{"id":"https://openalex.org/W2746908100","doi":"https://doi.org/10.1109/aipr.2016.8010602","title":"Hierarchical temporal and spatial memory for gait pattern recognition","display_name":"Hierarchical temporal and spatial memory for gait pattern recognition","publication_year":2016,"publication_date":"2016-10-01","ids":{"openalex":"https://openalex.org/W2746908100","doi":"https://doi.org/10.1109/aipr.2016.8010602","mag":"2746908100"},"language":"en","primary_location":{"id":"doi:10.1109/aipr.2016.8010602","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aipr.2016.8010602","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","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/A5079001083","display_name":"Jianghao Shen","orcid":"https://orcid.org/0000-0003-2818-1432"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jianghao Shen","raw_affiliation_strings":["Departments of Electrical and Computer Engineering, George Washington University, Washington D.C., USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Departments of Electrical and Computer Engineering, George Washington University, Washington D.C., USA","institution_ids":["https://openalex.org/I193531525"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071064016","display_name":"Murray H. Loew","orcid":"https://orcid.org/0000-0002-1255-9341"},"institutions":[{"id":"https://openalex.org/I193531525","display_name":"George Washington University","ror":"https://ror.org/00y4zzh67","country_code":"US","type":"education","lineage":["https://openalex.org/I193531525"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Murray Loew","raw_affiliation_strings":["Departments of Biomedical Engineering, George Washington University, Washington D.C., USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Departments of Biomedical Engineering, George Washington University, Washington D.C., USA","institution_ids":["https://openalex.org/I193531525"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.21411791,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9998999834060669,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9857000112533569,"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":0.9542999863624573,"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/concatenation","display_name":"Concatenation (mathematics)","score":0.7677838802337646},{"id":"https://openalex.org/keywords/gait","display_name":"Gait","score":0.7045328617095947},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6694836616516113},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6189882755279541},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.6126455664634705},{"id":"https://openalex.org/keywords/hidden-markov-model","display_name":"Hidden Markov model","score":0.5898785591125488},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5849670767784119},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5725241899490356},{"id":"https://openalex.org/keywords/extension","display_name":"Extension (predicate logic)","score":0.5121116638183594},{"id":"https://openalex.org/keywords/temporal-database","display_name":"Temporal database","score":0.4752338230609894},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2365029752254486},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.20323118567466736}],"concepts":[{"id":"https://openalex.org/C87619178","wikidata":"https://www.wikidata.org/wiki/Q126002","display_name":"Concatenation (mathematics)","level":2,"score":0.7677838802337646},{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.7045328617095947},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6694836616516113},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6189882755279541},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.6126455664634705},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.5898785591125488},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5849670767784119},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5725241899490356},{"id":"https://openalex.org/C2778029271","wikidata":"https://www.wikidata.org/wiki/Q5421931","display_name":"Extension (predicate logic)","level":2,"score":0.5121116638183594},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.4752338230609894},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2365029752254486},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.20323118567466736},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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},{"id":"https://openalex.org/C42407357","wikidata":"https://www.wikidata.org/wiki/Q521","display_name":"Physiology","level":1,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/aipr.2016.8010602","is_oa":false,"landing_page_url":"https://doi.org/10.1109/aipr.2016.8010602","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W1595098149","https://openalex.org/W1636244751","https://openalex.org/W1999192586","https://openalex.org/W2016053056","https://openalex.org/W2062036973","https://openalex.org/W2113408265","https://openalex.org/W2167682686","https://openalex.org/W2287948962","https://openalex.org/W2307856239","https://openalex.org/W6635635134","https://openalex.org/W6677051090"],"related_works":["https://openalex.org/W2373577936","https://openalex.org/W4221148444","https://openalex.org/W4387678054","https://openalex.org/W2389596151","https://openalex.org/W3095575180","https://openalex.org/W4306784355","https://openalex.org/W2169308097","https://openalex.org/W4246226292","https://openalex.org/W3091984855","https://openalex.org/W2150768546"],"abstract_inverted_index":{"This":[0,111],"research":[1],"extends":[2],"the":[3,32,41,46,57,61,69,73,76,109],"Hierarchical":[4],"Temporal":[5],"Memory":[6],"(HTM)":[7],"algorithm":[8],"and":[9,37,40,123],"applies":[10],"it":[11],"to":[12,50,107,130],"gait":[13,16],"recognition.":[14],"The":[15,27],"sequence":[17],"first":[18],"is":[19,72,115],"decomposed":[20],"into":[21],"temporal":[22,58,105],"sub-sequences":[23],"of":[24,34,60,75,78,94,98,101,120],"spatial":[25],"sub-regions.":[26],"sub-sequence":[28],"are":[29,43],"defined":[30,44],"as":[31,45],"period":[33],"one":[35],"step":[36],"half":[38],"step,":[39],"sub-regions":[42],"areas":[47],"that":[48],"correspond":[49],"body":[51,62],"parts.":[52],"Each":[53],"sub-area":[54],"will":[55],"learn":[56],"variation":[59],"part":[63],"by":[64],"constructing":[65],"Markov":[66],"Chains.":[67],"Finally,":[68],"classification":[70],"result":[71],"concatenation":[74],"beliefs":[77],"all":[79],"sub-areas.":[80,95],"Unlike":[81],"other":[82,131],"methods,":[83],"which":[84],"use":[85],"gait-specific":[86],"features,":[87],"our":[88],"method":[89],"uses":[90],"only":[91],"image":[92],"patches":[93],"Our":[96],"extension":[97],"previous":[99],"versions":[100],"HTM":[102],"provides":[103],"hierarchical":[104],"inference":[106],"cumulate":[108],"belief.":[110],"generalized":[112],"new":[113],"approach":[114],"evaluated":[116],"on":[117],"a":[118],"dataset":[119],"151":[121],"subjects":[122],"two":[124],"walking":[125],"conditions.":[126],"It":[127],"compares":[128],"favorably":[129],"current":[132],"methods":[133],"used":[134],"with":[135],"those":[136],"data,":[137],"without":[138],"requiring":[139],"problem-specific":[140],"inputs.":[141]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
