{"id":"https://openalex.org/W1503473358","doi":"https://doi.org/10.1109/fg.2015.7163094","title":"Spontaneous facial expression analysis based on temperature changes and head motions","display_name":"Spontaneous facial expression analysis based on temperature changes and head motions","publication_year":2015,"publication_date":"2015-05-01","ids":{"openalex":"https://openalex.org/W1503473358","doi":"https://doi.org/10.1109/fg.2015.7163094","mag":"1503473358"},"language":"en","primary_location":{"id":"doi:10.1109/fg.2015.7163094","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg.2015.7163094","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)","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/A5100346920","display_name":"Peng Liu","orcid":"https://orcid.org/0009-0003-1816-1670"},"institutions":[{"id":"https://openalex.org/I123946342","display_name":"Binghamton University","ror":"https://ror.org/008rmbt77","country_code":"US","type":"education","lineage":["https://openalex.org/I123946342"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Peng Liu","raw_affiliation_strings":["Department of Computer Science, State University of New York at Binghamton, Binghamton, USA","Dept. of Computer Science, State Univ. of New York at Binghamton, Binghamton, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, State University of New York at Binghamton, Binghamton, USA","institution_ids":["https://openalex.org/I123946342"]},{"raw_affiliation_string":"Dept. of Computer Science, State Univ. of New York at Binghamton, Binghamton, USA","institution_ids":["https://openalex.org/I123946342"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100411653","display_name":"Lijun Yin","orcid":"https://orcid.org/0000-0002-0343-7190"},"institutions":[{"id":"https://openalex.org/I123946342","display_name":"Binghamton University","ror":"https://ror.org/008rmbt77","country_code":"US","type":"education","lineage":["https://openalex.org/I123946342"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lijun Yin","raw_affiliation_strings":["Department of Computer Science, State University of New York at Binghamton, Binghamton, USA","Dept. of Computer Science, State Univ. of New York at Binghamton, Binghamton, USA"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, State University of New York at Binghamton, Binghamton, USA","institution_ids":["https://openalex.org/I123946342"]},{"raw_affiliation_string":"Dept. of Computer Science, State Univ. of New York at Binghamton, Binghamton, USA","institution_ids":["https://openalex.org/I123946342"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100346920"],"corresponding_institution_ids":["https://openalex.org/I123946342"],"apc_list":null,"apc_paid":null,"fwci":2.3932,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.92301765,"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":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9948999881744385,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9948999881744385,"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/T10667","display_name":"Emotion and Mood Recognition","score":0.9937999844551086,"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"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9905999898910522,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7899778485298157},{"id":"https://openalex.org/keywords/scale-invariant-feature-transform","display_name":"Scale-invariant feature transform","score":0.7423387169837952},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7265675067901611},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.717380166053772},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.6683435440063477},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.5533980131149292},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.5493058562278748},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5043445825576782},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4597092270851135},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.45241260528564453},{"id":"https://openalex.org/keywords/histogram-of-oriented-gradients","display_name":"Histogram of oriented gradients","score":0.43749701976776123},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4293716549873352},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.14675867557525635}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7899778485298157},{"id":"https://openalex.org/C61265191","wikidata":"https://www.wikidata.org/wiki/Q767770","display_name":"Scale-invariant feature transform","level":3,"score":0.7423387169837952},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7265675067901611},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.717380166053772},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.6683435440063477},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.5533980131149292},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.5493058562278748},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5043445825576782},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4597092270851135},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.45241260528564453},{"id":"https://openalex.org/C17426736","wikidata":"https://www.wikidata.org/wiki/Q419918","display_name":"Histogram of oriented gradients","level":4,"score":0.43749701976776123},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4293716549873352},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.14675867557525635},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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/fg.2015.7163094","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg.2015.7163094","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG)","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":29,"referenced_works":["https://openalex.org/W1542332827","https://openalex.org/W2018727909","https://openalex.org/W2019768939","https://openalex.org/W2034069713","https://openalex.org/W2042310585","https://openalex.org/W2047508432","https://openalex.org/W2063022220","https://openalex.org/W2076617402","https://openalex.org/W2090042335","https://openalex.org/W2090518410","https://openalex.org/W2095906285","https://openalex.org/W2096044434","https://openalex.org/W2104051600","https://openalex.org/W2104067190","https://openalex.org/W2105410756","https://openalex.org/W2105479305","https://openalex.org/W2106947945","https://openalex.org/W2110142955","https://openalex.org/W2124386111","https://openalex.org/W2128730107","https://openalex.org/W2142194269","https://openalex.org/W2157346641","https://openalex.org/W2161106546","https://openalex.org/W2162915993","https://openalex.org/W2533739470","https://openalex.org/W4251804053","https://openalex.org/W6662335928","https://openalex.org/W6676671045","https://openalex.org/W6679427232"],"related_works":["https://openalex.org/W1979041948","https://openalex.org/W2071599417","https://openalex.org/W2048716406","https://openalex.org/W1870444468","https://openalex.org/W2979608518","https://openalex.org/W1964725559","https://openalex.org/W2939132449","https://openalex.org/W1409560160","https://openalex.org/W3003960249","https://openalex.org/W2045053268"],"abstract_inverted_index":{"The":[0,57,147],"existing":[1],"approaches":[2,180],"to":[3,41,65,177],"automatic":[4],"emotion":[5,44],"analysis":[6],"rely":[7],"mostly":[8],"on":[9,70,96,112,164],"visible":[10],"spectrum":[11],"data,":[12],"and":[13,99,118,141],"very":[14],"few":[15],"works":[16],"have":[17],"been":[18],"reported":[19],"using":[20],"thermal":[21,36,50,92,166],"data":[22],"for":[23,155,181],"spontaneous":[24,43,183],"facial":[25,142,184],"expression":[26],"analysis.":[27],"In":[28],"this":[29],"paper,":[30],"we":[31,77],"present":[32],"a":[33,53,79,133,153],"novel":[34],"infra-red":[35],"video":[37,51,83,86,93,101,109,116,120,129,145],"descriptor":[38,154,174],"in":[39],"order":[40],"improve":[42],"recognition.":[45],"We":[46],"first":[47],"represent":[48],"each":[49,61,91,106,128],"as":[52,152,175],"series":[54],"of":[55,60,135,138,171],"clips.":[56],"face":[58],"regions":[59],"clip":[62,94,110],"are":[63,88,103,122],"warped":[64],"the":[66,136,158,169,172,178],"frontal":[67],"view":[68],"based":[69,95,111],"scale-invariant":[71],"feature":[72],"transform":[73],"(SIFT)":[74],"flow.":[75],"Meanwhile,":[76],"generate":[78],"corresponding":[80],"SIFT":[81,107,139],"flow":[82,108],"clip.":[84],"Thermal":[85,115],"cuboids":[87,102],"segmented":[89,104],"from":[90,105],"max":[97],"pooling":[98],"motion":[100,119],"average":[113],"pooling.":[114],"words":[117,121],"clustered":[123],"by":[124,132,157],"k-means":[125],"cluster.":[126],"Finally,":[127],"is":[130,150],"represented":[131],"histogram":[134,149],"bag":[137],"Flow":[140],"temperature":[143],"changes":[144],"words.":[146],"resulting":[148],"used":[151],"classification":[156],"support":[159],"vector":[160],"machine":[161],"(SVM).":[162],"Experiments":[163],"two":[165],"databases":[167],"show":[168],"advantage":[170],"new":[173],"compared":[176],"peer":[179],"classifying":[182],"expressions.":[185]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":5},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":4},{"year":2015,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}