{"id":"https://openalex.org/W2922789690","doi":"https://doi.org/10.1145/3232233","title":"AttentiveVideo","display_name":"AttentiveVideo","publication_year":2019,"publication_date":"2019-03-18","ids":{"openalex":"https://openalex.org/W2922789690","doi":"https://doi.org/10.1145/3232233","mag":"2922789690"},"language":"en","primary_location":{"id":"doi:10.1145/3232233","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3232233","pdf_url":null,"source":{"id":"https://openalex.org/S4210173818","display_name":"ACM Transactions on Interactive Intelligent Systems","issn_l":"2160-6455","issn":["2160-6455","2160-6463"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Interactive Intelligent Systems","raw_type":"journal-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/A5059182099","display_name":"Phuong Thao Pham","orcid":"https://orcid.org/0000-0002-6205-1298"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Phuong Pham","raw_affiliation_strings":["Microsoft"],"affiliations":[{"raw_affiliation_string":"Microsoft","institution_ids":["https://openalex.org/I4210164937"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101663420","display_name":"Jingtao Wang","orcid":"https://orcid.org/0000-0002-1712-7898"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jingtao Wang","raw_affiliation_strings":["Google"],"affiliations":[{"raw_affiliation_string":"Google","institution_ids":["https://openalex.org/I1291425158"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5059182099"],"corresponding_institution_ids":["https://openalex.org/I4210164937"],"apc_list":null,"apc_paid":null,"fwci":1.3434,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.81292968,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"9","issue":"2-3","first_page":"1","last_page":"30"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9932000041007996,"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"}},"topics":[{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9932000041007996,"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/T11165","display_name":"Image and Video Quality Assessment","score":0.9912999868392944,"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/T11707","display_name":"Gaze Tracking and Assistive Technology","score":0.9884999990463257,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8055232763290405},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.5319153666496277},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5212267637252808},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4270375967025757},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4206923246383667},{"id":"https://openalex.org/keywords/mobile-device","display_name":"Mobile device","score":0.41462892293930054},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3869514465332031}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8055232763290405},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5319153666496277},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5212267637252808},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4270375967025757},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4206923246383667},{"id":"https://openalex.org/C186967261","wikidata":"https://www.wikidata.org/wiki/Q5082128","display_name":"Mobile device","level":2,"score":0.41462892293930054},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3869514465332031},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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:10.1145/3232233","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3232233","pdf_url":null,"source":{"id":"https://openalex.org/S4210173818","display_name":"ACM Transactions on Interactive Intelligent Systems","issn_l":"2160-6455","issn":["2160-6455","2160-6463"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Interactive Intelligent Systems","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W149760548","https://openalex.org/W276347511","https://openalex.org/W1571620383","https://openalex.org/W1586241444","https://openalex.org/W1596947417","https://openalex.org/W1859092166","https://openalex.org/W1924159954","https://openalex.org/W1956121861","https://openalex.org/W1995641269","https://openalex.org/W2003249666","https://openalex.org/W2003731571","https://openalex.org/W2012003427","https://openalex.org/W2012905273","https://openalex.org/W2013486063","https://openalex.org/W2019608648","https://openalex.org/W2020911841","https://openalex.org/W2026243162","https://openalex.org/W2031828545","https://openalex.org/W2040896124","https://openalex.org/W2047967129","https://openalex.org/W2050509157","https://openalex.org/W2057482827","https://openalex.org/W2064239885","https://openalex.org/W2074381856","https://openalex.org/W2075126953","https://openalex.org/W2079888450","https://openalex.org/W2082757115","https://openalex.org/W2094998392","https://openalex.org/W2106728444","https://openalex.org/W2112195179","https://openalex.org/W2117645142","https://openalex.org/W2122038527","https://openalex.org/W2123198781","https://openalex.org/W2127624016","https://openalex.org/W2146738284","https://openalex.org/W2149822245","https://openalex.org/W2159094788","https://openalex.org/W2250871723","https://openalex.org/W2281488167","https://openalex.org/W2291663305","https://openalex.org/W2339343773","https://openalex.org/W2345729520","https://openalex.org/W2485075409","https://openalex.org/W2548265919","https://openalex.org/W2548874434","https://openalex.org/W2549051284","https://openalex.org/W2560887976","https://openalex.org/W2576865949","https://openalex.org/W2594448782","https://openalex.org/W2594496087","https://openalex.org/W2610702023","https://openalex.org/W2614794251","https://openalex.org/W2700896614","https://openalex.org/W2803189955","https://openalex.org/W2905561276","https://openalex.org/W3122305203","https://openalex.org/W4241273708","https://openalex.org/W4252816727"],"related_works":["https://openalex.org/W2389214306","https://openalex.org/W4235240664","https://openalex.org/W2965083567","https://openalex.org/W1838576100","https://openalex.org/W2095886385","https://openalex.org/W2089704382","https://openalex.org/W1983399550","https://openalex.org/W3034529322","https://openalex.org/W97075385","https://openalex.org/W2393741509"],"abstract_inverted_index":{"Understanding":[0],"a":[1,7,33,61,92,100,125],"target":[2],"audience's":[3],"emotional":[4,104,176],"responses":[5,177],"to":[6,12,42,73,178],"video":[8,50,86,180],"advertisement":[9],"is":[10],"crucial":[11],"evaluate":[13],"the":[14,46,75,131,143,148,166],"advertisement's":[15],"effectiveness.":[16],"However,":[17],"traditional":[18],"methods":[19],"for":[20,168],"collecting":[21],"such":[22],"information":[23],"are":[24],"slow,":[25],"expensive,":[26],"and":[27,44,68,79,147,160,172],"coarse":[28],"grained.":[29],"We":[30,139],"propose":[31],"AttentiveVideo,":[32],"scalable":[34],"intelligent":[35],"mobile":[36,49,179],"interface":[37],"with":[38,124,136],"corresponding":[39],"inference":[40],"algorithms":[41],"monitor":[43],"quantify":[45],"effects":[47],"of":[48,63,81,103,175],"advertising":[51],"in":[52,154],"real":[53],"time.":[54],"Without":[55],"requiring":[56],"additional":[57],"sensors,":[58],"AttentiveVideo":[59,95],"employs":[60],"combination":[62],"implicit":[64],"photoplethysmography":[65],"(PPG)":[66],"sensing":[67,145],"facial":[69],"expression":[70],"analysis":[71],"(FEA)":[72],"detect":[74],"attention,":[76],"engagement":[77],",":[78],"sentiment":[80],"viewers":[82],"as":[83],"they":[84],"watch":[85],"advertisements":[87],"on":[88,99],"unmodified":[89],"smartphones.":[90],"In":[91],"24-participant":[93],"study,":[94],"achieved":[96],"good":[97],"accuracy":[98,109,123,132],"wide":[101],"range":[102],"measures":[105],"(the":[106],"best":[107],"average":[108],"=":[110],"82.6%":[111],"across":[112],"nine":[113],"measures).":[114],"While":[115],"feature":[116],"fusion":[117],"alone":[118],"did":[119],"not":[120],"improve":[121],"prediction":[122],"single":[126],"model,":[127],"it":[128],"significantly":[129],"improved":[130],"when":[133],"working":[134],"together":[135],"model":[137],"fusion.":[138],"also":[140],"found":[141],"that":[142],"PPG":[144],"channel":[146],"FEA":[149],"technique":[150],"have":[151],"different":[152],"strength":[153],"data":[155],"availability,":[156],"latency":[157],"detection,":[158],"accuracy,":[159],"usage":[161],"environment.":[162],"These":[163],"findings":[164],"show":[165],"potential":[167],"both":[169],"low-cost":[170],"collection":[171],"deep":[173],"understanding":[174],"advertisements.":[181]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2019-04-01T00:00:00"}
