{"id":"https://openalex.org/W3207806886","doi":"https://doi.org/10.1145/3478472.3478476","title":"Video Abnormal Behavior Detection Based on Optical Flow Method and Convolutional Neural Network","display_name":"Video Abnormal Behavior Detection Based on Optical Flow Method and Convolutional Neural Network","publication_year":2021,"publication_date":"2021-05-07","ids":{"openalex":"https://openalex.org/W3207806886","doi":"https://doi.org/10.1145/3478472.3478476","mag":"3207806886"},"language":"en","primary_location":{"id":"doi:10.1145/3478472.3478476","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3478472.3478476","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Human-Machine Interaction","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/A5015335247","display_name":"Zhengyan Liu","orcid":"https://orcid.org/0009-0001-5750-1821"},"institutions":[{"id":"https://openalex.org/I13175533","display_name":"Fuyang Normal University","ror":"https://ror.org/02njz9p87","country_code":"CN","type":"education","lineage":["https://openalex.org/I13175533"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zheng-yan Liu","raw_affiliation_strings":["Fuyang Normal University, China"],"affiliations":[{"raw_affiliation_string":"Fuyang Normal University, China","institution_ids":["https://openalex.org/I13175533"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003183390","display_name":"Han-lin Xia","orcid":null},"institutions":[{"id":"https://openalex.org/I13175533","display_name":"Fuyang Normal University","ror":"https://ror.org/02njz9p87","country_code":"CN","type":"education","lineage":["https://openalex.org/I13175533"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Han-lin Xia","raw_affiliation_strings":["Fuyang Normal University, China"],"affiliations":[{"raw_affiliation_string":"Fuyang Normal University, China","institution_ids":["https://openalex.org/I13175533"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5015335247"],"corresponding_institution_ids":["https://openalex.org/I13175533"],"apc_list":null,"apc_paid":null,"fwci":0.136,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.55940745,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"13","last_page":"17"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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":1.0,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9921000003814697,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.9889000058174133,"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/optical-flow","display_name":"Optical flow","score":0.8949735760688782},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7875940799713135},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7737131118774414},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6774122714996338},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6754412651062012},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5166014432907104},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5137220621109009},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47968339920043945},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.44959911704063416},{"id":"https://openalex.org/keywords/motion-detection","display_name":"Motion detection","score":0.4283153712749481},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.4230364263057709}],"concepts":[{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.8949735760688782},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7875940799713135},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7737131118774414},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6774122714996338},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6754412651062012},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5166014432907104},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5137220621109009},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47968339920043945},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.44959911704063416},{"id":"https://openalex.org/C2780624872","wikidata":"https://www.wikidata.org/wiki/Q852453","display_name":"Motion detection","level":3,"score":0.4283153712749481},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.4230364263057709},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3478472.3478476","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3478472.3478476","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 International Conference on Human-Machine Interaction","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.49000000953674316,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1890253021","https://openalex.org/W1969319493","https://openalex.org/W2096229530","https://openalex.org/W2108404684","https://openalex.org/W2110383222","https://openalex.org/W2114925581","https://openalex.org/W2117734404","https://openalex.org/W2125105611","https://openalex.org/W2164261375","https://openalex.org/W2164489414","https://openalex.org/W2256811964","https://openalex.org/W2526027614","https://openalex.org/W2788636619","https://openalex.org/W2940479409","https://openalex.org/W2964232409"],"related_works":["https://openalex.org/W4286646204","https://openalex.org/W2564375980","https://openalex.org/W3092720353","https://openalex.org/W1632063848","https://openalex.org/W2005492187","https://openalex.org/W168225246","https://openalex.org/W2132221806","https://openalex.org/W2017155773","https://openalex.org/W2036630122","https://openalex.org/W2093542995"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,132],"new":[4],"algorithm":[5,109],"for":[6,56,60],"abnormal":[7,62,100,139],"behavior":[8,63,98,101,140],"detection":[9],"in":[10,84,135],"surveillance":[11],"video.":[12,104],"Firstly,":[13],"the":[14,25,30,34,43,51,66,68,80,85,96,103,114,125,136],"motion":[15,45,69,81],"information":[16,47,70,77,82],"image":[17,46,71,87],"of":[18,102,107,138],"each":[19],"frame":[20],"is":[21,48,110],"constructed":[22],"by":[23],"calculating":[24],"optical":[26,35,75],"flow":[27,36,76],"size":[28],"and":[29,41,58,99,128],"angle":[31],"difference":[32],"between":[33,38],"vectors":[37],"consecutive":[39],"frames,":[40],"then":[42],"obtained":[44],"input":[49],"into":[50],"convolutional":[52],"neural":[53],"network":[54],"(CNN)":[55],"training,":[57],"used":[59,116],"video":[61,86],"detection.":[64,141],"In":[65],"algorithm,":[67],"generated":[72],"based":[73],"on":[74,113],"can":[78],"provide":[79],"features":[83],"more":[88],"accurately,":[89],"which":[90],"makes":[91],"it":[92],"easier":[93],"to":[94],"distinguish":[95],"normal":[97],"The":[105],"experiment":[106],"this":[108],"carried":[111],"out":[112],"commonly":[115],"data":[117],"set":[118],"PETS":[119],"2009.":[120],"Experimental":[121],"results":[122],"show":[123],"that":[124],"proposed":[126],"method":[127],"other":[129],"algorithms":[130],"have":[131],"significant":[133],"improvement":[134],"accuracy":[137]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
