{"id":"https://openalex.org/W4386243133","doi":"https://doi.org/10.1145/3573381.3596460","title":"Validating Objective Evaluation Metric: Is Fr\u00e9chet Motion Distance able to Capture Foot Skating Artifacts ?","display_name":"Validating Objective Evaluation Metric: Is Fr\u00e9chet Motion Distance able to Capture Foot Skating Artifacts ?","publication_year":2023,"publication_date":"2023-06-12","ids":{"openalex":"https://openalex.org/W4386243133","doi":"https://doi.org/10.1145/3573381.3596460"},"language":"en","primary_location":{"id":"doi:10.1145/3573381.3596460","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3573381.3596460","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3573381.3596460","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 ACM International Conference on Interactive Media Experiences","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3573381.3596460","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015779130","display_name":"Antoine Maiorca","orcid":"https://orcid.org/0000-0001-5729-700X"},"institutions":[{"id":"https://openalex.org/I130929987","display_name":"University of Mons","ror":"https://ror.org/02qnnz951","country_code":"BE","type":"education","lineage":["https://openalex.org/I130929987"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"Antoine Maiorca","raw_affiliation_strings":["ISIA Lab, University of Mons, Belgium"],"affiliations":[{"raw_affiliation_string":"ISIA Lab, University of Mons, Belgium","institution_ids":["https://openalex.org/I130929987"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045112037","display_name":"Youngwoo Yoon","orcid":"https://orcid.org/0000-0003-4286-3421"},"institutions":[{"id":"https://openalex.org/I142401562","display_name":"Electronics and Telecommunications Research Institute","ror":"https://ror.org/03ysstz10","country_code":"KR","type":"facility","lineage":["https://openalex.org/I142401562","https://openalex.org/I2801339556","https://openalex.org/I4210144908","https://openalex.org/I4387152098"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Youngwoo Yoon","raw_affiliation_strings":["Electronics and Telecommunications Research Institute (ETRI), Korea, Republic of"],"affiliations":[{"raw_affiliation_string":"Electronics and Telecommunications Research Institute (ETRI), Korea, Republic of","institution_ids":["https://openalex.org/I142401562"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042439255","display_name":"Thierry Dutoit","orcid":"https://orcid.org/0000-0001-7024-2150"},"institutions":[{"id":"https://openalex.org/I130929987","display_name":"University of Mons","ror":"https://ror.org/02qnnz951","country_code":"BE","type":"education","lineage":["https://openalex.org/I130929987"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Thierry Dutoit","raw_affiliation_strings":["ISIA Lab, University of Mons, Belgium"],"affiliations":[{"raw_affiliation_string":"ISIA Lab, University of Mons, Belgium","institution_ids":["https://openalex.org/I130929987"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5015779130"],"corresponding_institution_ids":["https://openalex.org/I130929987"],"apc_list":null,"apc_paid":null,"fwci":0.2407,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.52199498,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"242","last_page":"247"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9994999766349792,"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":0.9994999766349792,"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/T12290","display_name":"Human Motion and Animation","score":0.9976999759674072,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.9975000023841858,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7429553270339966},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6892769932746887},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.6315927505493164},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6283272504806519},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.6089731454849243},{"id":"https://openalex.org/keywords/metric","display_name":"Metric (unit)","score":0.5937507152557373},{"id":"https://openalex.org/keywords/motion-capture","display_name":"Motion capture","score":0.5829596519470215},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.5060915350914001},{"id":"https://openalex.org/keywords/robotics","display_name":"Robotics","score":0.4924977719783783},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.45905813574790955},{"id":"https://openalex.org/keywords/foot","display_name":"Foot (prosody)","score":0.4555266499519348},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.44495949149131775},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.42662322521209717},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.2638501226902008},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.20291787385940552},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.14913883805274963},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1396317481994629},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10679861903190613}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7429553270339966},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6892769932746887},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.6315927505493164},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6283272504806519},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.6089731454849243},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.5937507152557373},{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.5829596519470215},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.5060915350914001},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.4924977719783783},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.45905813574790955},{"id":"https://openalex.org/C115076146","wikidata":"https://www.wikidata.org/wiki/Q1651051","display_name":"Foot (prosody)","level":2,"score":0.4555266499519348},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.44495949149131775},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.42662322521209717},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.2638501226902008},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.20291787385940552},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.14913883805274963},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1396317481994629},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10679861903190613},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","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/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","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":2,"locations":[{"id":"doi:10.1145/3573381.3596460","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3573381.3596460","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3573381.3596460","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 ACM International Conference on Interactive Media Experiences","raw_type":"proceedings-article"},{"id":"pmh:oai:orbi.umons.ac.be:20.500.12907/46735","is_oa":true,"landing_page_url":"https://orbi.umons.ac.be/handle/20.500.12907/46735","pdf_url":"https://orbi.umons.ac.be/bitstream/20.500.12907/46735/1/imx23-56_access.pdf","source":{"id":"https://openalex.org/S7407055454","display_name":"ORBi UMONS","issn_l":null,"issn":null,"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":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IMX '23: Proceedings of the 2023 ACM International Conference on Interactive Media Experiences (2023-08-29); IMX '23, 12-06-2023","raw_type":"peer reviewed"}],"best_oa_location":{"id":"doi:10.1145/3573381.3596460","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3573381.3596460","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3573381.3596460","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 ACM International Conference on Interactive Media Experiences","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4386243133.pdf","grobid_xml":"https://content.openalex.org/works/W4386243133.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W2078179989","https://openalex.org/W2120840438","https://openalex.org/W2150884987","https://openalex.org/W2194775991","https://openalex.org/W2526798603","https://openalex.org/W2611706523","https://openalex.org/W2758220497","https://openalex.org/W2801567109","https://openalex.org/W2963076818","https://openalex.org/W2964203186","https://openalex.org/W2972478942","https://openalex.org/W2983796203","https://openalex.org/W2983925976","https://openalex.org/W3010876998","https://openalex.org/W3034664137","https://openalex.org/W3083173864","https://openalex.org/W3095071412","https://openalex.org/W3125775899","https://openalex.org/W3153832461","https://openalex.org/W3174544525","https://openalex.org/W3188493377","https://openalex.org/W3204221554","https://openalex.org/W3205833998","https://openalex.org/W3206602673","https://openalex.org/W4234552385","https://openalex.org/W4283325290","https://openalex.org/W4286611287","https://openalex.org/W4287509562","https://openalex.org/W4288079574","https://openalex.org/W4292945985","https://openalex.org/W4304084213"],"related_works":["https://openalex.org/W1593608146","https://openalex.org/W2118728139","https://openalex.org/W3082611418","https://openalex.org/W2982970440","https://openalex.org/W2565579042","https://openalex.org/W4295532600","https://openalex.org/W2121966738","https://openalex.org/W2063823869","https://openalex.org/W2516207191","https://openalex.org/W4285650868"],"abstract_inverted_index":{"Automatically":[0],"generating":[1],"character":[2],"motion":[3,53,78,103,126],"is":[4,21,67,136,167,179],"one":[5],"of":[6,29,32,39,50,58,61,83,91,97,133,187],"the":[7,30,37,46,51,59,77,81,89,92,98,111,118,139,144,156,185,188],"technologies":[8],"required":[9],"for":[10],"virtual":[11],"reality,":[12],"graphics,":[13],"and":[14,48,102,174],"robotics.":[15],"Motion":[16,158],"synthesis":[17],"with":[18],"deep":[19],"learning":[20],"an":[22,34],"emerging":[23],"research":[24],"topic.":[25],"A":[26],"key":[27,56],"component":[28],"development":[31],"such":[33,84],"algorithm":[35],"involves":[36],"design":[38],"a":[40,69],"proper":[41],"objective":[42],"metric":[43],"to":[44,72,109,169,182],"evaluate":[45],"quality":[47],"diversity":[49],"synthesized":[52],"dataset,":[54],"two":[55],"factors":[57],"performance":[60],"generative":[62,115],"models.":[63],"The":[64],"Fr\u00e9chet":[65,93,157],"distance":[66,94],"nowadays":[68],"common":[70],"method":[71],"assess":[73],"this":[74,149],"performance.":[75],"In":[76,148],"generation":[79],"field,":[80],"validation":[82],"evaluation":[85],"methods":[86],"relies":[87],"on":[88,143],"computation":[90],"between":[95],"embeddings":[96],"ground":[99,145],"truth":[100],"dataset":[101],"samples":[104],"polluted":[105],"by":[106,114],"synthetic":[107,119],"noise":[108,120],"mimic":[110],"artifacts":[112,135],"produced":[113],"algorithms.":[116],"However,":[117],"degradation":[121],"does":[122],"not":[123,180],"fully":[124],"represent":[125],"perturbations":[127],"that":[128,177],"are":[129],"commonly":[130],"perceived.":[131],"One":[132],"these":[134],"foot":[137,141,171],"skating:":[138],"unnatural":[140],"slides":[142],"during":[146],"locomotion.":[147],"work-in-progress":[150],"paper,":[151],"we":[152,175],"tested":[153],"how":[154],"well":[155],"Distance":[159],"(FMD),":[160],"which":[161],"was":[162],"proposed":[163],"in":[164],"previous":[165],"works,":[166],"able":[168,181],"measure":[170,183],"skating":[172,189],"artifacts,":[173],"found":[176],"FMD":[178],"efficiently":[184],"intensity":[186],"degradation.":[190]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}