{"id":"https://openalex.org/W1578643944","doi":"https://doi.org/10.1109/fg.2015.7163129","title":"Play with me \u2014 Measuring a child's engagement in a social interaction","display_name":"Play with me \u2014 Measuring a child's engagement in a social interaction","publication_year":2015,"publication_date":"2015-05-01","ids":{"openalex":"https://openalex.org/W1578643944","doi":"https://doi.org/10.1109/fg.2015.7163129","mag":"1578643944"},"language":"en","primary_location":{"id":"doi:10.1109/fg.2015.7163129","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg.2015.7163129","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/A5042782640","display_name":"Shyam Sundar Rajagopalan","orcid":"https://orcid.org/0009-0005-5461-7465"},"institutions":[{"id":"https://openalex.org/I188329596","display_name":"University of Canberra","ror":"https://ror.org/04s1nv328","country_code":"AU","type":"education","lineage":["https://openalex.org/I188329596"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Shyam Sundar Rajagopalan","raw_affiliation_strings":["Vision & Sensing Group, University of Canberra, Australia","Vision & Sensing Group, HCC Lab, ESTeM University of Canberra, Australia"],"affiliations":[{"raw_affiliation_string":"Vision & Sensing Group, University of Canberra, Australia","institution_ids":["https://openalex.org/I188329596"]},{"raw_affiliation_string":"Vision & Sensing Group, HCC Lab, ESTeM University of Canberra, Australia","institution_ids":["https://openalex.org/I188329596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083446879","display_name":"O.V. Ramana Murthy","orcid":"https://orcid.org/0000-0002-9616-7942"},"institutions":[{"id":"https://openalex.org/I188329596","display_name":"University of Canberra","ror":"https://ror.org/04s1nv328","country_code":"AU","type":"education","lineage":["https://openalex.org/I188329596"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"O.V. Ramana Murthy","raw_affiliation_strings":["Vision & Sensing Group, HCC Lab, ESTeM, University of Canberra, Canberra, ACT, AU","Vision & Sensing Group, HCC Lab, ESTeM University of Canberra, Australia"],"affiliations":[{"raw_affiliation_string":"Vision & Sensing Group, HCC Lab, ESTeM, University of Canberra, Canberra, ACT, AU","institution_ids":["https://openalex.org/I188329596"]},{"raw_affiliation_string":"Vision & Sensing Group, HCC Lab, ESTeM University of Canberra, Australia","institution_ids":["https://openalex.org/I188329596"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046144886","display_name":"Roland Goecke","orcid":"https://orcid.org/0000-0003-2279-7041"},"institutions":[{"id":"https://openalex.org/I188329596","display_name":"University of Canberra","ror":"https://ror.org/04s1nv328","country_code":"AU","type":"education","lineage":["https://openalex.org/I188329596"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Roland Goecke","raw_affiliation_strings":["Vision & Sensing Group, University of Canberra, Australia","Vision & Sensing Group, HCC Lab, ESTeM University of Canberra, Australia"],"affiliations":[{"raw_affiliation_string":"Vision & Sensing Group, University of Canberra, Australia","institution_ids":["https://openalex.org/I188329596"]},{"raw_affiliation_string":"Vision & Sensing Group, HCC Lab, ESTeM University of Canberra, Australia","institution_ids":["https://openalex.org/I188329596"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085265585","display_name":"Agata Rozga","orcid":"https://orcid.org/0000-0002-5558-9786"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Agata Rozga","raw_affiliation_strings":["School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA, USA","[School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA USA]"],"affiliations":[{"raw_affiliation_string":"School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]},{"raw_affiliation_string":"[School of Interactive Computing, Georgia Institute of Technology, Atlanta, GA USA]","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5042782640"],"corresponding_institution_ids":["https://openalex.org/I188329596"],"apc_list":null,"apc_paid":null,"fwci":1.6834,"has_fulltext":false,"cited_by_count":22,"citation_normalized_percentile":{"value":0.89035045,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998000264167786,"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":0.9998000264167786,"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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9980999827384949,"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/T10860","display_name":"Speech and Audio Processing","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/robustness","display_name":"Robustness (evolution)","score":0.7082056999206543},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6857271194458008},{"id":"https://openalex.org/keywords/conditional-random-field","display_name":"Conditional random field","score":0.615034818649292},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.5712147355079651},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.566635012626648},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5592082142829895},{"id":"https://openalex.org/keywords/gesture","display_name":"Gesture","score":0.528842568397522},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4812186062335968},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4579010307788849},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.43656009435653687},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.4355354905128479},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.41294926404953003},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3651318848133087},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.07448425889015198}],"concepts":[{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.7082056999206543},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6857271194458008},{"id":"https://openalex.org/C152565575","wikidata":"https://www.wikidata.org/wiki/Q1124538","display_name":"Conditional random field","level":2,"score":0.615034818649292},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.5712147355079651},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.566635012626648},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5592082142829895},{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.528842568397522},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4812186062335968},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4579010307788849},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.43656009435653687},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.4355354905128479},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41294926404953003},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3651318848133087},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.07448425889015198},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/fg.2015.7163129","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg.2015.7163129","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"},{"id":"pmh:oai:openresearch-repository.anu.edu.au:1885/103773","is_oa":false,"landing_page_url":"http://hdl.handle.net/1885/103773","pdf_url":null,"source":{"id":"https://openalex.org/S4306402539","display_name":"ANU Open Research (Australian National University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I118347636","host_organization_name":"Australian National University","host_organization_lineage":["https://openalex.org/I118347636"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"The More the Merrier: Analysing the Affect of a Group of People in Images","raw_type":"Conference paper"},{"id":"pmh:tle:c2a9cd12-b243-45f0-96d1-24ea78ecf77d:1f071524-0ffb-45dd-b0fd-e2ac8222ffc2:1","is_oa":false,"landing_page_url":"http://www.canberra.edu.au/researchrepository/items/c2a9cd12-b243-45f0-96d1-24ea78ecf77d/1/","pdf_url":null,"source":{"id":"https://openalex.org/S7407050591","display_name":"University of Canberra Research Portal","issn_l":null,"issn":[],"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":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Conference Paper"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7900000214576721}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W136504859","https://openalex.org/W1973672195","https://openalex.org/W1990992394","https://openalex.org/W2012352275","https://openalex.org/W2014399678","https://openalex.org/W2020163092","https://openalex.org/W2034014085","https://openalex.org/W2062914254","https://openalex.org/W2066941820","https://openalex.org/W2096284813","https://openalex.org/W2097128017","https://openalex.org/W2101534792","https://openalex.org/W2105101328","https://openalex.org/W2130157722","https://openalex.org/W2148565578","https://openalex.org/W2153635508","https://openalex.org/W2157285372","https://openalex.org/W2166388096","https://openalex.org/W2167462312","https://openalex.org/W2171757151","https://openalex.org/W2239406506","https://openalex.org/W2396985712","https://openalex.org/W4211153864","https://openalex.org/W4298357390","https://openalex.org/W6605536666","https://openalex.org/W6712224591","https://openalex.org/W6997266731","https://openalex.org/W7047790039"],"related_works":["https://openalex.org/W2066003895","https://openalex.org/W2537963312","https://openalex.org/W2537762514","https://openalex.org/W2349788282","https://openalex.org/W577271088","https://openalex.org/W2356597680","https://openalex.org/W2120801881","https://openalex.org/W1974473538","https://openalex.org/W2020010749","https://openalex.org/W2164899521"],"abstract_inverted_index":{"Due":[0],"to":[1,31],"the":[2,36,64,96,111,124,130,136,147,150,165],"challenges":[3],"in":[4,9,49,81,87,164],"automatically":[5],"observing":[6],"child":[7],"behaviour":[8,156],"a":[10,83,88,133,161],"social":[11,89],"interaction,":[12],"an":[13,32,107],"automatic":[14],"extraction":[15],"of":[16,38,60,76,94,135,149,167],"high-level":[17,56,169],"features,":[18,57],"such":[19],"as":[20],"head":[21],"poses":[22],"and":[23,28,63,129,158],"hand":[24],"gestures,":[25],"is":[26,47,67,78,115,118],"difficult":[27],"noisy,":[29],"leading":[30],"inaccurate":[33],"model.":[34],"Hence,":[35],"feasibility":[37],"using":[39,99],"easily":[40],"obtainable":[41],"low-level":[42,65,151],"optical":[43],"flow":[44,71],"based":[45,72],"features":[46,66],"investigated":[48],"this":[50,144],"work.":[51],"A":[52,91],"comparative":[53],"study":[54,145],"involving":[55],"baseline":[58],"annotations":[59],"multiple":[61],"modalities":[62],"carried":[68],"out.":[69],"Optical":[70],"hidden":[73,97,112],"structure":[74],"learning":[75,106],"behaviours":[77],"strongly":[79],"discriminatory":[80],"predicting":[82],"child's":[84],"engagement":[85,155],"level":[86],"interaction.":[90],"two-stage":[92],"approach":[93,153],"discovering":[95],"structures":[98],"Hidden":[100],"Conditional":[101],"Random":[102],"Fields,":[103],"followed":[104],"by":[105,120],"SVM-based":[108],"model":[109],"on":[110,123],"state":[113,134],"marginals":[114],"proposed.":[116],"This":[117],"validated":[119],"conducting":[121],"experiments":[122],"Multimodal":[125],"Dyadic":[126],"Behaviour":[127],"Dataset":[128],"results":[131],"indicate":[132,146],"art":[137],"classification":[138],"performance.":[139],"The":[140],"insights":[141],"drawn":[142],"from":[143],"robustness":[148],"feature":[152],"towards":[154],"modelling":[157],"can":[159],"be":[160],"good":[162],"substitute":[163],"absence":[166],"accurate":[168],"features.":[170]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":5},{"year":2016,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
