{"id":"https://openalex.org/W3093565455","doi":"https://doi.org/10.1109/access.2020.3032533","title":"LaM-2SRN: A Method Which Can Enhance Local Features and Detect Moving Objects for Action Recognition","display_name":"LaM-2SRN: A Method Which Can Enhance Local Features and Detect Moving Objects for Action Recognition","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3093565455","doi":"https://doi.org/10.1109/access.2020.3032533","mag":"3093565455"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.3032533","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3032533","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09233362.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09233362.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015697464","display_name":"Yangyang Qiao","orcid":"https://orcid.org/0000-0002-9209-0343"},"institutions":[{"id":"https://openalex.org/I114117164","display_name":"University of Science and Technology Liaoning","ror":"https://ror.org/03grx7119","country_code":"CN","type":"education","lineage":["https://openalex.org/I114117164"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yangyang Qiao","raw_affiliation_strings":["School of Electronics and Information Technology, University of Science and Technology Liaoning, Anshan, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Technology, University of Science and Technology Liaoning, Anshan, China","institution_ids":["https://openalex.org/I114117164"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062865846","display_name":"Whenhua Cui","orcid":null},"institutions":[{"id":"https://openalex.org/I114117164","display_name":"University of Science and Technology Liaoning","ror":"https://ror.org/03grx7119","country_code":"CN","type":"education","lineage":["https://openalex.org/I114117164"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Whenhua Cui","raw_affiliation_strings":["School of Electronics and Information Technology, University of Science and Technology Liaoning, Anshan, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Technology, University of Science and Technology Liaoning, Anshan, China","institution_ids":["https://openalex.org/I114117164"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100370985","display_name":"Tianwei Shi","orcid":"https://orcid.org/0000-0003-2148-8108"},"institutions":[{"id":"https://openalex.org/I114117164","display_name":"University of Science and Technology Liaoning","ror":"https://ror.org/03grx7119","country_code":"CN","type":"education","lineage":["https://openalex.org/I114117164"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tianwei Shi","raw_affiliation_strings":["School of Electronics and Information Technology, University of Science and Technology Liaoning, Anshan, China"],"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Technology, University of Science and Technology Liaoning, Anshan, China","institution_ids":["https://openalex.org/I114117164"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5015697464"],"corresponding_institution_ids":["https://openalex.org/I114117164"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.2931,"has_fulltext":true,"cited_by_count":3,"citation_normalized_percentile":{"value":0.57286415,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"8","issue":null,"first_page":"192703","last_page":"192712"},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9979000091552734,"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":0.996999979019165,"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":0.8491311073303223},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.816512942314148},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8153381943702698},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6883898377418518},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5898656249046326},{"id":"https://openalex.org/keywords/clutter","display_name":"Clutter","score":0.5874451398849487},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5674682855606079},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.5417935848236084},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.4915347993373871},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.47204363346099854},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.43648669123649597},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.2768949866294861}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8491311073303223},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.816512942314148},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8153381943702698},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6883898377418518},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5898656249046326},{"id":"https://openalex.org/C132094186","wikidata":"https://www.wikidata.org/wiki/Q641585","display_name":"Clutter","level":3,"score":0.5874451398849487},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5674682855606079},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.5417935848236084},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.4915347993373871},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.47204363346099854},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.43648669123649597},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2768949866294861},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C554190296","wikidata":"https://www.wikidata.org/wiki/Q47528","display_name":"Radar","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.3032533","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3032533","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09233362.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:d5ac14be0f9a4de3b78f5876751080ee","is_oa":true,"landing_page_url":"https://doaj.org/article/d5ac14be0f9a4de3b78f5876751080ee","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 8, Pp 192703-192712 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.3032533","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.3032533","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09233362.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3093565455.pdf","grobid_xml":"https://content.openalex.org/works/W3093565455.grobid-xml"},"referenced_works_count":48,"referenced_works":["https://openalex.org/W24089286","https://openalex.org/W1522734439","https://openalex.org/W1686810756","https://openalex.org/W1926645898","https://openalex.org/W2012592962","https://openalex.org/W2020163092","https://openalex.org/W2068611653","https://openalex.org/W2105101328","https://openalex.org/W2126579184","https://openalex.org/W2127070222","https://openalex.org/W2133665775","https://openalex.org/W2139212933","https://openalex.org/W2158169396","https://openalex.org/W2194775991","https://openalex.org/W2235034809","https://openalex.org/W2462996230","https://openalex.org/W2554408731","https://openalex.org/W2604906478","https://openalex.org/W2739179646","https://openalex.org/W2765793020","https://openalex.org/W2791307013","https://openalex.org/W2868292291","https://openalex.org/W2887446291","https://openalex.org/W2897989494","https://openalex.org/W2899368224","https://openalex.org/W2913553303","https://openalex.org/W2926527602","https://openalex.org/W2940912530","https://openalex.org/W2963524571","https://openalex.org/W2963750390","https://openalex.org/W2963820951","https://openalex.org/W2967105321","https://openalex.org/W3001937790","https://openalex.org/W3010309966","https://openalex.org/W3013318875","https://openalex.org/W3015483809","https://openalex.org/W3023755016","https://openalex.org/W3033852812","https://openalex.org/W3038032083","https://openalex.org/W3099938251","https://openalex.org/W3121695629","https://openalex.org/W3123784868","https://openalex.org/W3141200356","https://openalex.org/W4294557331","https://openalex.org/W6600983433","https://openalex.org/W6684983439","https://openalex.org/W6735888532","https://openalex.org/W6910562601"],"related_works":["https://openalex.org/W2130674020","https://openalex.org/W2093748878","https://openalex.org/W2333771223","https://openalex.org/W2120056845","https://openalex.org/W1981531423","https://openalex.org/W2035264131","https://openalex.org/W1679012645","https://openalex.org/W1925461966","https://openalex.org/W3036468168","https://openalex.org/W2969228573"],"abstract_inverted_index":{"Visual":[0],"attention":[1,82],"mechanism":[2,32],"has":[3],"been":[4],"widely":[5],"used":[6,85,114],"in":[7,15,120,158,218],"computer":[8],"vision":[9],"and":[10,37,53,60,133,168,177,246],"plays":[11],"a":[12,27,39,148],"vital":[13],"role":[14],"the":[16,74,88,93,98,110,117,121,125,130,138,143,153,159,164,169,174,189,198,208,214,219,223,248,258],"research":[17],"of":[18,67,92,100,129,142,197],"human":[19,34,94,144,209],"action":[20,35],"recognition.":[21],"In":[22],"this":[23,68,203],"paper,":[24],"we":[25,162],"explore":[26],"novel":[28],"moving":[29,118,131,215],"target":[30,55,119,200],"detection":[31,201],"for":[33,58,191,240],"recognition":[36],"propose":[38],"new":[40],"3D":[41,175],"CNN":[42,176,179,225],"(3D":[43],"Convolutional":[44],"Neural":[45],"Network)":[46],"model,":[47],"dubbed":[48],"LaM-2SRN":[49,254],"(Local":[50],"Features":[51],"Enhanced":[52],"Moving":[54],"detected":[56],"2Stream-ResNet)":[57],"extracting":[59],"learning":[61],"attention-enhanced":[62],"spatiotemporal":[63],"features.":[64],"The":[65],"contributions":[66],"paper":[69,204],"are":[70],"as":[71,106,188],"follow:":[72],"First,":[73],"traditional":[75],"CAM":[76],"(Class":[77],"Activation":[78],"Map)":[79],"based":[80],"visual":[81],"algorithm":[83,112],"is":[84,113,156,255],"to":[86,115,146,182,257],"obtain":[87,147,228],"optical":[89,102,126,139],"flow":[90,103,127,140],"information":[91,104,128,141,155,232],"region,":[95,145],"thus":[96],"eliminating":[97],"influence":[99],"irrelevant":[101],"(such":[105],"background":[107],"clutter).":[108],"Second,":[109],"ViBe":[111],"identify":[116],"continuous":[122],"frame,":[123,161],"retain":[124],"target,":[132,210],"make":[134],"it":[135],"complement":[136],"with":[137],"complete":[149,230],"motion":[150,154,231],"descriptor.":[151],"After":[152],"marked":[157,165],"video":[160,166,171,192,238],"put":[163],"frames":[167,172],"original":[170],"into":[173],"2D":[178],"models":[180],"respectively,":[181],"acquired":[183],"mixed":[184],"descriptor,":[185],"which":[186],"serves":[187],"basis":[190],"classification.":[193],"Different":[194],"from":[195,233],"most":[196],"previous":[199,259],"algorithms,":[202],"not":[205],"only":[206],"detects":[207,213],"but":[211],"also":[212],"foreground":[216],"targets":[217],"video,":[220],"so":[221],"that":[222,252],"pre-trained":[224],"model":[226],"can":[227],"more":[229],"videos.":[234],"We":[235],"use":[236],"RGB-only":[237],"data":[239],"evaluation":[241],"on":[242],"two":[243],"benchmarks:":[244],"UCF101":[245],"HMDB51,":[247],"experimental":[249],"results":[250],"demonstrate":[251],"our":[253],"comparable":[256],"state-of-the-art":[260],"algorithms.":[261]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}