{"id":"https://openalex.org/W3108647877","doi":"https://doi.org/10.1109/iicaiet49801.2020.9257863","title":"Human Action Recognition with Sparse Autoencoder and Histogram of Oriented Gradients","display_name":"Human Action Recognition with Sparse Autoencoder and Histogram of Oriented Gradients","publication_year":2020,"publication_date":"2020-09-26","ids":{"openalex":"https://openalex.org/W3108647877","doi":"https://doi.org/10.1109/iicaiet49801.2020.9257863","mag":"3108647877"},"language":"en","primary_location":{"id":"doi:10.1109/iicaiet49801.2020.9257863","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iicaiet49801.2020.9257863","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 2nd International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","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/A5018784339","display_name":"Pooi Shiang Tan","orcid":null},"institutions":[{"id":"https://openalex.org/I173029219","display_name":"Multimedia University","ror":"https://ror.org/04zrbnc33","country_code":"MY","type":"education","lineage":["https://openalex.org/I173029219"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Pooi Shiang Tan","raw_affiliation_strings":["Faculty of Information Science & Technology, Multimedia University, Melaka, Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Information Science & Technology, Multimedia University, Melaka, Malaysia","institution_ids":["https://openalex.org/I173029219"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017532046","display_name":"Kian Ming Lim","orcid":"https://orcid.org/0000-0003-1929-7978"},"institutions":[{"id":"https://openalex.org/I173029219","display_name":"Multimedia University","ror":"https://ror.org/04zrbnc33","country_code":"MY","type":"education","lineage":["https://openalex.org/I173029219"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Kian Ming Lim","raw_affiliation_strings":["Faculty of Information Science & Technology, Multimedia University, Melaka, Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Information Science & Technology, Multimedia University, Melaka, Malaysia","institution_ids":["https://openalex.org/I173029219"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086127398","display_name":"Chin Poo Lee","orcid":"https://orcid.org/0000-0003-3679-8977"},"institutions":[{"id":"https://openalex.org/I173029219","display_name":"Multimedia University","ror":"https://ror.org/04zrbnc33","country_code":"MY","type":"education","lineage":["https://openalex.org/I173029219"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Chin Poo Lee","raw_affiliation_strings":["Faculty of Information Science & Technology, Multimedia University, Melaka, Malaysia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Information Science & Technology, Multimedia University, Melaka, Malaysia","institution_ids":["https://openalex.org/I173029219"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.5873,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.7017541,"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":"5"},"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9979000091552734,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9961000084877014,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.8480765223503113},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.7991695404052734},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7485948801040649},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6881614923477173},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.6805535554885864},{"id":"https://openalex.org/keywords/histogram-of-oriented-gradients","display_name":"Histogram of oriented gradients","score":0.6345921754837036},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5781320929527283},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5220515727996826},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5121331214904785},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49865293502807617},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.46165525913238525},{"id":"https://openalex.org/keywords/grayscale","display_name":"Grayscale","score":0.4612959623336792},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.433213472366333},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.38403332233428955}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8480765223503113},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7991695404052734},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7485948801040649},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6881614923477173},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.6805535554885864},{"id":"https://openalex.org/C17426736","wikidata":"https://www.wikidata.org/wiki/Q419918","display_name":"Histogram of oriented gradients","level":4,"score":0.6345921754837036},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5781320929527283},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5220515727996826},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5121331214904785},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49865293502807617},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.46165525913238525},{"id":"https://openalex.org/C78201319","wikidata":"https://www.wikidata.org/wiki/Q685727","display_name":"Grayscale","level":3,"score":0.4612959623336792},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.433213472366333},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.38403332233428955},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iicaiet49801.2020.9257863","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iicaiet49801.2020.9257863","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 2nd International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","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":26,"referenced_works":["https://openalex.org/W28988658","https://openalex.org/W1522734439","https://openalex.org/W1686810756","https://openalex.org/W1947481528","https://openalex.org/W1999789440","https://openalex.org/W2003543060","https://openalex.org/W2010399676","https://openalex.org/W2016053056","https://openalex.org/W2027020658","https://openalex.org/W2058079053","https://openalex.org/W2063153269","https://openalex.org/W2068611653","https://openalex.org/W2097117768","https://openalex.org/W2100686575","https://openalex.org/W2107105977","https://openalex.org/W2125556102","https://openalex.org/W2132734311","https://openalex.org/W2138232383","https://openalex.org/W2166346495","https://openalex.org/W2235034809","https://openalex.org/W2345600632","https://openalex.org/W2581582378","https://openalex.org/W2806990378","https://openalex.org/W2914599816","https://openalex.org/W2951183276","https://openalex.org/W6679404632"],"related_works":["https://openalex.org/W2060518359","https://openalex.org/W2772780115","https://openalex.org/W2592385986","https://openalex.org/W2134786086","https://openalex.org/W4281924768","https://openalex.org/W1528445814","https://openalex.org/W1576462183","https://openalex.org/W2550539038","https://openalex.org/W2767563364","https://openalex.org/W2380902646"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,43,133],"video-based":[4],"human":[5,36],"action":[6,38],"recognition":[7,203],"method":[8],"leveraging":[9],"deep":[10,156,185],"learning":[11,157,186],"model.":[12],"Prior":[13],"to":[14,61,103,116,139,144],"the":[15,18,30,48,58,62,68,77,82,90,94,104,118,125,130,141,150,155,183,192],"filtering":[16,63],"phase,":[17,67,132],"input":[19,59,91],"images":[20,99],"are":[21,39,71,100],"pre-processed":[22],"by":[23,42],"converting":[24],"them":[25],"into":[26],"grayscale":[27],"images.":[28,79,127],"Thereafter,":[29],"region":[31,49],"of":[32,50,110,124,154,205],"interest":[33,51],"that":[34,182],"contains":[35],"performing":[37],"cropped":[40],"out":[41],"pre-trained":[44],"pedestrian":[45],"detector.":[46],"Next,":[47],"will":[52],"be":[53],"resized":[54],"and":[55,93,120,171,197,208],"passed":[56,102],"as":[57],"image":[60,92],"phase.":[64,107],"In":[65],"this":[66],"filter":[69,83,95],"kernels":[70],"trained":[72],"using":[73],"Sparse":[74],"Autoencoder":[75],"on":[76,149,161,191],"natural":[78],"After":[80],"obtaining":[81],"kernels,":[84],"convolution":[85],"operation":[86],"is":[87,114,137,159],"performed":[88],"in":[89,129],"kernels.":[96],"The":[97,108,152,178],"filtered":[98,126],"then":[101],"feature":[105],"extraction":[106],"Histogram":[109],"Oriented":[111],"Gradients":[112],"descriptor":[113],"used":[115],"encode":[117],"local":[119],"global":[121],"texture":[122],"information":[123],"Lastly,":[128],"classification":[131],"Modified":[134],"Hausdorff":[135],"Distance":[136],"applied":[138],"classify":[140],"test":[142],"sample":[143],"its":[145],"nearest":[146],"match":[147],"based":[148],"histograms.":[151],"performance":[153],"algorithm":[158,187],"evaluated":[160],"three":[162],"benchmark":[163],"datasets,":[164],"namely":[165],"Weizmann":[166,193],"Action":[167,176,200],"Dataset,":[168,194],"CAD-60":[169,195],"Dataset":[170,196,201],"Multimedia":[172],"University":[173],"(MMU)":[174],"Human":[175,199],"Dataset.":[177],"experimental":[179],"results":[180],"show":[181],"proposed":[184],"outperforms":[188],"other":[189],"methods":[190],"MMU":[198],"with":[202],"rates":[204],"100%,":[206],"88.24%":[207],"99.5%":[209],"respectively.":[210]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
