{"id":"https://openalex.org/W3201918448","doi":"https://doi.org/10.1109/arso51874.2021.9541546","title":"Can't hide your disappointment: Using human pose and facial cues for intent prediction in a target game","display_name":"Can't hide your disappointment: Using human pose and facial cues for intent prediction in a target game","publication_year":2021,"publication_date":"2021-07-08","ids":{"openalex":"https://openalex.org/W3201918448","doi":"https://doi.org/10.1109/arso51874.2021.9541546","mag":"3201918448"},"language":"en","primary_location":{"id":"doi:10.1109/arso51874.2021.9541546","is_oa":false,"landing_page_url":"https://doi.org/10.1109/arso51874.2021.9541546","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Advanced Robotics and Its Social Impacts (ARSO)","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/A5034672129","display_name":"Vidullan Surendran","orcid":"https://orcid.org/0000-0002-9951-3513"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Vidullan Surendran","raw_affiliation_strings":["Pennsylvania State University, University Park, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pennsylvania State University, University Park, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045198429","display_name":"Alan R. Wagner","orcid":"https://orcid.org/0000-0002-7941-3814"},"institutions":[{"id":"https://openalex.org/I130769515","display_name":"Pennsylvania State University","ror":"https://ror.org/04p491231","country_code":"US","type":"education","lineage":["https://openalex.org/I130769515"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alan R. Wagner","raw_affiliation_strings":["Pennsylvania State University, University Park, PA, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pennsylvania State University, University Park, PA, USA","institution_ids":["https://openalex.org/I130769515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130769515"],"apc_list":null,"apc_paid":null,"fwci":0.1821,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.57443692,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"53","issue":null,"first_page":"21","last_page":"28"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10667","display_name":"Emotion and Mood Recognition","score":0.9923999905586243,"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":0.9923999905586243,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9876000285148621,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T10709","display_name":"Social Robot Interaction and HRI","score":0.98580002784729,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/outcome","display_name":"Outcome (game theory)","score":0.7623764276504517},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7096921801567078},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5536424517631531},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5347809791564941},{"id":"https://openalex.org/keywords/mistake","display_name":"Mistake","score":0.5276614427566528},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.4664205014705658},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.44823285937309265},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.43842241168022156},{"id":"https://openalex.org/keywords/facial-expression","display_name":"Facial expression","score":0.4298434853553772},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4180401861667633},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.4122895896434784},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.4114202857017517},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10852491855621338}],"concepts":[{"id":"https://openalex.org/C148220186","wikidata":"https://www.wikidata.org/wiki/Q7111912","display_name":"Outcome (game theory)","level":2,"score":0.7623764276504517},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7096921801567078},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5536424517631531},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5347809791564941},{"id":"https://openalex.org/C2777179996","wikidata":"https://www.wikidata.org/wiki/Q911222","display_name":"Mistake","level":2,"score":0.5276614427566528},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4664205014705658},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.44823285937309265},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.43842241168022156},{"id":"https://openalex.org/C195704467","wikidata":"https://www.wikidata.org/wiki/Q327968","display_name":"Facial expression","level":2,"score":0.4298434853553772},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4180401861667633},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4122895896434784},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.4114202857017517},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10852491855621338},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C144237770","wikidata":"https://www.wikidata.org/wiki/Q747534","display_name":"Mathematical economics","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/arso51874.2021.9541546","is_oa":false,"landing_page_url":"https://doi.org/10.1109/arso51874.2021.9541546","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Advanced Robotics and Its Social Impacts (ARSO)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1549492624","https://openalex.org/W1979492804","https://openalex.org/W2008348094","https://openalex.org/W2013637713","https://openalex.org/W2096733369","https://openalex.org/W2139019684","https://openalex.org/W2156303437","https://openalex.org/W2168736308","https://openalex.org/W2172156083","https://openalex.org/W2172642905","https://openalex.org/W2323122434","https://openalex.org/W2502051089","https://openalex.org/W2555139634","https://openalex.org/W2560474170","https://openalex.org/W2754051771","https://openalex.org/W2765425545","https://openalex.org/W2766891703","https://openalex.org/W2925327970","https://openalex.org/W2958183066","https://openalex.org/W2963569498","https://openalex.org/W2963781481","https://openalex.org/W2998435435","https://openalex.org/W3000061411","https://openalex.org/W3013640622","https://openalex.org/W3099206234","https://openalex.org/W4229726131","https://openalex.org/W4297736515","https://openalex.org/W6685542148","https://openalex.org/W6729937758","https://openalex.org/W6730303213","https://openalex.org/W6745588108"],"related_works":["https://openalex.org/W1590719878","https://openalex.org/W4244271513","https://openalex.org/W2365974527","https://openalex.org/W4306382224","https://openalex.org/W4226517682","https://openalex.org/W3108263396","https://openalex.org/W2895872277","https://openalex.org/W1561425952","https://openalex.org/W2496555895","https://openalex.org/W4236454870"],"abstract_inverted_index":{"Recognising":[0],"intent":[1,44,65,98,105,161,183],"in":[2,66,109,152,162],"collaborative":[3],"human":[4,12,64,108,122],"robot":[5],"tasks":[6],"can":[7,40,62],"improve":[8],"team":[9],"performance":[10],"and":[11,57,99,101,178],"perception":[13],"of":[14,26,45,54,69,82,106,112,121,154,160,165,176,189],"the":[15,24,30,37,43,46,67,80,83,87,92,97,104,107,110,113,119,155,158,163,181],"robot.":[16],"Tasks":[17],"that":[18,61,118,134,180],"involve":[19],"dynamic":[20],"physical":[21],"motions":[22],"increase":[23],"likelihood":[25],"mistakes":[27,166],"committed":[28],"by":[29],"human.":[31,47],"When":[32],"a":[33,50,59,74,136,173],"mistake":[34],"is":[35,144,167],"made,":[36],"observed":[38],"outcome":[39,81,93,125],"differ":[41],"from":[42],"We":[48,116],"setup":[49],"throwing":[51,114],"task":[52],"consisting":[53],"9":[55],"targets,":[56],"propose":[58],"method":[60,72,143],"predict":[63,79,103,148],"presence":[68,164],"mistakes.":[70],"This":[71],"uses":[73,135],"vision":[75],"based":[76],"pipeline":[77,185],"to":[78,91,128,131,139,147],"throw,":[84],"determine":[85],"if":[86],"subject's":[88],"emotional":[89],"reaction":[90],"indicates":[94],"incongruence":[95],"between":[96],"outcome,":[100],"finally":[102],"context":[111],"task.":[115],"show":[117],"use":[120],"pose":[123],"improves":[124],"prediction":[126,159],"accuracy":[127,188],"28%":[129],"compared":[130],"prior":[132],"work":[133],"two-stream":[137],"architecture":[138],"achieve":[140],"22%.":[141],"The":[142],"also":[145],"able":[146],"intent-outcome":[149],"congruence":[150],"accurately":[151],"75%":[153],"cases.":[156],"Since":[157],"currently":[168],"understudied,":[169],"we":[170],"compare":[171],"against":[172],"random":[174],"baseline":[175],"11%":[177],"find":[179],"end-to-end":[182],"recognition":[184],"achieves":[186],"an":[187],"23%.":[190]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}