{"id":"https://openalex.org/W1539740272","doi":"https://doi.org/10.1109/fg.2015.7163105","title":"Sports Videos in the Wild (SVW): A video dataset for sports analysis","display_name":"Sports Videos in the Wild (SVW): A video dataset for sports analysis","publication_year":2015,"publication_date":"2015-05-01","ids":{"openalex":"https://openalex.org/W1539740272","doi":"https://doi.org/10.1109/fg.2015.7163105","mag":"1539740272"},"language":"en","primary_location":{"id":"doi:10.1109/fg.2015.7163105","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg.2015.7163105","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/A5071594466","display_name":"S. Morteza Safdarnejad","orcid":null},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Seyed Morteza Safdarnejad","raw_affiliation_strings":["Michigan State University, East Lansing, MI, USA","Michigan State University,East Lansing, MI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Michigan State University,East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100409053","display_name":"Xiaoming Liu","orcid":"https://orcid.org/0000-0003-3467-5607"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaoming Liu","raw_affiliation_strings":["Michigan State University, East Lansing, MI, USA","Michigan State University,East Lansing, MI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Michigan State University,East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090893424","display_name":"\u041b\u0430\u043b\u0438\u0442\u0430 \u0423\u0434\u043f\u0430","orcid":"https://orcid.org/0000-0003-2007-0244"},"institutions":[{"id":"https://openalex.org/I87216513","display_name":"Michigan State University","ror":"https://ror.org/05hs6h993","country_code":"US","type":"education","lineage":["https://openalex.org/I87216513"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lalita Udpa","raw_affiliation_strings":["Michigan State University, East Lansing, MI, USA","Michigan State University,East Lansing, MI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Michigan State University, East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]},{"raw_affiliation_string":"Michigan State University,East Lansing, MI, USA","institution_ids":["https://openalex.org/I87216513"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052463490","display_name":"Brooks Andrus","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Brooks Andrus","raw_affiliation_strings":["TechSmith Corporation, Okemos, MI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TechSmith Corporation, Okemos, MI, USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030412645","display_name":"John Wood","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"John Wood","raw_affiliation_strings":["TechSmith Corporation, Okemos, MI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TechSmith Corporation, Okemos, MI, USA","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5084776920","display_name":"Dean Craven","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dean Craven","raw_affiliation_strings":["TechSmith Corporation, Okemos, MI, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"TechSmith Corporation, Okemos, MI, USA","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5071594466"],"corresponding_institution_ids":["https://openalex.org/I87216513"],"apc_list":null,"apc_paid":null,"fwci":1.4973,"has_fulltext":false,"cited_by_count":59,"citation_normalized_percentile":{"value":0.87724079,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"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/T11439","display_name":"Video Analysis and Summarization","score":0.9983999729156494,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9865000247955322,"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/categorization","display_name":"Categorization","score":0.8202565312385559},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8039271235466003},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.514360785484314},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5102493762969971},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.48714539408683777},{"id":"https://openalex.org/keywords/multimedia","display_name":"Multimedia","score":0.47344040870666504},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.4455740749835968},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4417562782764435},{"id":"https://openalex.org/keywords/broadcasting","display_name":"Broadcasting (networking)","score":0.4297757148742676},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.42529380321502686},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3266512155532837},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.26919466257095337},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.07572948932647705}],"concepts":[{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.8202565312385559},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8039271235466003},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.514360785484314},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5102493762969971},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.48714539408683777},{"id":"https://openalex.org/C49774154","wikidata":"https://www.wikidata.org/wiki/Q131765","display_name":"Multimedia","level":1,"score":0.47344040870666504},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.4455740749835968},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4417562782764435},{"id":"https://openalex.org/C110157686","wikidata":"https://www.wikidata.org/wiki/Q922122","display_name":"Broadcasting (networking)","level":2,"score":0.4297757148742676},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.42529380321502686},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3266512155532837},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.26919466257095337},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.07572948932647705},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0},{"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/fg.2015.7163105","is_oa":false,"landing_page_url":"https://doi.org/10.1109/fg.2015.7163105","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:CiteSeerX.psu:10.1.1.720.1830","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.720.1830","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cse.msu.edu/%7Eliuxm/publication/Safdarnejad_Liu_Udpa_Andrus_Wood_Craven_FG2015.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":53,"referenced_works":["https://openalex.org/W7859433","https://openalex.org/W24089286","https://openalex.org/W157898781","https://openalex.org/W1498368596","https://openalex.org/W1595717062","https://openalex.org/W1625255723","https://openalex.org/W1782590233","https://openalex.org/W1856951181","https://openalex.org/W1909591079","https://openalex.org/W1972482772","https://openalex.org/W1981781955","https://openalex.org/W1993521836","https://openalex.org/W1999666191","https://openalex.org/W2010399676","https://openalex.org/W2012001137","https://openalex.org/W2016053056","https://openalex.org/W2019464758","https://openalex.org/W2020163092","https://openalex.org/W2033419168","https://openalex.org/W2034328688","https://openalex.org/W2041941194","https://openalex.org/W2063153269","https://openalex.org/W2068611653","https://openalex.org/W2076424778","https://openalex.org/W2081589848","https://openalex.org/W2101194540","https://openalex.org/W2105101328","https://openalex.org/W2108431203","https://openalex.org/W2122319321","https://openalex.org/W2123477621","https://openalex.org/W2126574503","https://openalex.org/W2126579184","https://openalex.org/W2143792226","https://openalex.org/W2144719056","https://openalex.org/W2151103935","https://openalex.org/W2152583421","https://openalex.org/W2161969291","https://openalex.org/W2162591519","https://openalex.org/W2163292664","https://openalex.org/W2166070055","https://openalex.org/W4249279051","https://openalex.org/W6600334036","https://openalex.org/W6600983433","https://openalex.org/W6606408464","https://openalex.org/W6635755983","https://openalex.org/W6636494156","https://openalex.org/W6650080228","https://openalex.org/W6671212865","https://openalex.org/W6676357427","https://openalex.org/W6681396514","https://openalex.org/W6681585585","https://openalex.org/W6684114947","https://openalex.org/W7002092386"],"related_works":["https://openalex.org/W2165912799","https://openalex.org/W2735662278","https://openalex.org/W2130674020","https://openalex.org/W2093748878","https://openalex.org/W2333771223","https://openalex.org/W2382615723","https://openalex.org/W4311804456","https://openalex.org/W1987484445","https://openalex.org/W2623658258","https://openalex.org/W2120056845"],"abstract_inverted_index":{"Considering":[0],"the":[1,51,61,104,129,195,202],"enormous":[2],"creation":[3],"rate":[4],"of":[5,23,37,47,55,60,89,97,119,179],"usergenerated":[6],"videos":[7,56,81,86,143],"on":[8],"websites":[9],"like":[10],"YouTube,":[11],"there":[12],"is":[13],"an":[14],"immediate":[15],"need":[16],"for":[17,28,134,148,175,213],"automatic":[18],"categorization,":[19,190],"recognition":[20],"and":[21,33,87,93,123,157,163,191,205],"analysis":[22],"videos.":[24],"To":[25],"develop":[26],"algorithms":[27],"analyzing":[29],"user-generated":[30],"videos,":[31],"unconstrained":[32],"representative":[34],"datasets":[35],"are":[36],"great":[38],"significance.":[39],"For":[40],"this":[41,170],"purpose,":[42],"we":[43,200],"collected":[44],"a":[45,71,75,176],"dataset":[46,78,171],"Sports":[48],"Videos":[49,96],"in":[50,140],"Wild":[52],"(SVW),":[53],"consisting":[54],"captured":[57,144],"by":[58,83,137,145],"users":[59],"leading":[62],"sports":[63,91,98,106],"training":[64,121],"mobile":[65],"app":[66],"(Coach's":[67],"Eye)":[68],"while":[69],"practicing":[70],"sport":[72,196],"or":[73],"watching":[74],"game.":[76],"The":[77],"contains":[79],"4100":[80],"selected":[82],"reviewing":[84],"~85,000":[85],"consists":[88],"30":[90],"categories":[92],"44":[94],"actions.":[95,127],"practice,":[99],"which":[100],"frequently":[101],"happens":[102],"outside":[103],"typical":[105],"field,":[107],"have":[108],"huge":[109],"intra-class":[110],"variations":[111],"due":[112,153],"to":[113,142,151,154,210],"background":[114],"clutter,":[115],"unrepresentative":[116],"environment,":[117],"existence":[118],"different":[120,208],"equipment":[122],"most":[124],"importantly,":[125],"imperfect":[126],"On":[128,194],"other":[130],"hand,":[131],"using":[132],"smartphones":[133],"video":[135],"capturing":[136],"ordinary":[138],"people,":[139],"comparison":[141],"professional":[146],"crew":[147],"broadcasting,":[149],"leads":[150],"challenges":[152],"camera":[155],"vibration":[156],"motion,":[158],"occlusion,":[159],"view":[160],"point":[161],"variation,":[162],"poor":[164],"illumination.":[165],"Given":[166],"various":[167],"manual":[168],"labels,":[169],"can":[172],"be":[173],"used":[174],"wide":[177],"range":[178],"computer":[180],"vision":[181],"applications,":[182],"such":[183],"as":[184],"action":[185,187],"recognition,":[186],"detection,":[188],"genre":[189,197],"spatio-temporal":[192],"alignment.":[193],"categorization":[198],"problem,":[199],"design":[201],"evaluation":[203],"protocol":[204],"evaluate":[206],"three":[207],"methods":[209],"provide":[211],"baselines":[212],"future":[214],"works.":[215]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":8},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":3}],"updated_date":"2026-05-22T09:01:20.584952","created_date":"2025-10-10T00:00:00"}
