{"id":"https://openalex.org/W3134694665","doi":"https://doi.org/10.1145/3411764.3445765","title":"GestureMap: Supporting Visual Analytics and Quantitative Analysis of Motion Elicitation Data by Learning 2D Embeddings","display_name":"GestureMap: Supporting Visual Analytics and Quantitative Analysis of Motion Elicitation Data by Learning 2D Embeddings","publication_year":2021,"publication_date":"2021-05-06","ids":{"openalex":"https://openalex.org/W3134694665","doi":"https://doi.org/10.1145/3411764.3445765","mag":"3134694665"},"language":"en","primary_location":{"id":"doi:10.1145/3411764.3445765","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3411764.3445765","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2103.00912","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Hai Dang","orcid":null},"institutions":[{"id":"https://openalex.org/I54009628","display_name":"University of Bayreuth","ror":"https://ror.org/0234wmv40","country_code":"DE","type":"education","lineage":["https://openalex.org/I54009628"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Hai Dang","raw_affiliation_strings":["Department of Computer Science, University of Bayreuth, Bayreuth, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Bayreuth, Bayreuth, Germany","institution_ids":["https://openalex.org/I54009628"]}]},{"author_position":"last","author":{"id":null,"display_name":"Daniel Buschek","orcid":null},"institutions":[{"id":"https://openalex.org/I54009628","display_name":"University of Bayreuth","ror":"https://ror.org/0234wmv40","country_code":"DE","type":"education","lineage":["https://openalex.org/I54009628"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Daniel Buschek","raw_affiliation_strings":["Department of Computer Science, University of Bayreuth, Bayreuth, Germany"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Bayreuth, Bayreuth, Germany","institution_ids":["https://openalex.org/I54009628"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I54009628"],"apc_list":null,"apc_paid":null,"fwci":0.6697,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.68335951,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9998999834060669,"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/T10914","display_name":"Tactile and Sensory Interactions","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10789","display_name":"Interactive and Immersive Displays","score":0.9939000010490417,"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/gesture","display_name":"Gesture","score":0.8647000193595886},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6582000255584717},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.46050000190734863},{"id":"https://openalex.org/keywords/visual-analytics","display_name":"Visual analytics","score":0.4496999979019165},{"id":"https://openalex.org/keywords/quantitative-analysis","display_name":"Quantitative analysis (chemistry)","score":0.4381999969482422},{"id":"https://openalex.org/keywords/analytics","display_name":"Analytics","score":0.4374000132083893},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4189000129699707},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.3652999997138977}],"concepts":[{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.8647000193595886},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7753999829292297},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6582000255584717},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6004999876022339},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.46050000190734863},{"id":"https://openalex.org/C59732488","wikidata":"https://www.wikidata.org/wiki/Q2528440","display_name":"Visual analytics","level":3,"score":0.4496999979019165},{"id":"https://openalex.org/C95986675","wikidata":"https://www.wikidata.org/wiki/Q185168","display_name":"Quantitative analysis (chemistry)","level":2,"score":0.4381999969482422},{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.4374000132083893},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4189000129699707},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4156999886035919},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38909998536109924},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.3652999997138977},{"id":"https://openalex.org/C159437735","wikidata":"https://www.wikidata.org/wiki/Q1519524","display_name":"Gesture recognition","level":3,"score":0.3449000120162964},{"id":"https://openalex.org/C99740376","wikidata":"https://www.wikidata.org/wiki/Q17092520","display_name":"Interactive visual analysis","level":4,"score":0.32679998874664307},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.32109999656677246},{"id":"https://openalex.org/C172367668","wikidata":"https://www.wikidata.org/wiki/Q6504956","display_name":"Data visualization","level":3,"score":0.3010999858379364},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.29510000348091125},{"id":"https://openalex.org/C2777036941","wikidata":"https://www.wikidata.org/wiki/Q6917771","display_name":"Motion analysis","level":2,"score":0.29190000891685486},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.2903999984264374},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.29010000824928284},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.28299999237060547},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.26570001244544983},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.25780001282691956},{"id":"https://openalex.org/C545860419","wikidata":"https://www.wikidata.org/wiki/Q5193251","display_name":"Cultural analytics","level":5,"score":0.2572999894618988}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3411764.3445765","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3411764.3445765","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2103.00912","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2103.00912","pdf_url":"https://arxiv.org/pdf/2103.00912","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:eref.uni-bayreuth.de:64581","is_oa":false,"landing_page_url":"https://eref.uni-bayreuth.de/64581/","pdf_url":null,"source":{"id":"https://openalex.org/S4377196442","display_name":"ERef Bayreuth (University of Bayreuth)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I54009628","host_organization_name":"University of Bayreuth","host_organization_lineage":["https://openalex.org/I54009628"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Veranstaltungsbeitrag"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2103.00912","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2103.00912","pdf_url":"https://arxiv.org/pdf/2103.00912","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":43,"referenced_works":["https://openalex.org/W1915551841","https://openalex.org/W1965694745","https://openalex.org/W1977199120","https://openalex.org/W1995113806","https://openalex.org/W2015776973","https://openalex.org/W2021264779","https://openalex.org/W2025647423","https://openalex.org/W2033955170","https://openalex.org/W2040947111","https://openalex.org/W2044874154","https://openalex.org/W2045035854","https://openalex.org/W2045127238","https://openalex.org/W2050571058","https://openalex.org/W2059140492","https://openalex.org/W2065228210","https://openalex.org/W2084616221","https://openalex.org/W2090687959","https://openalex.org/W2136691781","https://openalex.org/W2161304134","https://openalex.org/W2162425553","https://openalex.org/W2296311849","https://openalex.org/W2395981059","https://openalex.org/W2414191836","https://openalex.org/W2578634652","https://openalex.org/W2611642266","https://openalex.org/W2660336915","https://openalex.org/W2775663585","https://openalex.org/W2795371077","https://openalex.org/W2795922077","https://openalex.org/W2804807416","https://openalex.org/W2807983015","https://openalex.org/W2896078687","https://openalex.org/W2924334974","https://openalex.org/W2937541351","https://openalex.org/W2941025144","https://openalex.org/W2950579362","https://openalex.org/W2963207848","https://openalex.org/W3010390614","https://openalex.org/W3032058861","https://openalex.org/W3038778614","https://openalex.org/W3093594167","https://openalex.org/W3212137874","https://openalex.org/W4210979681"],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"GestureMap,":[3],"a":[4,19,60,64,108],"visual":[5,109],"analytics":[6],"tool":[7],"for":[8,129],"gesture":[9,57,113,144],"elicitation":[10,130],"which":[11],"directly":[12],"visualises":[13],"the":[14],"space":[15],"of":[16,91,111],"gestures.":[17],"Concretely,":[18],"Variational":[20],"Autoencoder":[21],"embeds":[22],"gestures":[23,53,75],"recorded":[24],"as":[25,121],"3D":[26],"skeletons":[27],"on":[28],"an":[29,88],"interactive":[30],"2D":[31],"map.":[32],"GestureMap":[33,80,98],"further":[34,116],"integrates":[35],"three":[36],"computational":[37],"capabilities":[38],"to":[39,42,54,106,136,140],"connect":[40],"exploration":[41],"quantitative":[43],"measures:":[44],"Leveraging":[45],"DTW":[46],"Barycenter":[47],"Averaging":[48],"(DBA),":[49],"we":[50],"compute":[51,63],"average":[52,70],"1)":[55],"represent":[56],"groups":[58],"at":[59],"glance;":[61],"2)":[62],"new":[65,118],"consensus":[66],"measure":[67],"(variance":[68],"around":[69],"gesture);":[71],"and":[72,81,87,103,132,134],"3)":[73],"cluster":[74],"with":[76,84],"k-means.":[77],"We":[78,126],"evaluate":[79],"its":[82],"concepts":[83],"eight":[85],"experts":[86],"in-depth":[89],"analysis":[90],"published":[92],"data.":[93],"Our":[94],"findings":[95],"show":[96],"how":[97],"facilitates":[99],"exploring":[100],"large":[101],"datasets":[102],"helps":[104],"researchers":[105],"gain":[107],"understanding":[110],"elicited":[112],"spaces.":[114],"It":[115],"opens":[117],"directions,":[119],"such":[120],"comparing":[122],"elicitations":[123],"across":[124],"studies.":[125],"discuss":[127],"implications":[128],"studies":[131],"research,":[133],"opportunities":[135],"extend":[137],"our":[138],"approach":[139],"additional":[141],"tasks":[142],"in":[143],"elicitation.":[145]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2021-03-15T00:00:00"}
