{"id":"https://openalex.org/W2072062802","doi":"https://doi.org/10.1109/icmlc.2010.5580722","title":"A new method of gait recognition independent of view angle","display_name":"A new method of gait recognition independent of view angle","publication_year":2010,"publication_date":"2010-07-01","ids":{"openalex":"https://openalex.org/W2072062802","doi":"https://doi.org/10.1109/icmlc.2010.5580722","mag":"2072062802"},"language":"en","primary_location":{"id":"doi:10.1109/icmlc.2010.5580722","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2010.5580722","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 International Conference on Machine Learning and Cybernetics","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/A5109277500","display_name":"Han Su","orcid":null},"institutions":[{"id":"https://openalex.org/I5467274","display_name":"Akita Prefectural University","ror":"https://ror.org/05b1kx621","country_code":"JP","type":"education","lineage":["https://openalex.org/I5467274"]},{"id":"https://openalex.org/I63354593","display_name":"Sichuan Normal University","ror":"https://ror.org/043dxc061","country_code":"CN","type":"education","lineage":["https://openalex.org/I63354593"]}],"countries":["CN","JP"],"is_corresponding":false,"raw_author_name":"Han Su","raw_affiliation_strings":["Akita Prefectural University, Honjo, Japan","School of Computer Science, Sichuan Normal University, Chengdu, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Akita Prefectural University, Honjo, Japan","institution_ids":["https://openalex.org/I5467274"]},{"raw_affiliation_string":"School of Computer Science, Sichuan Normal University, Chengdu, China","institution_ids":["https://openalex.org/I63354593"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5080070181","display_name":"Guoyue Chen","orcid":"https://orcid.org/0000-0001-7928-9334"},"institutions":[{"id":"https://openalex.org/I5467274","display_name":"Akita Prefectural University","ror":"https://ror.org/05b1kx621","country_code":"JP","type":"education","lineage":["https://openalex.org/I5467274"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Guo-Yue Chen","raw_affiliation_strings":["Akita Prefectural University, Honjo, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Akita Prefectural University, Honjo, Japan","institution_ids":["https://openalex.org/I5467274"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.2174,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.60617384,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":"46","issue":null,"first_page":"3091","last_page":"3096"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":1.0,"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":1.0,"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":0.9869999885559082,"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":0.9825000166893005,"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/gait","display_name":"Gait","score":0.7561308145523071},{"id":"https://openalex.org/keywords/azimuth","display_name":"Azimuth","score":0.7183117866516113},{"id":"https://openalex.org/keywords/viewing-angle","display_name":"Viewing angle","score":0.6529510021209717},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6153427362442017},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6041539907455444},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5805705785751343},{"id":"https://openalex.org/keywords/background-subtraction","display_name":"Background subtraction","score":0.5783207416534424},{"id":"https://openalex.org/keywords/subtraction","display_name":"Subtraction","score":0.4544823169708252},{"id":"https://openalex.org/keywords/gait-analysis","display_name":"Gait analysis","score":0.4149465560913086},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3738883435726166},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2991018295288086},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.13696569204330444},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.1301945447921753}],"concepts":[{"id":"https://openalex.org/C151800584","wikidata":"https://www.wikidata.org/wiki/Q2370000","display_name":"Gait","level":2,"score":0.7561308145523071},{"id":"https://openalex.org/C159737794","wikidata":"https://www.wikidata.org/wiki/Q124274","display_name":"Azimuth","level":2,"score":0.7183117866516113},{"id":"https://openalex.org/C2776694159","wikidata":"https://www.wikidata.org/wiki/Q351676","display_name":"Viewing angle","level":3,"score":0.6529510021209717},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6153427362442017},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6041539907455444},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5805705785751343},{"id":"https://openalex.org/C32653426","wikidata":"https://www.wikidata.org/wiki/Q3813641","display_name":"Background subtraction","level":3,"score":0.5783207416534424},{"id":"https://openalex.org/C68060419","wikidata":"https://www.wikidata.org/wiki/Q40754","display_name":"Subtraction","level":2,"score":0.4544823169708252},{"id":"https://openalex.org/C173906292","wikidata":"https://www.wikidata.org/wiki/Q1493441","display_name":"Gait analysis","level":3,"score":0.4149465560913086},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3738883435726166},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2991018295288086},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.13696569204330444},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.1301945447921753},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C128019096","wikidata":"https://www.wikidata.org/wiki/Q83341","display_name":"Liquid-crystal display","level":2,"score":0.0},{"id":"https://openalex.org/C42407357","wikidata":"https://www.wikidata.org/wiki/Q521","display_name":"Physiology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icmlc.2010.5580722","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icmlc.2010.5580722","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 International Conference on Machine Learning and Cybernetics","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":20,"referenced_works":["https://openalex.org/W1485180327","https://openalex.org/W1600404837","https://openalex.org/W1977418735","https://openalex.org/W1979856851","https://openalex.org/W2034383054","https://openalex.org/W2100086166","https://openalex.org/W2114652514","https://openalex.org/W2116208049","https://openalex.org/W2116939210","https://openalex.org/W2120526922","https://openalex.org/W2120861453","https://openalex.org/W2128233502","https://openalex.org/W2129215140","https://openalex.org/W2135541996","https://openalex.org/W2150130015","https://openalex.org/W2165715280","https://openalex.org/W2170828496","https://openalex.org/W4285719527","https://openalex.org/W6635624922","https://openalex.org/W6676963212"],"related_works":["https://openalex.org/W3006474185","https://openalex.org/W2188430267","https://openalex.org/W2483195039","https://openalex.org/W2610698896","https://openalex.org/W2369265144","https://openalex.org/W2281797687","https://openalex.org/W2358411735","https://openalex.org/W2048211457","https://openalex.org/W1575672096","https://openalex.org/W3100796443"],"abstract_inverted_index":{"The":[0,37,45,109,137],"research":[1],"of":[2,5,70,76],"gait":[3,17,25,38],"independent":[4,69],"view":[6,71,84,125],"angle":[7,80,92,118],"has":[8,85],"become":[9],"an":[10,34],"urgent":[11],"problem":[12],"to":[13,93],"be":[14,68,128],"solved":[15],"for":[16],"recognition.":[18],"In":[19],"this":[20,107],"paper,":[21],"we":[22],"propose":[23],"a":[24,50,146],"recognition":[26],"method":[27,133,144],"that":[28,142],"the":[29,57,63,73,77,82,90,94,116,122],"subject":[30],"can":[31],"walk":[32,117],"at":[33],"arbitrary":[35],"angle.":[36,99],"is":[39,47,119,145],"detected":[40],"through":[41],"background":[42],"subtraction":[43],"technique.":[44],"contour":[46,60],"represented":[48],"by":[49],"novel":[51],"approach":[52],"which":[53,111],"includes":[54],"not":[55],"only":[56,123],"spatial":[58],"body":[59],"but":[61],"also":[62],"temporal":[64],"information.":[65],"To":[66],"prove":[67],"angle,":[72],"relationship":[74],"model":[75],"walking":[78,91],"azimuth":[79],"and":[81],"reference":[83],"been":[86],"modeled.":[87],"We":[88,130],"transform":[89],"most":[95],"similar":[96],"canonical":[97,101,124],"views":[98,102],"Three":[100],"angles":[103],"are":[104],"adopted":[105],"in":[106],"paper.":[108],"errors":[110],"come":[112],"from":[113,121],"transformation":[114],"when":[115],"far":[120],"will":[126],"greatly":[127],"reduced.":[129],"test":[131],"our":[132,143],"on":[134],"multi-views":[135],"database.":[136],"correct":[138],"classification":[139],"ratios":[140],"show":[141],"nice":[147],"try.":[148]},"counts_by_year":[{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
