{"id":"https://openalex.org/W2186449605","doi":"https://doi.org/10.1109/mmsp.2015.7340857","title":"Human action recognition using temporal hierarchical pyramid of depth motion map and KECA","display_name":"Human action recognition using temporal hierarchical pyramid of depth motion map and KECA","publication_year":2015,"publication_date":"2015-10-01","ids":{"openalex":"https://openalex.org/W2186449605","doi":"https://doi.org/10.1109/mmsp.2015.7340857","mag":"2186449605"},"language":"en","primary_location":{"id":"doi:10.1109/mmsp.2015.7340857","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmsp.2015.7340857","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP)","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/A5021639083","display_name":"Nour El Din El Madany","orcid":null},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Nour El Din El Madany","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Ryerson University, Toronto, Ontario, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Ryerson University, Toronto, Ontario, Canada","institution_ids":["https://openalex.org/I530967"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100461963","display_name":"Yifeng He","orcid":"https://orcid.org/0000-0002-1700-3166"},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Yifeng He","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Ryerson University, Toronto, Ontario, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Ryerson University, Toronto, Ontario, Canada","institution_ids":["https://openalex.org/I530967"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001287866","display_name":"Ling Guan","orcid":"https://orcid.org/0000-0002-2681-2504"},"institutions":[{"id":"https://openalex.org/I530967","display_name":"Toronto Metropolitan University","ror":"https://ror.org/05g13zd79","country_code":"CA","type":"education","lineage":["https://openalex.org/I530967"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Ling Guan","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Ryerson University, Toronto, Ontario, Canada"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Ryerson University, Toronto, Ontario, Canada","institution_ids":["https://openalex.org/I530967"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5021639083"],"corresponding_institution_ids":["https://openalex.org/I530967"],"apc_list":null,"apc_paid":null,"fwci":1.841,"has_fulltext":false,"cited_by_count":15,"citation_normalized_percentile":{"value":0.90415731,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"7441","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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9991000294685364,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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":0.9986000061035156,"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":0.7751317024230957},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7372289299964905},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.6994425058364868},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.6932075023651123},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6163289546966553},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5374569892883301},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5250247120857239},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.5179337859153748},{"id":"https://openalex.org/keywords/gesture-recognition","display_name":"Gesture recognition","score":0.48638585209846497},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.466513991355896},{"id":"https://openalex.org/keywords/human-motion","display_name":"Human motion","score":0.4613606333732605},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.44771116971969604},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4249612092971802},{"id":"https://openalex.org/keywords/gesture","display_name":"Gesture","score":0.3550541400909424},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14524447917938232}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7751317024230957},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7372289299964905},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.6994425058364868},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.6932075023651123},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6163289546966553},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5374569892883301},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5250247120857239},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.5179337859153748},{"id":"https://openalex.org/C159437735","wikidata":"https://www.wikidata.org/wiki/Q1519524","display_name":"Gesture recognition","level":3,"score":0.48638585209846497},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.466513991355896},{"id":"https://openalex.org/C2986578859","wikidata":"https://www.wikidata.org/wiki/Q657632","display_name":"Human motion","level":3,"score":0.4613606333732605},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.44771116971969604},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4249612092971802},{"id":"https://openalex.org/C207347870","wikidata":"https://www.wikidata.org/wiki/Q371174","display_name":"Gesture","level":2,"score":0.3550541400909424},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14524447917938232},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mmsp.2015.7340857","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mmsp.2015.7340857","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE 17th International Workshop on Multimedia Signal Processing (MMSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7400000095367432,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W203345490","https://openalex.org/W1568156700","https://openalex.org/W1596216457","https://openalex.org/W1983363688","https://openalex.org/W1983705368","https://openalex.org/W1990596128","https://openalex.org/W1995784006","https://openalex.org/W2008824967","https://openalex.org/W2010676632","https://openalex.org/W2016240821","https://openalex.org/W2030061193","https://openalex.org/W2046013836","https://openalex.org/W2048821851","https://openalex.org/W2079447555","https://openalex.org/W2085735683","https://openalex.org/W2089439253","https://openalex.org/W2114361838","https://openalex.org/W2125073690","https://openalex.org/W2128859583","https://openalex.org/W2143267104","https://openalex.org/W2144380653","https://openalex.org/W2145546283","https://openalex.org/W2149803014","https://openalex.org/W2153635508","https://openalex.org/W2161969291","https://openalex.org/W2162915993","https://openalex.org/W2169251375","https://openalex.org/W2173046955","https://openalex.org/W4236055315","https://openalex.org/W6608276133","https://openalex.org/W6634103714","https://openalex.org/W6635654010","https://openalex.org/W6677137762","https://openalex.org/W6685306902","https://openalex.org/W6685520734"],"related_works":["https://openalex.org/W2902873204","https://openalex.org/W2185750513","https://openalex.org/W3147379364","https://openalex.org/W2010878661","https://openalex.org/W2026258298","https://openalex.org/W3204639664","https://openalex.org/W2970836791","https://openalex.org/W2805039731","https://openalex.org/W2989699735","https://openalex.org/W2608683086"],"abstract_inverted_index":{"Human":[0],"action":[1,23,65],"recognition":[2],"is":[3,52],"one":[4],"of":[5,33],"the":[6,39,43,56,61,87],"challenging":[7],"research":[8],"problems":[9],"in":[10],"computer":[11],"vision.":[12],"In":[13,45],"this":[14],"paper,":[15],"we":[16],"propose":[17],"a":[18,29,92],"novel":[19],"approach":[20,27],"for":[21,64],"human":[22],"recognition.":[24,66],"The":[25,67,82],"proposed":[26,68,88],"employs":[28],"temporal":[30,40],"hierarchical":[31],"pyramid":[32],"depth":[34],"motion":[35],"map":[36],"to":[37,54,59,97],"capture":[38],"variations":[41],"over":[42],"time.":[44],"addition,":[46],"Kernel":[47],"Entropy":[48],"Component":[49],"Analysis":[50],"(KECA)":[51],"used":[53],"reduce":[55],"dimension":[57],"and":[58,78],"enhance":[60],"discriminatory":[62],"power":[63],"method":[69,89],"was":[70],"evaluated":[71],"using":[72],"two":[73],"datasets,":[74],"MSR-Action":[75],"3D":[76,80],"dataset":[77],"MSR-Gesture":[79],"dataset.":[81],"experimental":[83],"results":[84],"demonstrated":[85],"that":[86],"can":[90],"achieve":[91],"higher":[93],"average":[94],"accuracy":[95],"compared":[96],"several":[98],"existing":[99],"methods.":[100]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}