{"id":"https://openalex.org/W2895559961","doi":"https://doi.org/10.1145/3242969.3264986","title":"An Ensemble Model Using Face and Body Tracking for Engagement Detection","display_name":"An Ensemble Model Using Face and Body Tracking for Engagement Detection","publication_year":2018,"publication_date":"2018-10-02","ids":{"openalex":"https://openalex.org/W2895559961","doi":"https://doi.org/10.1145/3242969.3264986","mag":"2895559961"},"language":"en","primary_location":{"id":"doi:10.1145/3242969.3264986","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3242969.3264986","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 20th ACM International Conference on Multimodal Interaction","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/A5041872254","display_name":"Cheng Chang","orcid":"https://orcid.org/0000-0002-0361-2438"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Cheng Chang","raw_affiliation_strings":["Liulishuo, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Liulishuo, Shanghai, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100439643","display_name":"Cheng Zhang","orcid":"https://orcid.org/0000-0002-4510-0238"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Zhang","raw_affiliation_strings":["Tongji University, Shanghai, China"],"affiliations":[{"raw_affiliation_string":"Tongji University, Shanghai, China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100333468","display_name":"Lei Chen","orcid":"https://orcid.org/0000-0002-4279-3892"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lei Chen","raw_affiliation_strings":["Liulishuo AI Lab, San Mateo, CA, USA"],"affiliations":[{"raw_affiliation_string":"Liulishuo AI Lab, San Mateo, CA, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100355692","display_name":"Yang Liu","orcid":"https://orcid.org/0000-0001-7300-9215"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang Liu","raw_affiliation_strings":["Liulishuo AI Lab, San Mateo, CA, USA"],"affiliations":[{"raw_affiliation_string":"Liulishuo AI Lab, San Mateo, CA, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5041872254"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.7231,"has_fulltext":false,"cited_by_count":62,"citation_normalized_percentile":{"value":0.9517492,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"616","last_page":"622"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9995999932289124,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9995999932289124,"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":0.9869999885559082,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9549000263214111,"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":0.7266116738319397},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.7061439156532288},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6452718377113342},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.6050757169723511},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.5431458353996277},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5319350957870483},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5170746445655823},{"id":"https://openalex.org/keywords/mean-squared-error","display_name":"Mean squared error","score":0.5132503509521484},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.44816893339157104},{"id":"https://openalex.org/keywords/face","display_name":"Face (sociological concept)","score":0.43507298827171326},{"id":"https://openalex.org/keywords/ensemble-learning","display_name":"Ensemble learning","score":0.43199506402015686},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4248020350933075},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4212242066860199},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11431115865707397},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.09324151277542114},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09060999751091003}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7266116738319397},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.7061439156532288},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6452718377113342},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.6050757169723511},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.5431458353996277},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5319350957870483},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5170746445655823},{"id":"https://openalex.org/C139945424","wikidata":"https://www.wikidata.org/wiki/Q1940696","display_name":"Mean squared error","level":2,"score":0.5132503509521484},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.44816893339157104},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.43507298827171326},{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.43199506402015686},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4248020350933075},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4212242066860199},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11431115865707397},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.09324151277542114},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09060999751091003},{"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/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3242969.3264986","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3242969.3264986","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 20th ACM International Conference on Multimodal Interaction","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":20,"referenced_works":["https://openalex.org/W168564468","https://openalex.org/W1628791547","https://openalex.org/W1769933788","https://openalex.org/W1836465849","https://openalex.org/W1988790447","https://openalex.org/W2010792435","https://openalex.org/W2064675550","https://openalex.org/W2081112272","https://openalex.org/W2098597588","https://openalex.org/W2131744502","https://openalex.org/W2271840356","https://openalex.org/W2345031027","https://openalex.org/W2546309605","https://openalex.org/W2548431713","https://openalex.org/W2559085405","https://openalex.org/W2787783313","https://openalex.org/W2888683367","https://openalex.org/W2950402190","https://openalex.org/W2963962355","https://openalex.org/W4248437541"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W2900413183","https://openalex.org/W4390975304","https://openalex.org/W147410782","https://openalex.org/W3022252430","https://openalex.org/W4287804464","https://openalex.org/W2951627661","https://openalex.org/W4301628046","https://openalex.org/W2170587542"],"abstract_inverted_index":{"Precise":[0],"detection":[1,20,76],"and":[2,55,62],"localization":[3],"of":[4,26,107],"learners'":[5],"engagement":[6,19,36,75],"levels":[7],"are":[8],"useful":[9],"for":[10,34,59],"monitoring":[11],"their":[12],"learning":[13],"quality.":[14],"In":[15],"the":[16,44,79,86,96],"emotiW":[17],"Challenge's":[18],"task,":[21],"we":[22],"proposed":[23,71],"a":[24,31,40,103],"series":[25],"novel":[27],"improvements,":[28],"including":[29],"(a)":[30],"cluster-based":[32],"framework":[33],"fast":[35],"level":[37],"predictions,":[38],"(b)":[39],"neural":[41],"network":[42],"using":[43,51],"attention":[45],"pooling":[46],"mechanism,":[47],"(c)":[48],"heuristic":[49],"rules":[50],"body":[52],"posture":[53],"information,":[54],"(d)":[56],"model":[57],"ensemble":[58],"more":[60],"accurate":[61],"robust":[63],"predictions.":[64],"Our":[65],"experimental":[66],"results":[67],"suggest":[68],"that":[69],"our":[70,82,100],"methods":[72],"effectively":[73],"improved":[74],"performance.":[77],"On":[78,95],"validation":[80],"set,":[81,99],"system":[83,101],"can":[84],"reduce":[85],"baseline":[87],"Mean":[88],"Squared":[89],"Error":[90],"(MSE)":[91],"by":[92],"about":[93],"56%.":[94],"final":[97],"test":[98],"yielded":[102],"competitively":[104],"low":[105],"MSE":[106],"0.081.":[108]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":17},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":3}],"updated_date":"2026-03-31T07:56:22.981413","created_date":"2025-10-10T00:00:00"}
