{"id":"https://openalex.org/W2991015170","doi":"https://doi.org/10.1145/3355056.3364555","title":"Real-time Table Tennis Forecasting System based on Long Short-term Pose Prediction Network","display_name":"Real-time Table Tennis Forecasting System based on Long Short-term Pose Prediction Network","publication_year":2019,"publication_date":"2019-11-17","ids":{"openalex":"https://openalex.org/W2991015170","doi":"https://doi.org/10.1145/3355056.3364555","mag":"2991015170"},"language":"en","primary_location":{"id":"doi:10.1145/3355056.3364555","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3355056.3364555","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIGGRAPH Asia 2019 Posters","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/A5080771266","display_name":"Erwin Wu","orcid":"https://orcid.org/0000-0002-6723-2864"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Erwin Wu","raw_affiliation_strings":["Tokyo Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology","institution_ids":["https://openalex.org/I114531698"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060423255","display_name":"Florian Perteneder","orcid":"https://orcid.org/0000-0003-0664-570X"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Florian Perteneder","raw_affiliation_strings":["Tokyo Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology","institution_ids":["https://openalex.org/I114531698"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056982483","display_name":"Hideki Koike","orcid":"https://orcid.org/0000-0002-8989-6434"},"institutions":[{"id":"https://openalex.org/I114531698","display_name":"Tokyo Institute of Technology","ror":"https://ror.org/0112mx960","country_code":"JP","type":"education","lineage":["https://openalex.org/I114531698"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hideki Koike","raw_affiliation_strings":["Tokyo Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Tokyo Institute of Technology","institution_ids":["https://openalex.org/I114531698"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5080771266"],"corresponding_institution_ids":["https://openalex.org/I114531698"],"apc_list":null,"apc_paid":null,"fwci":2.1928,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.91874261,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"23","issue":null,"first_page":"1","last_page":"2"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11674","display_name":"Sports Analytics and Performance","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11674","display_name":"Sports Analytics and Performance","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12677","display_name":"Sports Dynamics and Biomechanics","score":0.9900000095367432,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/T10157","display_name":"Sports Performance and Training","score":0.9783999919891357,"subfield":{"id":"https://openalex.org/subfields/2732","display_name":"Orthopedics and Sports Medicine"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7236961722373962},{"id":"https://openalex.org/keywords/table","display_name":"Table (database)","score":0.6821921467781067},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5890382528305054},{"id":"https://openalex.org/keywords/tennis-ball","display_name":"Tennis ball","score":0.5798869729042053},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5721361637115479},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.5358060598373413},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.4992513656616211},{"id":"https://openalex.org/keywords/long-term-prediction","display_name":"Long-term prediction","score":0.42096078395843506},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3737342953681946},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.37011247873306274},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3440510034561157},{"id":"https://openalex.org/keywords/sports-equipment","display_name":"sports equipment","score":0.2105560302734375},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.17521989345550537},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14323052763938904}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7236961722373962},{"id":"https://openalex.org/C45235069","wikidata":"https://www.wikidata.org/wiki/Q278425","display_name":"Table (database)","level":2,"score":0.6821921467781067},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5890382528305054},{"id":"https://openalex.org/C2992174615","wikidata":"https://www.wikidata.org/wiki/Q246514","display_name":"Tennis ball","level":3,"score":0.5798869729042053},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5721361637115479},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.5358060598373413},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.4992513656616211},{"id":"https://openalex.org/C2776537626","wikidata":"https://www.wikidata.org/wiki/Q4047883","display_name":"Long-term prediction","level":2,"score":0.42096078395843506},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3737342953681946},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.37011247873306274},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3440510034561157},{"id":"https://openalex.org/C2780101202","wikidata":"https://www.wikidata.org/wiki/Q768186","display_name":"sports equipment","level":2,"score":0.2105560302734375},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.17521989345550537},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14323052763938904},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3355056.3364555","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3355056.3364555","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"SIGGRAPH Asia 2019 Posters","raw_type":"proceedings-article"},{"id":"pmh:oai:irdb.nii.ac.jp:00897:0004492083","is_oa":false,"landing_page_url":"http://t2r2.star.titech.ac.jp/cgi-bin/publicationinfo.cgi?q_publication_content_number=CTT100821991","pdf_url":null,"source":{"id":"https://openalex.org/S7407056385","display_name":"Institutional Repositories DataBase (IRDB)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I184597095","host_organization_name":"National Institute of Informatics","host_organization_lineage":["https://openalex.org/I184597095"],"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":"conference paper"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","score":0.5099999904632568,"id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W2112090547","https://openalex.org/W2920953136","https://openalex.org/W2922183553","https://openalex.org/W4231290138","https://openalex.org/W4386729509"],"related_works":["https://openalex.org/W2283162247","https://openalex.org/W4212983513","https://openalex.org/W2524507886","https://openalex.org/W2314488738","https://openalex.org/W2052518016","https://openalex.org/W2771653066","https://openalex.org/W2085956791","https://openalex.org/W2901949253","https://openalex.org/W2081022503","https://openalex.org/W2767823485"],"abstract_inverted_index":{"Humans\u2019":[0],"ability":[1],"to":[2,30,106],"forecast":[3],"motions":[4,78],"and":[5,23,76],"trajectories,":[6],"are":[7],"one":[8],"of":[9,20,62,79],"the":[10,18,32,60,66,74],"most":[11],"important":[12],"abilities":[13],"in":[14],"many":[15],"sports.":[16],"With":[17],"development":[19],"deep":[21],"learning":[22],"computer":[24],"vision,":[25],"it":[26],"is":[27,69,83],"becoming":[28],"possible":[29],"do":[31],"same":[33],"thing":[34],"with":[35],"real-time":[36,44],"computing.":[37],"In":[38],"this":[39],"paper,":[40],"we":[41],"present":[42,77],"a":[43,50,63,80,87,108],"table":[45],"tennis":[46],"forecasting":[47],"system":[48,57,92],"using":[49,86],"long":[51],"short-term":[52],"pose":[53],"prediction":[54,100],"network.":[55],"Our":[56],"can":[58,93],"predict":[59],"trajectory":[61],"serve":[64],"before":[65],"pingpong":[67],"ball":[68],"even":[70],"hit":[71],"based":[72],"on":[73],"previous":[75],"player,":[81],"which":[82],"captured":[84],"only":[85],"single":[88],"RGB":[89],"camera.":[90],"The":[91],"be":[94],"either":[95],"used":[96,103],"for":[97,104],"training":[98],"beginner\u2019s":[99],"skill,":[101],"or":[102],"practitioners":[105],"train":[107],"conceal":[109],"serve.":[110]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}