{"id":"https://openalex.org/W1997018215","doi":"https://doi.org/10.1109/icmew.2013.6618448","title":"A spatio-temporal interest point detector based on vorticity for action recognition","display_name":"A spatio-temporal interest point detector based on vorticity for action recognition","publication_year":2013,"publication_date":"2013-07-01","ids":{"openalex":"https://openalex.org/W1997018215","doi":"https://doi.org/10.1109/icmew.2013.6618448","mag":"1997018215"},"language":"en","primary_location":{"id":"doi:10.1109/icmew.2013.6618448","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew.2013.6618448","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101504771","display_name":"Yuanbo Chen","orcid":"https://orcid.org/0009-0001-0697-7045"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanbo Chen","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","Sch. of Inf. & Commun. Eng., Beijing Univ. of Posts & Telecommun., Beijing, , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Sch. of Inf. & Commun. Eng., Beijing Univ. of Posts & Telecommun., Beijing, , China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101540014","display_name":"Zhixuan Li","orcid":"https://orcid.org/0009-0003-7215-3209"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhixuan Li","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","Sch. of Inf. & Commun. Eng., Beijing Univ. of Posts & Telecommun., Beijing, , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Sch. of Inf. & Commun. Eng., Beijing Univ. of Posts & Telecommun., Beijing, , China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101507341","display_name":"Xin Guo","orcid":"https://orcid.org/0000-0003-4153-4642"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xin Guo","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","Sch. of Inf. & Commun. Eng., Beijing Univ. of Posts & Telecommun., Beijing, , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Sch. of Inf. & Commun. Eng., Beijing Univ. of Posts & Telecommun., Beijing, , China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101099912","display_name":"Yanyun Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanyun Zhao","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing Key Laboratory of Network System and Network Culture, Beijing University of Posts and Telecommunications, Beijing, China","Sch. of Inf. & Commun. Eng., Beijing Univ. of Posts & Telecommun., Beijing, , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing Key Laboratory of Network System and Network Culture, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Sch. of Inf. & Commun. Eng., Beijing Univ. of Posts & Telecommun., Beijing, , China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5109683899","display_name":"Anni Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Anni Cai","raw_affiliation_strings":["School of Information and Communication Engineering, Beijing Key Laboratory of Network System and Network Culture, Beijing University of Posts and Telecommunications, Beijing, China","Sch. of Inf. & Commun. Eng., Beijing Univ. of Posts & Telecommun., Beijing, , China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Information and Communication Engineering, Beijing Key Laboratory of Network System and Network Culture, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]},{"raw_affiliation_string":"Sch. of Inf. & Commun. Eng., Beijing Univ. of Posts & Telecommun., Beijing, , China","institution_ids":["https://openalex.org/I139759216"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I139759216"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":1.0,"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":1.0,"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":0.9952999949455261,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9945999979972839,"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/detector","display_name":"Detector","score":0.7378730177879333},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.7209445834159851},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7064750790596008},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6878292560577393},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6464102864265442},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.609577476978302},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5225785970687866},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.47360777854919434},{"id":"https://openalex.org/keywords/interest-point-detection","display_name":"Interest point detection","score":0.4712505638599396},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4681703448295593},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.46532246470451355},{"id":"https://openalex.org/keywords/computational-complexity-theory","display_name":"Computational complexity theory","score":0.4507744312286377},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.4313390254974365},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4071108102798462},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.28740185499191284},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2224099040031433},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.20170095562934875},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.13293597102165222},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.08720389008522034},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.07171645760536194}],"concepts":[{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.7378730177879333},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.7209445834159851},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7064750790596008},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6878292560577393},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6464102864265442},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.609577476978302},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5225785970687866},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.47360777854919434},{"id":"https://openalex.org/C38785706","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Interest point detection","level":5,"score":0.4712505638599396},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4681703448295593},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.46532246470451355},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.4507744312286377},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.4313390254974365},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4071108102798462},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.28740185499191284},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2224099040031433},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.20170095562934875},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.13293597102165222},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.08720389008522034},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.07171645760536194},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","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/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"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":1,"locations":[{"id":"doi:10.1109/icmew.2013.6618448","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmew.2013.6618448","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 IEEE International Conference on Multimedia and Expo Workshops (ICMEW)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1489737693","https://openalex.org/W1513753641","https://openalex.org/W1595717062","https://openalex.org/W1625255723","https://openalex.org/W1755205674","https://openalex.org/W1970453205","https://openalex.org/W1979606776","https://openalex.org/W1993229407","https://openalex.org/W2003543060","https://openalex.org/W2024868105","https://openalex.org/W2032266162","https://openalex.org/W2063153269","https://openalex.org/W2073605108","https://openalex.org/W2075280134","https://openalex.org/W2101194540","https://openalex.org/W2119799051","https://openalex.org/W2126574503","https://openalex.org/W2146776177","https://openalex.org/W2172207578","https://openalex.org/W2533739470","https://openalex.org/W3141021069","https://openalex.org/W4249279051","https://openalex.org/W6635755983","https://openalex.org/W6636494156","https://openalex.org/W6658482064"],"related_works":["https://openalex.org/W1979041948","https://openalex.org/W4297270893","https://openalex.org/W2577671007","https://openalex.org/W3091300685","https://openalex.org/W2912100719","https://openalex.org/W2331280411","https://openalex.org/W2963330455","https://openalex.org/W1591216093","https://openalex.org/W2783931899","https://openalex.org/W4225597351"],"abstract_inverted_index":{"How":[0],"to":[1],"separate":[2],"foreground":[3],"from":[4],"camera":[5,46,72],"and":[6,38,91,117,137,157,159,167],"background":[7],"motions":[8],"is":[9,61,155],"a":[10,51,161],"difficult":[11],"problem":[12],"for":[13],"human":[14],"action":[15],"recognition":[16,165],"in":[17,42],"unconstrained":[18],"environments.":[19],"Although":[20],"the":[21,85,97,125,146],"existing":[22],"interest":[23,54,79],"point":[24,55,107],"based":[25,57],"methods":[26],"have":[27],"shown":[28],"attractive":[29],"results,":[30],"they":[31],"always":[32],"come":[33],"with":[34,45,101,124,142,150],"high":[35],"computational":[36,168],"complexity":[37],"lose":[39],"their":[40],"power":[41],"cluttered":[43],"field":[44],"motion.":[47],"In":[48],"this":[49],"paper,":[50],"new":[52],"spatio-temporal":[53,78],"detector":[56,99],"on":[58,89],"flow":[59],"vorticity":[60],"proposed,":[62],"which":[63],"can":[64],"not":[65],"only":[66],"suppress":[67],"most":[68],"of":[69,71,84],"effects":[70],"motion":[73],"but":[74],"also":[75,138],"provide":[76],"prominent":[77],"points":[80],"around":[81],"key":[82],"positions":[83],"moving":[86],"foreground.":[87],"Experiments":[88],"KTH":[90],"UCF":[92],"sports":[93],"datasets":[94],"demonstrate":[95],"that":[96],"proposed":[98,126],"combined":[100,123],"HOG/HOF":[102,116],"descriptors":[103],"outperforms":[104],"four":[105],"popular":[106],"detectors.":[108],"Moreover,":[109],"when":[110],"rich":[111],"descriptors,":[112],"such":[113],"as":[114],"trajectory,":[115],"MBH":[118],"(Motion":[119],"Boundary":[120],"Histogram),":[121],"are":[122],"detector,":[127],"our":[128],"approach":[129,154],"offers":[130],"better":[131],"results":[132],"than":[133,144],"other":[134],"state-of-the-art":[135],"methods,":[136],"achieves":[139],"comparable":[140],"performance":[141],"less":[143],"half":[145],"computation":[147],"time":[148],"compared":[149],"dense":[151],"sampling.":[152],"Our":[153],"simple":[156],"effective,":[158],"manifests":[160],"good":[162],"tradeoff":[163],"between":[164],"accuracy":[166],"complexity.":[169]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":2},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}