://ror.org/00rcvgx40","country_code":"NL","type":"other","lineage":["https://openalex.org/I4210096112"]}],"countries":["NL"],"is_corresponding":false,"raw_author_name":"Tong Wu","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Rutgers University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Rutgers University","institution_ids":["https://openalex.org/I4210096112"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081847831","display_name":"Gungor Polatkan","orcid":null},"institutions":[{"id":"https://openalex.org/I113979032","display_name":"Twitter (United States)","ror":"https://ror.org/04wt43v05","country_code":"US","type":"company","lineage":["https://openalex.org/I113979032"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Gungor Polatkan","raw_affiliation_strings":["North Carolina Museum of Art","Twitter Inc"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"North Carolina Museum of Art","institution_ids":[]},{"raw_affiliation_string":"Twitter Inc","institution_ids":["https://openalex.org/I113979032"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039042181","display_name":"David Steel","orcid":"https://orcid.org/0000-0001-8734-3089"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"David Steel","raw_affiliation_strings":["North Carolina Museum of Art"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"North Carolina Museum of Art","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033801781","display_name":"William Brown","orcid":"https://orcid.org/0000-0001-9045-9787"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"William Brown","raw_affiliation_strings":["North Carolina Museum of Art"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"North Carolina Museum of Art","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108565885","display_name":"Ingrid Daubechies","orcid":null},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ingrid Daubechies","raw_affiliation_strings":["Department of Mathematics, Duke University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Duke University","institution_ids":["https://openalex.org/I170897317"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037795370","display_name":"Robert Calderbank","orcid":"https://orcid.org/0000-0003-2084-9717"},"institutions":[{"id":"https://openalex.org/I170897317","display_name":"Duke University","ror":"https://ror.org/00py81415","country_code":"US","type":"education","lineage":["https://openalex.org/I170897317"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Robert Calderbank","raw_affiliation_strings":["Department of Computer Science, Duke University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Duke University","institution_ids":["https://openalex.org/I170897317"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4701,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.66507582,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"3264","last_page":"3268"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12650","display_name":"Aesthetic Perception and Analysis","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T12650","display_name":"Aesthetic Perception and Analysis","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9818000197410583,"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/T13342","display_name":"Art History and Market Analysis","score":0.9212999939918518,"subfield":{"id":"https://openalex.org/subfields/1213","display_name":"Visual Arts and Performing Arts"},"field":{"id":"https://openalex.org/fields/12","display_name":"Arts and Humanities"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7163923978805542},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7150924205780029},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5945338010787964},{"id":"https://openalex.org/keywords/painting","display_name":"Painting","score":0.5603912472724915},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.5592378377914429},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5527106523513794},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5466747879981995},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.5385748744010925},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.5349534749984741},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.511504054069519},{"id":"https://openalex.org/keywords/hierarchical-clustering","display_name":"Hierarchical clustering","score":0.46053504943847656},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.45045074820518494},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.43906140327453613},{"id":"https://openalex.org/keywords/complex-wavelet-transform","display_name":"Complex wavelet transform","score":0.4162577688694},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.41278302669525146},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.34376630187034607},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.3168339729309082},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1257058084011078},{"id":"https://openalex.org/keywords/art","display_name":"Art","score":0.10586771368980408},{"id":"https://openalex.org/keywords/discrete-wavelet-transform","display_name":"Discrete wavelet transform","score":0.08805951476097107}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7163923978805542},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7150924205780029},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5945338010787964},{"id":"https://openalex.org/C205783811","wikidata":"https://www.wikidata.org/wiki/Q11629","display_name":"Painting","level":2,"score":0.5603912472724915},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.5592378377914429},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5527106523513794},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5466747879981995},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.5385748744010925},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.5349534749984741},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.511504054069519},{"id":"https://openalex.org/C92835128","wikidata":"https://www.wikidata.org/wiki/Q1277447","display_name":"Hierarchical clustering","level":3,"score":0.46053504943847656},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.45045074820518494},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.43906140327453613},{"id":"https://openalex.org/C2777885455","wikidata":"https://www.wikidata.org/wiki/Q5156615","display_name":"Complex wavelet transform","level":5,"score":0.4162577688694},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.41278302669525146},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.34376630187034607},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.3168339729309082},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1257058084011078},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.10586771368980408},{"id":"https://openalex.org/C46286280","wikidata":"https://www.wikidata.org/wiki/Q2414958","display_name":"Discrete wavelet transform","level":4,"score":0.08805951476097107},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2013.6738672","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2013.6738672","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.7099999785423279}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1522968858","https://openalex.org/W1880262756","https://openalex.org/W1987309482","https://openalex.org/W2018332268","https://openalex.org/W2107034620","https://openalex.org/W2108240927","https://openalex.org/W2132334273","https://openalex.org/W2134929491","https://openalex.org/W2140653665","https://openalex.org/W2164503390","https://openalex.org/W2187089797","https://openalex.org/W4237791300","https://openalex.org/W6631378878","https://openalex.org/W7075742223"],"related_works":["https://openalex.org/W2364370872","https://openalex.org/W2053269318","https://openalex.org/W2364423108","https://openalex.org/W2025614924","https://openalex.org/W2294335174","https://openalex.org/W2293526996","https://openalex.org/W2293120661","https://openalex.org/W2293966869","https://openalex.org/W2170667735","https://openalex.org/W2096126648"],"abstract_inverted_index":{"In":[0],"this":[1,88],"paper,":[2],"computer-based":[3],"techniques":[4],"for":[5,59],"stylistic":[6,49,72],"analysis":[7],"of":[8,16,74,85,111],"paintings":[9],"are":[10,27,57,78],"applied":[11],"to":[12,47,81,92,107],"the":[13,17,83,86],"five":[14],"panels":[15],"14th":[18],"century":[19],"Peruzzi":[20],"Altarpiece":[21],"by":[22,29],"Giotto":[23],"di":[24],"Bondone.":[25],"Features":[26],"extracted":[28],"combining":[30],"a":[31,37],"dual-tree":[32],"complex":[33],"wavelet":[34],"transform":[35],"with":[36],"hidden":[38],"Markov":[39],"tree":[40],"(HMT)":[41],"model.":[42],"Hierarchical":[43],"clustering":[44],"is":[45],"used":[46,80],"identify":[48],"keywords":[50],"in":[51,89],"image":[52],"patches,":[53],"and":[54],"keyword":[55],"frequencies":[56],"calculated":[58],"sub-images":[60],"that":[61,98],"each":[62],"contains":[63],"many":[64],"patches.":[65],"A":[66],"generative":[67],"hierarchical":[68],"Bayesian":[69],"model":[70],"learns":[71],"patterns":[73,77],"keywords;":[75],"these":[76],"then":[79],"characterize":[82],"styles":[84],"sub-images;":[87],"turn,":[90],"permits":[91],"discriminate":[93],"between":[94],"paintings.":[95],"Results":[96],"suggest":[97],"such":[99],"unsupervised":[100],"probabilistic":[101],"topic":[102],"models":[103],"can":[104],"be":[105],"useful":[106],"distill":[108],"characteristic":[109],"elements":[110],"style.":[112]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
