{"id":"https://openalex.org/W2346219687","doi":"https://doi.org/10.1145/2897735","title":"Isolated Sign Language Recognition with Grassmann Covariance Matrices","display_name":"Isolated Sign Language Recognition with Grassmann Covariance Matrices","publication_year":2016,"publication_date":"2016-05-07","ids":{"openalex":"https://openalex.org/W2346219687","doi":"https://doi.org/10.1145/2897735","mag":"2346219687"},"language":"en","primary_location":{"id":"doi:10.1145/2897735","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2897735","pdf_url":null,"source":{"id":"https://openalex.org/S79551877","display_name":"ACM Transactions on Accessible Computing","issn_l":"1936-7228","issn":["1936-7228","1936-7236"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Accessible 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/A5039723440","display_name":"Hanjie Wang","orcid":"https://orcid.org/0000-0001-9400-814X"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanjie Wang","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003198738","display_name":"Xiujuan Chai","orcid":"https://orcid.org/0000-0002-2757-9900"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiujuan Chai","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026880795","display_name":"Xiaopeng Hong","orcid":"https://orcid.org/0000-0002-0611-0636"},"institutions":[{"id":"https://openalex.org/I98381234","display_name":"University of Oulu","ror":"https://ror.org/03yj89h83","country_code":"FI","type":"education","lineage":["https://openalex.org/I98381234"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Xiaopeng Hong","raw_affiliation_strings":["University of Oulu, Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Oulu, Finland","institution_ids":["https://openalex.org/I98381234"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082301986","display_name":"Guoying Zhao","orcid":"https://orcid.org/0000-0003-3694-206X"},"institutions":[{"id":"https://openalex.org/I98381234","display_name":"University of Oulu","ror":"https://ror.org/03yj89h83","country_code":"FI","type":"education","lineage":["https://openalex.org/I98381234"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Guoying Zhao","raw_affiliation_strings":["University of Oulu, Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Oulu, Finland","institution_ids":["https://openalex.org/I98381234"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5083420537","display_name":"Xilin Chen","orcid":"https://orcid.org/0000-0003-3024-4404"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210090176","display_name":"Institute of Computing Technology","ror":"https://ror.org/0090r4d87","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210090176"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xilin Chen","raw_affiliation_strings":["Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210090176","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.9252,"has_fulltext":false,"cited_by_count":87,"citation_normalized_percentile":{"value":0.96328624,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"8","issue":"4","first_page":"1","last_page":"21"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T11398","display_name":"Hand Gesture Recognition Systems","score":1.0,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9947999715805054,"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":0.9839000105857849,"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/metric","display_name":"Metric (unit)","score":0.6885596513748169},{"id":"https://openalex.org/keywords/sign","display_name":"Sign (mathematics)","score":0.6206954717636108},{"id":"https://openalex.org/keywords/covariance","display_name":"Covariance","score":0.6003453135490417},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.5972840189933777},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5847269892692566},{"id":"https://openalex.org/keywords/covariance-matrix","display_name":"Covariance matrix","score":0.5572500824928284},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5427624583244324},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5340161919593811},{"id":"https://openalex.org/keywords/grassmannian","display_name":"Grassmannian","score":0.5198603272438049},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5145984888076782},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5053172707557678},{"id":"https://openalex.org/keywords/covariance-intersection","display_name":"Covariance intersection","score":0.4816788136959076},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.47046932578086853},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.38452252745628357},{"id":"https://openalex.org/keywords/estimation-of-covariance-matrices","display_name":"Estimation of covariance matrices","score":0.37508395314216614},{"id":"https://openalex.org/keywords/combinatorics","display_name":"Combinatorics","score":0.08750030398368835},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.06987833976745605}],"concepts":[{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.6885596513748169},{"id":"https://openalex.org/C139676723","wikidata":"https://www.wikidata.org/wiki/Q1193832","display_name":"Sign (mathematics)","level":2,"score":0.6206954717636108},{"id":"https://openalex.org/C178650346","wikidata":"https://www.wikidata.org/wiki/Q201984","display_name":"Covariance","level":2,"score":0.6003453135490417},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.5972840189933777},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5847269892692566},{"id":"https://openalex.org/C185142706","wikidata":"https://www.wikidata.org/wiki/Q1134404","display_name":"Covariance matrix","level":2,"score":0.5572500824928284},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5427624583244324},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5340161919593811},{"id":"https://openalex.org/C162929932","wikidata":"https://www.wikidata.org/wiki/Q129638","display_name":"Grassmannian","level":2,"score":0.5198603272438049},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5145984888076782},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5053172707557678},{"id":"https://openalex.org/C83042196","wikidata":"https://www.wikidata.org/wiki/Q5178898","display_name":"Covariance intersection","level":4,"score":0.4816788136959076},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.47046932578086853},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.38452252745628357},{"id":"https://openalex.org/C180877172","wikidata":"https://www.wikidata.org/wiki/Q5401390","display_name":"Estimation of covariance matrices","level":3,"score":0.37508395314216614},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.08750030398368835},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.06987833976745605},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2897735","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2897735","pdf_url":null,"source":{"id":"https://openalex.org/S79551877","display_name":"ACM Transactions on Accessible Computing","issn_l":"1936-7228","issn":["1936-7228","1936-7236"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Accessible Computing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.75,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321108","display_name":"Academy of Finland","ror":"https://ror.org/05k73zm37"},{"id":"https://openalex.org/F4320336704","display_name":"Infotech Oulu","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":55,"referenced_works":["https://openalex.org/W203421571","https://openalex.org/W1502174448","https://openalex.org/W1506441995","https://openalex.org/W1524281572","https://openalex.org/W1534763723","https://openalex.org/W1549083695","https://openalex.org/W1550277507","https://openalex.org/W1969724184","https://openalex.org/W1975292803","https://openalex.org/W1980938127","https://openalex.org/W1983496390","https://openalex.org/W1984588366","https://openalex.org/W1986964250","https://openalex.org/W1989614008","https://openalex.org/W1993014362","https://openalex.org/W2008716258","https://openalex.org/W2020163092","https://openalex.org/W2024868105","https://openalex.org/W2029364672","https://openalex.org/W2030605635","https://openalex.org/W2040448851","https://openalex.org/W2049353206","https://openalex.org/W2060280062","https://openalex.org/W2071414260","https://openalex.org/W2075295044","https://openalex.org/W2085489682","https://openalex.org/W2095687464","https://openalex.org/W2096910120","https://openalex.org/W2096976709","https://openalex.org/W2097384738","https://openalex.org/W2102170500","https://openalex.org/W2108036388","https://openalex.org/W2108333036","https://openalex.org/W2112382942","https://openalex.org/W2116022929","https://openalex.org/W2116030300","https://openalex.org/W2121996250","https://openalex.org/W2122399640","https://openalex.org/W2126017757","https://openalex.org/W2131308039","https://openalex.org/W2135478857","https://openalex.org/W2137940226","https://openalex.org/W2141830256","https://openalex.org/W2143267104","https://openalex.org/W2144093206","https://openalex.org/W2146221819","https://openalex.org/W2153635508","https://openalex.org/W2161969291","https://openalex.org/W2188882108","https://openalex.org/W2210722207","https://openalex.org/W2250670799","https://openalex.org/W2798909945","https://openalex.org/W2997426117","https://openalex.org/W3100876745","https://openalex.org/W4312258136"],"related_works":["https://openalex.org/W1974588588","https://openalex.org/W2572601863","https://openalex.org/W2118568436","https://openalex.org/W2018001152","https://openalex.org/W2109377650","https://openalex.org/W4390642134","https://openalex.org/W2344632425","https://openalex.org/W1987404909","https://openalex.org/W2097670344","https://openalex.org/W4309794518"],"abstract_inverted_index":{"In":[0],"this":[1,62],"article,":[2],"to":[3,18,56,96],"utilize":[4],"long-term":[5],"dynamics":[6],"over":[7],"an":[8],"isolated":[9],"sign":[10,77,124],"sequence,":[11],"we":[12,120],"propose":[13],"a":[14,98,112],"covariance":[15,39,58,74,87],"matrix--based":[16],"representation":[17,82],"naturally":[19],"fuse":[20],"information":[21],"from":[22],"multimodal":[23],"sources.":[24],"To":[25,115],"tackle":[26],"the":[27,31,36,44,48,57,68,85,91,101,109,117,133,137],"drawback":[28],"induced":[29],"by":[30,64],"commonly":[32],"used":[33,95],"Riemannian":[34],"metric,":[35],"proximity":[37],"of":[38,73,76,108],"matrices":[40,75],"is":[41,83,94],"measured":[42],"on":[43,127],"Grassmann":[45,50,86,92],"manifold.":[46],"However,":[47],"inherent":[49],"metric":[51,93],"cannot":[52],"be":[53,97],"directly":[54],"applied":[55],"matrix.":[59],"We":[60],"solve":[61],"problem":[63],"evaluating":[65],"and":[66,143],"selecting":[67],"most":[69],"significant":[70],"singular":[71],"vectors":[72],"sequences.":[78],"The":[79],"resulting":[80],"compact":[81],"called":[84],"matrix":[88],".":[89],"Finally,":[90],"kernel":[99],"for":[100],"support":[102],"vector":[103],"machine,":[104],"which":[105,128],"enables":[106],"learning":[107],"signs":[110],"in":[111,141],"discriminative":[113],"manner.":[114],"validate":[116],"proposed":[118,134],"method,":[119],"collect":[121],"three":[122],"challenging":[123],"language":[125],"datasets,":[126],"comprehensive":[129],"evaluations":[130],"show":[131],"that":[132],"method":[135],"outperforms":[136],"state-of-the-art":[138],"methods":[139],"both":[140],"accuracy":[142],"computational":[144],"cost.":[145]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":6},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":9},{"year":2022,"cited_by_count":10},{"year":2021,"cited_by_count":20},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":9},{"year":2018,"cited_by_count":6},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":3}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}