{"id":"https://openalex.org/W2609071044","doi":"https://doi.org/10.1109/icpr.2016.7899607","title":"Bi-modal regression for Apparent Personality trait Recognition","display_name":"Bi-modal regression for Apparent Personality trait Recognition","publication_year":2016,"publication_date":"2016-12-01","ids":{"openalex":"https://openalex.org/W2609071044","doi":"https://doi.org/10.1109/icpr.2016.7899607","mag":"2609071044"},"language":"en","primary_location":{"id":"doi:10.1109/icpr.2016.7899607","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7899607","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","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/A5002861710","display_name":"Nishant Rai","orcid":"https://orcid.org/0009-0000-5784-3306"},"institutions":[{"id":"https://openalex.org/I94234084","display_name":"Indian Institute of Technology Kanpur","ror":"https://ror.org/05pjsgx75","country_code":"IN","type":"education","lineage":["https://openalex.org/I94234084"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Nishant Rai","raw_affiliation_strings":["Department of Computer Science and Engineering, Indian Institute of Technology, Kanpur, Uttar Pradesh, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Indian Institute of Technology, Kanpur, Uttar Pradesh, India","institution_ids":["https://openalex.org/I94234084"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5002861710"],"corresponding_institution_ids":["https://openalex.org/I94234084"],"apc_list":null,"apc_paid":null,"fwci":0.334,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.69481598,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"55","last_page":"60"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","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/T11448","display_name":"Face recognition and analysis","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/T11040","display_name":"Personality Traits and Psychology","score":0.9907000064849854,"subfield":{"id":"https://openalex.org/subfields/3203","display_name":"Clinical 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/T11118","display_name":"Evolutionary Psychology and Human Behavior","score":0.9861999750137329,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7220545411109924},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6157561540603638},{"id":"https://openalex.org/keywords/trait","display_name":"Trait","score":0.5908490419387817},{"id":"https://openalex.org/keywords/big-five-personality-traits","display_name":"Big Five personality traits","score":0.5862337350845337},{"id":"https://openalex.org/keywords/regression","display_name":"Regression","score":0.5470479726791382},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.46232110261917114},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4500371813774109},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.4491640031337738},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.43155449628829956},{"id":"https://openalex.org/keywords/personality","display_name":"Personality","score":0.42251789569854736},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4178128242492676},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3876056671142578},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.12357926368713379},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.11876711249351501},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.10089901089668274}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7220545411109924},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6157561540603638},{"id":"https://openalex.org/C106934330","wikidata":"https://www.wikidata.org/wiki/Q1971873","display_name":"Trait","level":2,"score":0.5908490419387817},{"id":"https://openalex.org/C2865642","wikidata":"https://www.wikidata.org/wiki/Q378132","display_name":"Big Five personality traits","level":3,"score":0.5862337350845337},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.5470479726791382},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.46232110261917114},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4500371813774109},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.4491640031337738},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.43155449628829956},{"id":"https://openalex.org/C187288502","wikidata":"https://www.wikidata.org/wiki/Q641118","display_name":"Personality","level":2,"score":0.42251789569854736},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4178128242492676},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3876056671142578},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.12357926368713379},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.11876711249351501},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.10089901089668274},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"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/icpr.2016.7899607","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icpr.2016.7899607","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 23rd International Conference on Pattern Recognition (ICPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W15066456","https://openalex.org/W147964346","https://openalex.org/W1480583224","https://openalex.org/W1529410181","https://openalex.org/W1686810756","https://openalex.org/W2086815031","https://openalex.org/W2087681821","https://openalex.org/W2097998348","https://openalex.org/W2099465598","https://openalex.org/W2122481149","https://openalex.org/W2134951257","https://openalex.org/W2153531094","https://openalex.org/W2165312226","https://openalex.org/W2168432963","https://openalex.org/W2194775991","https://openalex.org/W2411161539","https://openalex.org/W2576686289","https://openalex.org/W2609984075","https://openalex.org/W2963542991","https://openalex.org/W6600593648","https://openalex.org/W6605980550","https://openalex.org/W6628771001","https://openalex.org/W6674385629","https://openalex.org/W6678249123","https://openalex.org/W6732508302"],"related_works":["https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W2352448290","https://openalex.org/W2380820513","https://openalex.org/W2913146933","https://openalex.org/W4301143707","https://openalex.org/W3125957671","https://openalex.org/W2952745240","https://openalex.org/W2898389145","https://openalex.org/W1966488223"],"abstract_inverted_index":{"The":[0,50,173],"task":[1],"of":[2,16,25,37,59,121,134,180],"the":[3,23,35,94,103,161,184],"ChaLearn":[4],"Apparent":[5],"Personality":[6],"Analysis:":[7],"First":[8],"Impressions":[9],"Challenge":[10],"is":[11,31],"to":[12,167],"rate/quantify":[13],"personality":[14,26],"traits":[15,40,75,117],"users":[17],"in":[18,93,158],"short":[19,29],"video":[20],"sequences.":[21],"Although":[22],"validity":[24],"judgments":[27],"from":[28,64,102,170],"interactions":[30],"questionable,":[32],"studies":[33],"show":[34],"possibility":[36],"predicting":[38,74],"attributed":[39],"(First":[41],"Impressions)":[42],"using":[43,107],"facial":[44],"[15]":[45],"and":[46,105,123],"acoustic":[47,108],"[13]":[48],"features.":[49,109],"challenge":[51,186],"introduces":[52],"a":[53,119,155],"newly":[54],"constructed":[55],"dataset":[56],"which":[57,87],"consists":[58],"manually":[60],"annotated":[61],"videos":[62,135],"collected":[63],"YouTube.":[65],"In":[66],"this":[67],"paper,":[68],"we":[69],"present":[70],"our":[71],"approach":[72,114],"for":[73,115,129,146],"by":[76],"combining":[77],"multiple":[78],"modality":[79],"specific":[80],"models.":[81],"Our":[82],"models":[83,106],"include":[84],"Deep":[85],"Networks":[86,97],"focus":[88],"on":[89,99,137],"leveraging":[90],"visual":[91],"information":[92,101,169],"given":[95],"faces,":[96],"focusing":[98],"supplementary":[100],"background":[104],"We":[110,126,140,150],"also":[111,141],"discuss":[112],"another":[113],"modeling":[116],"as":[118],"combination":[120],"global":[122],"trait-specific":[124],"variables.":[125],"explore":[127],"methods":[128,145],"extracting":[130],"fixed":[131],"length":[132],"descriptors":[133],"based":[136],"frame-level":[138],"predictions.":[139,149],"experiment":[142],"with":[143],"various":[144],"fusing":[147],"model":[148],"observe":[151],"that":[152],"fusion":[153],"achieves":[154,176],"considerable":[156],"gain":[157,179],"accuracy":[159,178],"over":[160],"best":[162],"stand-alone":[163],"model,":[164],"possibly":[165],"due":[166],"utilizing":[168],"all":[171],"modalities.":[172],"proposed":[174],"method":[175],"an":[177],"approximately":[181],"18%":[182],"above":[183],"provided":[185],"baseline.":[187]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":1},{"year":2019,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}