{"id":"https://openalex.org/W3004653267","doi":"https://doi.org/10.1109/icspcs47537.2019.9008460","title":"Active Player Detection in Handball Videos Using Optical Flow and STIPs Based Measures","display_name":"Active Player Detection in Handball Videos Using Optical Flow and STIPs Based Measures","publication_year":2019,"publication_date":"2019-12-01","ids":{"openalex":"https://openalex.org/W3004653267","doi":"https://doi.org/10.1109/icspcs47537.2019.9008460","mag":"3004653267"},"language":"en","primary_location":{"id":"doi:10.1109/icspcs47537.2019.9008460","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icspcs47537.2019.9008460","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS)","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/A5065120677","display_name":"Marina Iva\u0161i\u0107-Kos","orcid":"https://orcid.org/0000-0002-1940-5089"},"institutions":[{"id":"https://openalex.org/I154347574","display_name":"University of Rijeka","ror":"https://ror.org/05r8dqr10","country_code":"HR","type":"education","lineage":["https://openalex.org/I154347574"]}],"countries":["HR"],"is_corresponding":false,"raw_author_name":"Marina Ivasic-Kos","raw_affiliation_strings":["Department of Informatics, University of Rijeka, Rijeka, Croatia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Informatics, University of Rijeka, Rijeka, Croatia","institution_ids":["https://openalex.org/I154347574"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039436597","display_name":"Miran Pobar","orcid":"https://orcid.org/0000-0001-5604-2128"},"institutions":[{"id":"https://openalex.org/I154347574","display_name":"University of Rijeka","ror":"https://ror.org/05r8dqr10","country_code":"HR","type":"education","lineage":["https://openalex.org/I154347574"]}],"countries":["HR"],"is_corresponding":false,"raw_author_name":"Miran Pobar","raw_affiliation_strings":["Department of Informatics, University of Rijeka, Rijeka, Croatia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Informatics, University of Rijeka, Rijeka, Croatia","institution_ids":["https://openalex.org/I154347574"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085462015","display_name":"Jordi Gonz\u00e0lez","orcid":"https://orcid.org/0000-0001-8033-0306"},"institutions":[{"id":"https://openalex.org/I4387153096","display_name":"Computer Vision Center","ror":"https://ror.org/00s0nnj93","country_code":null,"type":"other","lineage":["https://openalex.org/I4387153040","https://openalex.org/I4387153096"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Jordi Gonzalez","raw_affiliation_strings":["Computer Vision Center, Univ. Autflnoma de Barcelona, Bellaterra, Barcelona, Spain"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Vision Center, Univ. Autflnoma de Barcelona, Bellaterra, Barcelona, Spain","institution_ids":["https://openalex.org/I4387153096"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4338,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.73604656,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9815000295639038,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9815000295639038,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9800999760627747,"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":0.967199981212616,"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/computer-science","display_name":"Computer science","score":0.694156289100647},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6891579627990723},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6514102816581726},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.6131370067596436},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.546952486038208},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5449432730674744},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5223187804222107},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5189216136932373},{"id":"https://openalex.org/keywords/activity-recognition","display_name":"Activity recognition","score":0.4455043375492096},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.24970412254333496},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1265430748462677},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09609967470169067},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.05883216857910156}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.694156289100647},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6891579627990723},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6514102816581726},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.6131370067596436},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.546952486038208},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5449432730674744},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5223187804222107},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5189216136932373},{"id":"https://openalex.org/C121687571","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Activity recognition","level":2,"score":0.4455043375492096},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.24970412254333496},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1265430748462677},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09609967470169067},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.05883216857910156},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icspcs47537.2019.9008460","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icspcs47537.2019.9008460","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 13th International Conference on Signal Processing and Communication Systems (ICSPCS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1534763723","https://openalex.org/W1536680647","https://openalex.org/W1861492603","https://openalex.org/W2002706836","https://openalex.org/W2020163092","https://openalex.org/W2024868105","https://openalex.org/W2031489346","https://openalex.org/W2116367120","https://openalex.org/W2124386111","https://openalex.org/W2193145675","https://openalex.org/W2533739470","https://openalex.org/W2565639579","https://openalex.org/W2570343428","https://openalex.org/W2613718673","https://openalex.org/W2796347433","https://openalex.org/W2811186270","https://openalex.org/W2911099261","https://openalex.org/W2921065222","https://openalex.org/W2922442852","https://openalex.org/W2950800384","https://openalex.org/W2963037989","https://openalex.org/W2963150697","https://openalex.org/W2997110625","https://openalex.org/W3003662786","https://openalex.org/W3106250896","https://openalex.org/W4293584584","https://openalex.org/W6620707391","https://openalex.org/W6639102338","https://openalex.org/W6714138976","https://openalex.org/W6750227808"],"related_works":["https://openalex.org/W3195649134","https://openalex.org/W2366906938","https://openalex.org/W2281498195","https://openalex.org/W2349391998","https://openalex.org/W4205655149","https://openalex.org/W2017526120","https://openalex.org/W2610664080","https://openalex.org/W2000775715","https://openalex.org/W4292830139","https://openalex.org/W4319309705"],"abstract_inverted_index":{"In":[0],"handball":[1,38,56,122,185,190],"videos":[2],"recorded":[3],"during":[4,189],"the":[5,12,15,30,36,95,105,115,135,158,174],"training,":[6],"multiple":[7],"players":[8,27,49,87,107],"are":[9,59,108,124,180],"present":[10,88],"in":[11,89,129,134],"scene":[13],"at":[14],"same":[16],"time.":[17],"Although":[18],"they":[19],"all":[20,26],"might":[21],"move":[22],"and":[23,58,92,132,145,162,169,177],"interact,":[24],"not":[25],"contribute":[28],"to":[29,46],"currently":[31],"relevant":[32],"exercise":[33],"nor":[34],"practice":[35],"given":[37,55],"techniques.":[39],"The":[40,171],"goal":[41],"of":[42,104,117,173],"this":[43],"experiment":[44],"is":[45,64,75,112],"automatically":[47],"determine":[48,102],"on":[50,167,182],"training":[51,191],"footage":[52],"that":[53,77],"perform":[54],"techniques":[57],"therefore":[60],"considered":[61],"active.":[62],"It":[63],"a":[65,71,183],"very":[66],"challenging":[67],"task":[68],"for":[69],"which":[70,103],"precise":[72],"object":[73,160],"detector":[74,161],"needed":[76,113],"can":[78],"handle":[79],"cluttered":[80],"scenes":[81],"with":[82,85],"poor":[83],"illumination,":[84],"many":[86,121],"different":[90],"sizes":[91],"distances":[93],"from":[94],"camera,":[96],"partially":[97],"occluded,":[98],"moving":[99],"fast.":[100],"To":[101],"detected":[106],"active,":[109],"additional":[110],"information":[111],"about":[114],"level":[116],"player":[118,154],"activity.":[119],"Since":[120],"actions":[123],"characterized":[125],"by":[126],"considerable":[127],"changes":[128],"speed,":[130],"position,":[131],"variations":[133],"player's":[136],"appearance,":[137],"we":[138,150],"propose":[139,151],"using":[140],"spatio-temporal":[141],"interest":[142],"points":[143],"(STIPs)":[144],"optical":[146],"flow":[147],"(OF).":[148],"Therefore,":[149],"an":[152],"active":[153],"detection":[155],"method":[156,176],"combining":[157],"YOLO":[159],"two":[163],"activity":[164,178],"measures":[165,179],"based":[166],"STIPs":[168],"OF.":[170],"performance":[172],"proposed":[175],"evaluated":[181],"custom":[184],"video":[186],"dataset":[187],"acquired":[188],"lessons.":[192]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
