{"id":"https://openalex.org/W2196884876","doi":"https://doi.org/10.1080/10798587.2015.1095487","title":"Video Recognition of Human Fall Based on Spatiotemporal Features","display_name":"Video Recognition of Human Fall Based on Spatiotemporal Features","publication_year":2015,"publication_date":"2015-11-17","ids":{"openalex":"https://openalex.org/W2196884876","doi":"https://doi.org/10.1080/10798587.2015.1095487","mag":"2196884876"},"language":"en","primary_location":{"id":"doi:10.1080/10798587.2015.1095487","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10798587.2015.1095487","pdf_url":null,"source":{"id":"https://openalex.org/S40639465","display_name":"Intelligent Automation & Soft Computing","issn_l":"1079-8587","issn":["1079-8587","2326-005X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Automation & Soft Computing","raw_type":"journal-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/A5100437036","display_name":"Kai Wang","orcid":"https://orcid.org/0000-0002-6170-4744"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Kai Wang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Youjin Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Youjin Zhao","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073066762","display_name":"Qingyu Xiong","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Qingyu Xiong","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023687769","display_name":"Xiling Shen","orcid":"https://orcid.org/0000-0002-4978-3531"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiling Shen","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":null,"display_name":"Min Fan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Min Fan","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5002210013","display_name":"Min Gao","orcid":"https://orcid.org/0000-0003-0127-7477"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Min Gao","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5100437036"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.10376073,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"22","issue":"2","first_page":"303","last_page":"309"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9998999834060669,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9998999834060669,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9932000041007996,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11196","display_name":"Non-Invasive Vital Sign Monitoring","score":0.9901999831199646,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.9345983266830444},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5467350482940674},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.39811092615127563},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3525434732437134}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9345983266830444},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5467350482940674},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.39811092615127563},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3525434732437134}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1080/10798587.2015.1095487","is_oa":false,"landing_page_url":"https://doi.org/10.1080/10798587.2015.1095487","pdf_url":null,"source":{"id":"https://openalex.org/S40639465","display_name":"Intelligent Automation & Soft Computing","issn_l":"1079-8587","issn":["1079-8587","2326-005X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320547","host_organization_name":"Taylor & Francis","host_organization_lineage":["https://openalex.org/P4310320547"],"host_organization_lineage_names":["Taylor & Francis"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Intelligent Automation & Soft Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.4699999988079071,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W1505641881","https://openalex.org/W1601795611","https://openalex.org/W1663973292","https://openalex.org/W1967018481","https://openalex.org/W1971422403","https://openalex.org/W1971440247","https://openalex.org/W1976656107","https://openalex.org/W1985052560","https://openalex.org/W1999192586","https://openalex.org/W2001965006","https://openalex.org/W2002427501","https://openalex.org/W2007717933","https://openalex.org/W2013549628","https://openalex.org/W2020163092","https://openalex.org/W2020957915","https://openalex.org/W2028656089","https://openalex.org/W2030574544","https://openalex.org/W2032369862","https://openalex.org/W2032791935","https://openalex.org/W2034328688","https://openalex.org/W2052332753","https://openalex.org/W2060599388","https://openalex.org/W2076068958","https://openalex.org/W2087897412","https://openalex.org/W2088904018","https://openalex.org/W2098422462","https://openalex.org/W2113134263","https://openalex.org/W2120999040","https://openalex.org/W2138797044","https://openalex.org/W2139212933","https://openalex.org/W2145072179","https://openalex.org/W2148694408","https://openalex.org/W2148927972","https://openalex.org/W2151103935","https://openalex.org/W2154422044","https://openalex.org/W2158169396","https://openalex.org/W2158358659","https://openalex.org/W2171846896","https://openalex.org/W2177274842","https://openalex.org/W2473526392","https://openalex.org/W2496323672","https://openalex.org/W2533739470","https://openalex.org/W4249279051","https://openalex.org/W4255402332"],"related_works":["https://openalex.org/W2755342338","https://openalex.org/W1891287906","https://openalex.org/W2036807459","https://openalex.org/W2775347418","https://openalex.org/W1969923398","https://openalex.org/W2772917594","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2058170566"],"abstract_inverted_index":{"AbstractA":[0],"systematic":[1],"framework":[2],"for":[3,136],"recognizing":[4],"human":[5],"fall":[6,86,100,137],"from":[7,42],"video":[8,24,43,49,67,94],"is":[9,78],"presented":[10],"in":[11],"this":[12],"work.":[13],"For":[14],"the":[15,82,110,119,125],"foreground":[16],"extraction,":[17],"instead":[18],"of":[19,22,33],"remodeling":[20],"background":[21],"every":[23],"frame,":[25],"we":[26],"directly":[27],"extract":[28],"cuboids":[29],"that":[30],"are":[31],"composed":[32],"spatiotemporal":[34],"interest":[35],"points":[36],"detected":[37],"by":[38,60,104],"separable":[39],"linear":[40],"filter":[41],"sequences.":[44],"We":[45,108],"then":[46,91],"represent":[47],"these":[48],"patches":[50],"as":[51],"local":[52],"image":[53],"gradient":[54],"descriptors":[55],"with":[56],"greatly":[57],"reduced":[58],"dimensions":[59],"principle":[61],"component":[62],"analysis":[63],"(PCA).":[64],"From":[65],"labeled":[66],"patches,":[68],"a":[69,92],"supervised":[70],"learning":[71],"method":[72,112,127],"based":[73,117],"on":[74,113,118],"Gaussian":[75],"RBF":[76],"kernel":[77],"proposed":[79,126],"to":[80],"determine":[81],"maximum":[83],"margin":[84],"between":[85],"and":[87,90,128],"normal":[88,102],"activity,":[89],"novel":[93],"sequence":[95],"can":[96],"be":[97],"categorize":[98],"into":[99],"or":[101],"activity":[103],"an":[105],"optimal":[106],"hyperplane.":[107],"tested":[109],"above":[111],"datasets":[114],"set":[115],"up":[116],"LPO-CV":[120],"testing":[121],"paradigm,":[122],"which":[123],"verified":[124],"demonstrated":[129],"its":[130],"advantage":[131],"over":[132],"other":[133],"state-of-the-art":[134],"approaches":[135],"recognition.":[138]},"counts_by_year":[],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}