{"id":"https://openalex.org/W2787182113","doi":"https://doi.org/10.1109/btas.2017.8272721","title":"Deep learning with time-frequency representation for pulse estimation from facial videos","display_name":"Deep learning with time-frequency representation for pulse estimation from facial videos","publication_year":2017,"publication_date":"2017-10-01","ids":{"openalex":"https://openalex.org/W2787182113","doi":"https://doi.org/10.1109/btas.2017.8272721","mag":"2787182113"},"language":"en","primary_location":{"id":"doi:10.1109/btas.2017.8272721","is_oa":false,"landing_page_url":"https://doi.org/10.1109/btas.2017.8272721","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Joint Conference on Biometrics (IJCB)","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/A5015206948","display_name":"Gee-Sern Hsu","orcid":"https://orcid.org/0000-0003-2631-0448"},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":true,"raw_author_name":"Gee-Sern Hsu","raw_affiliation_strings":["Dept. of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei City, Taiwan"],"affiliations":[{"raw_affiliation_string":"Dept. of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei City, Taiwan","institution_ids":["https://openalex.org/I154864474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051935928","display_name":"ArulMurugan Ambikapathi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"ArulMurugan Ambikapathi","raw_affiliation_strings":["Utechzone Co. Ltd., New Taipei City, Taiwan"],"affiliations":[{"raw_affiliation_string":"Utechzone Co. Ltd., New Taipei City, Taiwan","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5064336793","display_name":"Ming-Shiang Chen","orcid":null},"institutions":[{"id":"https://openalex.org/I154864474","display_name":"National Taiwan University of Science and Technology","ror":"https://ror.org/00q09pe49","country_code":"TW","type":"education","lineage":["https://openalex.org/I154864474"]}],"countries":["TW"],"is_corresponding":false,"raw_author_name":"Ming-Shiang Chen","raw_affiliation_strings":["Dept. of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei City, Taiwan"],"affiliations":[{"raw_affiliation_string":"Dept. of Mechanical Engineering, National Taiwan University of Science and Technology, Taipei City, Taiwan","institution_ids":["https://openalex.org/I154864474"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5015206948"],"corresponding_institution_ids":["https://openalex.org/I154864474"],"apc_list":null,"apc_paid":null,"fwci":2.5995,"has_fulltext":false,"cited_by_count":112,"citation_normalized_percentile":{"value":0.89871262,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"383","last_page":"389"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11021","display_name":"ECG Monitoring and Analysis","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/2705","display_name":"Cardiology and Cardiovascular Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T10977","display_name":"Optical Imaging and Spectroscopy Techniques","score":0.980400025844574,"subfield":{"id":"https://openalex.org/subfields/2741","display_name":"Radiology, Nuclear Medicine and Imaging"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7850145101547241},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7781212329864502},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.606165885925293},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.5255842804908752},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.517157256603241},{"id":"https://openalex.org/keywords/pulse","display_name":"Pulse (music)","score":0.5127192735671997},{"id":"https://openalex.org/keywords/short-time-fourier-transform","display_name":"Short-time Fourier transform","score":0.5045763254165649},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4746471047401428},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.4665992259979248},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4474581778049469},{"id":"https://openalex.org/keywords/fourier-transform","display_name":"Fourier transform","score":0.39546018838882446},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3635784983634949},{"id":"https://openalex.org/keywords/fourier-analysis","display_name":"Fourier analysis","score":0.18721452355384827},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14127644896507263}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7850145101547241},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7781212329864502},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.606165885925293},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.5255842804908752},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.517157256603241},{"id":"https://openalex.org/C2780167933","wikidata":"https://www.wikidata.org/wiki/Q1550652","display_name":"Pulse (music)","level":3,"score":0.5127192735671997},{"id":"https://openalex.org/C166386157","wikidata":"https://www.wikidata.org/wiki/Q1477735","display_name":"Short-time Fourier transform","level":4,"score":0.5045763254165649},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4746471047401428},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.4665992259979248},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4474581778049469},{"id":"https://openalex.org/C102519508","wikidata":"https://www.wikidata.org/wiki/Q6520159","display_name":"Fourier transform","level":2,"score":0.39546018838882446},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3635784983634949},{"id":"https://openalex.org/C203024314","wikidata":"https://www.wikidata.org/wiki/Q1365258","display_name":"Fourier analysis","level":3,"score":0.18721452355384827},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14127644896507263},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/btas.2017.8272721","is_oa":false,"landing_page_url":"https://doi.org/10.1109/btas.2017.8272721","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Joint Conference on Biometrics (IJCB)","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":28,"referenced_works":["https://openalex.org/W1686810756","https://openalex.org/W1849007038","https://openalex.org/W1984026713","https://openalex.org/W1984554603","https://openalex.org/W1986273245","https://openalex.org/W1998294030","https://openalex.org/W2003922338","https://openalex.org/W2008821584","https://openalex.org/W2016778993","https://openalex.org/W2047508432","https://openalex.org/W2048032753","https://openalex.org/W2058961190","https://openalex.org/W2069692225","https://openalex.org/W2082046021","https://openalex.org/W2103484453","https://openalex.org/W2122098299","https://openalex.org/W2145487065","https://openalex.org/W2155893237","https://openalex.org/W2157285372","https://openalex.org/W2472200183","https://openalex.org/W2950094539","https://openalex.org/W2962835968","https://openalex.org/W2963566548","https://openalex.org/W3106250896","https://openalex.org/W6637373629","https://openalex.org/W6638943231","https://openalex.org/W6662335928","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2318109418","https://openalex.org/W2008311543","https://openalex.org/W2802845977","https://openalex.org/W3097412542","https://openalex.org/W2120847449","https://openalex.org/W2078793534","https://openalex.org/W3167466058","https://openalex.org/W4225639054","https://openalex.org/W2143985734","https://openalex.org/W1967434260"],"abstract_inverted_index":{"Accurate":[0],"pulse":[1,22,50,142,174,185,216],"estimation":[2,23,53,143,175,217],"is":[3,122,165],"of":[4,13,63,92,131,140,167],"pivotal":[5],"importance":[6],"in":[7,153],"acquiring":[8],"the":[9,46,71,79,88,93,100,117,126,132,138,141,168,188,198,220,224],"critical":[10],"physical":[11],"conditions":[12],"human":[14],"subjects":[15],"under":[16],"test,":[17],"and":[18,73,76,96,103,111,193],"facial":[19,81,101],"video":[20],"based":[21],"approaches":[24,218],"recently":[25],"gained":[26],"attention":[27],"owing":[28],"to":[29,38,124,196,208,214],"their":[30],"simplicity.":[31],"In":[32,83,114],"this":[33],"work,":[34],"we":[35,86],"have":[36,182],"endeavored":[37],"develop":[39],"a":[40,56,157,177,184],"novel":[41],"deep":[42,158,178],"learning":[43,179],"approach":[44,61,164,226],"as":[45,144],"core":[47],"part":[48],"for":[49,108,171],"(heart":[51],"rate)":[52],"by":[54,69,156],"using":[55,176],"common":[57],"RGB":[58],"camera.":[59],"Our":[60,163],"consists":[62],"four":[64],"steps.":[65],"We":[66,181],"first":[67],"begin":[68],"detecting":[70],"face":[72],"its":[74],"landmarks,":[75],"thereby":[77],"locate":[78],"required":[80],"ROI.":[82],"Step":[84,115,154],"2,":[85],"extract":[87],"sample":[89],"mean":[90],"sequences":[91],"R,":[94],"G,":[95],"B":[97],"channels":[98],"from":[99,190],"ROI,":[102],"explore":[104],"three":[105],"processing":[106],"schemes":[107],"noise":[109],"removal":[110],"signal":[112],"enhancement.":[113],"3,":[116],"Short-Time":[118],"Fourier":[119],"Transform":[120],"(STFT)":[121],"employed":[123],"build":[125],"2D":[127,135],"Time-Frequency":[128],"Representations":[129],"(TFRs)":[130],"sequences.":[133],"The":[134,200],"TFR":[136],"enables":[137],"formulation":[139],"an":[145],"image-based":[146],"classification":[147],"problem,":[148],"which":[149],"can":[150],"be":[151,204],"solved":[152],"4":[155],"Con-volutional":[159],"Neural":[160],"Network":[161],"(CNN).":[162],"one":[166],"pioneering":[169],"works":[170],"attempting":[172],"real-time":[173],"framework.":[180],"developed":[183],"database,":[186,223],"called":[187],"Pulse":[189],"Face":[191],"(PFF),":[192],"used":[194],"it":[195],"train":[197],"CNN.":[199],"PFF":[201],"database":[202],"will":[203],"made":[205],"publicly":[206],"available":[207],"advance":[209],"related":[210],"research.":[211],"When":[212],"compared":[213],"state-of-the-art":[215],"on":[219],"standard":[221],"MAHNOB-HCI":[222],"proposed":[225],"has":[227],"exhibited":[228],"superior":[229],"performance.":[230]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":14},{"year":2024,"cited_by_count":18},{"year":2023,"cited_by_count":19},{"year":2022,"cited_by_count":20},{"year":2021,"cited_by_count":20},{"year":2020,"cited_by_count":10},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":4}],"updated_date":"2026-03-09T08:58:05.943551","created_date":"2025-10-10T00:00:00"}