{"id":"https://openalex.org/W2982484396","doi":"https://doi.org/10.1109/lifetech.2019.8884060","title":"Estimation of Emotions Evoked by Images Based on Multiple Gaze-based CNN Features","display_name":"Estimation of Emotions Evoked by Images Based on Multiple Gaze-based CNN Features","publication_year":2019,"publication_date":"2019-03-01","ids":{"openalex":"https://openalex.org/W2982484396","doi":"https://doi.org/10.1109/lifetech.2019.8884060","mag":"2982484396"},"language":"en","primary_location":{"id":"doi:10.1109/lifetech.2019.8884060","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lifetech.2019.8884060","pdf_url":null,"source":{"id":"https://openalex.org/S4306498475","display_name":"2019 IEEE 1st Global Conference on Life Sciences and Technologies (LifeTech)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 1st Global Conference on Life Sciences and Technologies (LifeTech)","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/A5023205428","display_name":"Taiga Matsui","orcid":null},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Taiga Matsui","raw_affiliation_strings":["Hokkaido University, Sapporo, Japan"],"affiliations":[{"raw_affiliation_string":"Hokkaido University, Sapporo, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103129627","display_name":"Naoki Saito","orcid":"https://orcid.org/0000-0001-7611-2461"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Naoki Saito","raw_affiliation_strings":["Hokkaido University, Sapporo, Japan"],"affiliations":[{"raw_affiliation_string":"Hokkaido University, Sapporo, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009032240","display_name":"Takahiro Ogawa","orcid":"https://orcid.org/0000-0001-5332-8112"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takahiro Ogawa","raw_affiliation_strings":["Hokkaido University, Sapporo, Japan"],"affiliations":[{"raw_affiliation_string":"Hokkaido University, Sapporo, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017174031","display_name":"Satoshi Asamizu","orcid":null},"institutions":[{"id":"https://openalex.org/I2800341562","display_name":"Kushiro Junior College","ror":"https://ror.org/00a7kn731","country_code":"JP","type":"education","lineage":["https://openalex.org/I2800341562"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Satoshi Asamizu","raw_affiliation_strings":["Kushiro College, Kushiro, Japan"],"affiliations":[{"raw_affiliation_string":"Kushiro College, Kushiro, Japan","institution_ids":["https://openalex.org/I2800341562"]}]},{"author_position":"last","author":{"id":null,"display_name":"Miki Haseyama","orcid":null},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Miki Haseyama","raw_affiliation_strings":["Hokkaido University, Sapporo, Japan"],"affiliations":[{"raw_affiliation_string":"Hokkaido University, Sapporo, Japan","institution_ids":["https://openalex.org/I205349734"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5023205428"],"corresponding_institution_ids":["https://openalex.org/I205349734"],"apc_list":null,"apc_paid":null,"fwci":0.3788,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.50497512,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":93},"biblio":{"volume":"321","issue":null,"first_page":"194","last_page":"195"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.994700014591217,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9927999973297119,"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/gaze","display_name":"Gaze","score":0.8032481074333191},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7638835906982422},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7606450915336609},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7513145208358765},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7094554901123047},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5675708055496216},{"id":"https://openalex.org/keywords/canonical-correlation","display_name":"Canonical correlation","score":0.5642253160476685},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.5163089632987976},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49852514266967773},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.43087124824523926}],"concepts":[{"id":"https://openalex.org/C2779916870","wikidata":"https://www.wikidata.org/wiki/Q14467155","display_name":"Gaze","level":2,"score":0.8032481074333191},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7638835906982422},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7606450915336609},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7513145208358765},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7094554901123047},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5675708055496216},{"id":"https://openalex.org/C153874254","wikidata":"https://www.wikidata.org/wiki/Q115542","display_name":"Canonical correlation","level":2,"score":0.5642253160476685},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.5163089632987976},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49852514266967773},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.43087124824523926},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lifetech.2019.8884060","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lifetech.2019.8884060","pdf_url":null,"source":{"id":"https://openalex.org/S4306498475","display_name":"2019 IEEE 1st Global Conference on Life Sciences and Technologies (LifeTech)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE 1st Global Conference on Life Sciences and Technologies (LifeTech)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.800000011920929}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":8,"referenced_works":["https://openalex.org/W108816716","https://openalex.org/W2003856922","https://openalex.org/W2119821739","https://openalex.org/W2183341477","https://openalex.org/W2407797316","https://openalex.org/W2798322248","https://openalex.org/W4239510810","https://openalex.org/W6604368413"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W1880689012","https://openalex.org/W2093195256","https://openalex.org/W2154562908","https://openalex.org/W3131016912"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,34],"method":[4,24,41],"for":[5],"estimating":[6],"emotions":[7],"evoked":[8],"by":[9,53,67,84],"watching":[10],"images":[11],"based":[12],"on":[13],"multiple":[14,26,30,69,87],"visual":[15,27,46,76],"features":[16,28,47],"considering":[17],"relationship":[18],"with":[19,50],"gaze":[20,51],"information.":[21],"The":[22,61],"proposed":[23,40],"obtains":[25],"from":[29,73],"middle":[31],"layers":[32],"of":[33,96],"Convolutional":[35],"Neural":[36],"Network.":[37],"Then":[38],"the":[39],"newly":[42],"derives":[43],"their":[44],"gaze-based":[45,75],"maximizing":[48],"correlation":[49],"information":[52],"using":[54,85],"Discriminative":[55],"Locality":[56],"Preserving":[57],"Canonical":[58],"Correlation":[59],"Analysis.":[60],"final":[62],"estimation":[63,70,81,88],"result":[64],"is":[65],"calculated":[66],"integrating":[68],"results":[71,89],"obtained":[72],"these":[74],"features.":[77],"Consequently,":[78],"successful":[79],"emotion":[80],"becomes":[82],"feasible":[83],"such":[86],"which":[90],"correspond":[91],"to":[92],"different":[93],"semantic":[94],"levels":[95],"target":[97],"images.":[98]},"counts_by_year":[{"year":2021,"cited_by_count":1}],"updated_date":"2026-03-25T23:56:10.502304","created_date":"2025-10-10T00:00:00"}
