{"id":"https://openalex.org/W2124919505","doi":"https://doi.org/10.1109/iccv.2009.5459255","title":"Directional statistics BRDF model","display_name":"Directional statistics BRDF model","publication_year":2009,"publication_date":"2009-09-01","ids":{"openalex":"https://openalex.org/W2124919505","doi":"https://doi.org/10.1109/iccv.2009.5459255","mag":"2124919505"},"language":"en","primary_location":{"id":"doi:10.1109/iccv.2009.5459255","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2009.5459255","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE 12th International Conference on Computer Vision","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/A5034253077","display_name":"Ko Nishino","orcid":"https://orcid.org/0000-0002-3534-3447"},"institutions":[{"id":"https://openalex.org/I72816309","display_name":"Drexel University","ror":"https://ror.org/04bdffz58","country_code":"US","type":"education","lineage":["https://openalex.org/I72816309"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"K Nishino","raw_affiliation_strings":["Department of Computer Science, Drexel University, Philadelphia, PA, USA","Dept. of Comput. Sci., Drexel Univ., Philadelphia, PA, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Drexel University, Philadelphia, PA, USA","institution_ids":["https://openalex.org/I72816309"]},{"raw_affiliation_string":"Dept. of Comput. Sci., Drexel Univ., Philadelphia, PA, USA","institution_ids":["https://openalex.org/I72816309"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5034253077"],"corresponding_institution_ids":["https://openalex.org/I72816309"],"apc_list":null,"apc_paid":null,"fwci":2.2964,"has_fulltext":false,"cited_by_count":42,"citation_normalized_percentile":{"value":0.8979688,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"476","last_page":"483"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9955999851226807,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9955999851226807,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.9950000047683716,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/T10688","display_name":"Image and Signal Denoising Methods","score":0.9941999912261963,"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/bidirectional-reflectance-distribution-function","display_name":"Bidirectional reflectance distribution function","score":0.9708212614059448},{"id":"https://openalex.org/keywords/isotropy","display_name":"Isotropy","score":0.608723521232605},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.5961750745773315},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5644155144691467},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5487488508224487},{"id":"https://openalex.org/keywords/parametric-model","display_name":"Parametric model","score":0.4999196529388428},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.4798559546470642},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.43271175026893616},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4087132215499878},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.340097039937973},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.26724082231521606},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.21672934293746948},{"id":"https://openalex.org/keywords/reflectivity","display_name":"Reflectivity","score":0.1568755805492401},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.11893534660339355},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10852491855621338}],"concepts":[{"id":"https://openalex.org/C151596937","wikidata":"https://www.wikidata.org/wiki/Q856980","display_name":"Bidirectional reflectance distribution function","level":3,"score":0.9708212614059448},{"id":"https://openalex.org/C184050105","wikidata":"https://www.wikidata.org/wiki/Q273163","display_name":"Isotropy","level":2,"score":0.608723521232605},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.5961750745773315},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5644155144691467},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5487488508224487},{"id":"https://openalex.org/C24574437","wikidata":"https://www.wikidata.org/wiki/Q7135228","display_name":"Parametric model","level":3,"score":0.4999196529388428},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.4798559546470642},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.43271175026893616},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4087132215499878},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.340097039937973},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.26724082231521606},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.21672934293746948},{"id":"https://openalex.org/C108597893","wikidata":"https://www.wikidata.org/wiki/Q663650","display_name":"Reflectivity","level":2,"score":0.1568755805492401},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.11893534660339355},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10852491855621338},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv.2009.5459255","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv.2009.5459255","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2009 IEEE 12th International Conference on Computer Vision","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.151.5918","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.151.5918","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.drexel.edu/~kon/publication/KNishino_ICCV09_preprint.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.188.8273","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.188.8273","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.drexel.edu/%7Ekon/publication/KNishino_ICCV09.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1494645067","https://openalex.org/W1564611446","https://openalex.org/W1663973292","https://openalex.org/W2001141328","https://openalex.org/W2002699656","https://openalex.org/W2040692352","https://openalex.org/W2066303290","https://openalex.org/W2072135195","https://openalex.org/W2092752047","https://openalex.org/W2095800081","https://openalex.org/W2099478163","https://openalex.org/W2104587129","https://openalex.org/W2105933175","https://openalex.org/W2122585444","https://openalex.org/W2129074579","https://openalex.org/W2134205233","https://openalex.org/W2135861823","https://openalex.org/W2144736368","https://openalex.org/W2149015394","https://openalex.org/W2150810898","https://openalex.org/W2160203169","https://openalex.org/W2161446118","https://openalex.org/W2235136907","https://openalex.org/W2292718758","https://openalex.org/W2313299119","https://openalex.org/W2801179766","https://openalex.org/W2914531995","https://openalex.org/W3005895305","https://openalex.org/W4212863985","https://openalex.org/W4232290346","https://openalex.org/W4294489724","https://openalex.org/W4300223101","https://openalex.org/W6651090538","https://openalex.org/W6682038435","https://openalex.org/W6696704304","https://openalex.org/W6759793505"],"related_works":["https://openalex.org/W1996671438","https://openalex.org/W2002739602","https://openalex.org/W1968042686","https://openalex.org/W2897881820","https://openalex.org/W2345647014","https://openalex.org/W2201192772","https://openalex.org/W2161960196","https://openalex.org/W3136891595","https://openalex.org/W1964819397","https://openalex.org/W2111813998"],"abstract_inverted_index":{"We":[0,44,94,120,138],"introduce":[1],"a":[2,11,19,31,37,41,46,67,81,115],"novel":[3,47,72,145],"parametric":[4],"BRDF":[5,32,65,75,146],"model":[6,62,76,98,126,147],"that":[7,30,96,124],"can":[8],"accurately":[9],"encode":[10],"wide":[12],"variety":[13],"of":[14,22,69,92,103,143,161],"real-world":[15,104],"isotropic":[16,64,105,162],"BRDFs":[17,106],"with":[18,66,107,114,130,134],"small":[20],"number":[21,91],"parameters.":[23],"The":[24,71],"key":[25],"observation":[26],"we":[27,52],"make":[28],"is":[29],"may":[33],"be":[34],"viewed":[35],"as":[36,55],"statistical":[38],"distribution":[39],"on":[40],"unit":[42],"hemisphere.":[43],"derive":[45,80],"directional":[48,73],"statistics":[49,74],"distribution,":[50,60],"which":[51],"refer":[53],"to":[54,79,110],"the":[56,90,97,100,125,141,144,159],"hemispherical":[57],"exponential":[58],"power":[59],"and":[61,156],"an":[63],"mixture":[68],"it.":[70],"allows":[77],"us":[78],"canonical":[82],"probabilistic":[83],"method":[84],"for":[85,152,157],"estimating":[86],"its":[87,150],"parameters":[88],"including":[89],"components.":[93],"show":[95,123],"captures":[99],"full":[101],"spectrum":[102],"accuracy":[108,129],"comparable":[109],"non-parametric":[111,136],"models":[112],"but":[113],"much":[116],"more":[117],"compact":[118],"representation.":[119],"also":[121],"experimentally":[122],"achieves":[127],"better":[128],"less":[131],"measurements":[132],"compared":[133],"such":[135],"models.":[137],"further":[139],"demonstrate":[140],"advantages":[142],"by":[148],"showing":[149],"use":[151],"reflection":[153],"component":[154],"separation":[155],"exploring":[158],"space":[160],"BRDFs.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":5},{"year":2014,"cited_by_count":3},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":4}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}