{"id":"https://openalex.org/W2090374580","doi":"https://doi.org/10.1145/1924559.1924599","title":"Learning moods and emotions from color combinations","display_name":"Learning moods and emotions from color combinations","publication_year":2010,"publication_date":"2010-12-12","ids":{"openalex":"https://openalex.org/W2090374580","doi":"https://doi.org/10.1145/1924559.1924599","mag":"2090374580"},"language":"en","primary_location":{"id":"doi:10.1145/1924559.1924599","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1924559.1924599","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing","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/A5109475590","display_name":"Gabriela Csurka","orcid":null},"institutions":[{"id":"https://openalex.org/I33976269","display_name":"Xerox (France)","ror":"https://ror.org/033q0mv79","country_code":"FR","type":"company","lineage":["https://openalex.org/I33976269","https://openalex.org/I4210132870"]}],"countries":["FR"],"is_corresponding":true,"raw_author_name":"Gabriela Csurka","raw_affiliation_strings":["XRCE-Xerox Research Centre, Europe, Meylan, France"],"affiliations":[{"raw_affiliation_string":"XRCE-Xerox Research Centre, Europe, Meylan, France","institution_ids":["https://openalex.org/I33976269"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046392298","display_name":"Sandra Skaff","orcid":null},"institutions":[{"id":"https://openalex.org/I33976269","display_name":"Xerox (France)","ror":"https://ror.org/033q0mv79","country_code":"FR","type":"company","lineage":["https://openalex.org/I33976269","https://openalex.org/I4210132870"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Sandra Skaff","raw_affiliation_strings":["XRCE-Xerox Research Centre, Europe, Meylan, France"],"affiliations":[{"raw_affiliation_string":"XRCE-Xerox Research Centre, Europe, Meylan, France","institution_ids":["https://openalex.org/I33976269"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018191127","display_name":"Luca Marchesotti","orcid":null},"institutions":[{"id":"https://openalex.org/I33976269","display_name":"Xerox (France)","ror":"https://ror.org/033q0mv79","country_code":"FR","type":"company","lineage":["https://openalex.org/I33976269","https://openalex.org/I4210132870"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Luca Marchesotti","raw_affiliation_strings":["XRCE-Xerox Research Centre, Europe, Meylan, France"],"affiliations":[{"raw_affiliation_string":"XRCE-Xerox Research Centre, Europe, Meylan, France","institution_ids":["https://openalex.org/I33976269"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078473813","display_name":"Craig Saunders","orcid":null},"institutions":[{"id":"https://openalex.org/I33976269","display_name":"Xerox (France)","ror":"https://ror.org/033q0mv79","country_code":"FR","type":"company","lineage":["https://openalex.org/I33976269","https://openalex.org/I4210132870"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"Craig Saunders","raw_affiliation_strings":["XRCE-Xerox Research Centre, Europe, Meylan, France"],"affiliations":[{"raw_affiliation_string":"XRCE-Xerox Research Centre, Europe, Meylan, France","institution_ids":["https://openalex.org/I33976269"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5109475590"],"corresponding_institution_ids":["https://openalex.org/I33976269"],"apc_list":null,"apc_paid":null,"fwci":4.9316,"has_fulltext":false,"cited_by_count":40,"citation_normalized_percentile":{"value":0.94577657,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"298","last_page":"305"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12496","display_name":"Color perception and design","score":0.9873999953269958,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12496","display_name":"Color perception and design","score":0.9873999953269958,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11666","display_name":"Color Science and Applications","score":0.9763000011444092,"subfield":{"id":"https://openalex.org/subfields/3107","display_name":"Atomic and Molecular Physics, and Optics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10824","display_name":"Image Retrieval and Classification Techniques","score":0.9747999906539917,"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/computer-science","display_name":"Computer science","score":0.6217311024665833},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40887361764907837},{"id":"https://openalex.org/keywords/cognitive-psychology","display_name":"Cognitive psychology","score":0.40500926971435547},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.3651407063007355}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6217311024665833},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40887361764907837},{"id":"https://openalex.org/C180747234","wikidata":"https://www.wikidata.org/wiki/Q23373","display_name":"Cognitive psychology","level":1,"score":0.40500926971435547},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.3651407063007355}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/1924559.1924599","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1924559.1924599","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G524208518","display_name":null,"funder_award_id":"ANR-07-MDCO-009-02","funder_id":"https://openalex.org/F4320320883","funder_display_name":"Agence Nationale de la Recherche"}],"funders":[{"id":"https://openalex.org/F4320320883","display_name":"Agence Nationale de la Recherche","ror":"https://ror.org/00rbzpz17"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W39969610","https://openalex.org/W280632315","https://openalex.org/W394379334","https://openalex.org/W1495887101","https://openalex.org/W1592774159","https://openalex.org/W1625255723","https://openalex.org/W1974689608","https://openalex.org/W1989665241","https://openalex.org/W2001700175","https://openalex.org/W2059234575","https://openalex.org/W2125005457","https://openalex.org/W2129112648","https://openalex.org/W2160530465","https://openalex.org/W2162349892","https://openalex.org/W2166473218","https://openalex.org/W2296168388","https://openalex.org/W2801844694","https://openalex.org/W6613689849","https://openalex.org/W6636494156","https://openalex.org/W6989518224"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2085642841","https://openalex.org/W2065074698","https://openalex.org/W2093287941","https://openalex.org/W2128524530","https://openalex.org/W2042940951","https://openalex.org/W2118417921","https://openalex.org/W1985950550","https://openalex.org/W2050944115"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,36,53,104],"tackle":[4],"the":[5,73,98,117],"problem":[6],"of":[7,10,39,79,101,119],"associating":[8],"combinations":[9,38],"colors":[11,40],"to":[12,30],"abstract":[13,108],"categories":[14,109],"(e.g.":[15],"capricious,":[16],"classic,":[17],"cool,":[18],"delicate,":[19],"etc.).":[20],"It":[21],"is":[22,72],"evident":[23],"that":[24,66],"such":[25],"concepts":[26],"would":[27],"be":[28,114],"difficult":[29],"distinguish":[31],"using":[32,57],"single":[33],"colors,":[34],"therefore":[35],"consider":[37],"or":[41],"color":[42,50,111,120],"palettes.":[43],"We":[44,86],"leverage":[45],"two":[46],"novel":[47],"databases":[48],"for":[49,91],"palettes":[51,112],"and":[52,59,123],"learn":[54],"categorization":[55],"models":[56],"low":[58],"high":[60],"level":[61],"descriptors.":[62],"Preliminary":[63],"results":[64],"show":[65],"Fisher":[67],"representation":[68],"based":[69],"on":[70,110],"GMMs":[71],"most":[74],"rewarding":[75],"strategy":[76],"in":[77,116],"terms":[78],"classification":[80],"performance":[81],"over":[82],"a":[83,89],"baseline":[84],"model.":[85],"also":[87],"suggest":[88],"process":[90],"cleaning":[92],"weakly":[93],"annotated":[94],"data,":[95],"whilst":[96],"preserving":[97],"visual":[99],"coherence":[100],"categories.":[102],"Finally,":[103],"demonstrate":[105],"how":[106],"learning":[107],"can":[113],"used":[115],"application":[118],"transfer,":[121],"personalization":[122],"image":[124],"re-ranking.":[125]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
