{"id":"https://openalex.org/W4292347995","doi":"https://doi.org/10.1109/tim.2022.3200438","title":"A Local\u2013Global Estimator Based on Large Kernel CNN and Transformer for Human Pose Estimation and Running Pose Measurement","display_name":"A Local\u2013Global Estimator Based on Large Kernel CNN and Transformer for Human Pose Estimation and Running Pose Measurement","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4292347995","doi":"https://doi.org/10.1109/tim.2022.3200438"},"language":"en","primary_location":{"id":"doi:10.1109/tim.2022.3200438","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3200438","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","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/A5045187270","display_name":"Qingtian Wu","orcid":"https://orcid.org/0000-0002-2475-9156"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Qingtian Wu","raw_affiliation_strings":["Faculty of Sciences and Technology, University of Macau, Macau, China"],"raw_orcid":"https://orcid.org/0000-0002-2475-9156","affiliations":[{"raw_affiliation_string":"Faculty of Sciences and Technology, University of Macau, Macau, China","institution_ids":["https://openalex.org/I204512498"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103164935","display_name":"Yongfei Wu","orcid":"https://orcid.org/0000-0002-6344-1992"},"institutions":[{"id":"https://openalex.org/I9086337","display_name":"Taiyuan University of Technology","ror":"https://ror.org/03kv08d37","country_code":"CN","type":"education","lineage":["https://openalex.org/I9086337"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongfei Wu","raw_affiliation_strings":["College of Data Science, Taiyuan University of Technology, Taiyuan, China","College of Data Science, Taiyuan University of Technology, Taiyuan, Shanxi, China"],"raw_orcid":"https://orcid.org/0000-0002-6344-1992","affiliations":[{"raw_affiliation_string":"College of Data Science, Taiyuan University of Technology, Taiyuan, China","institution_ids":["https://openalex.org/I9086337"]},{"raw_affiliation_string":"College of Data Science, Taiyuan University of Technology, Taiyuan, Shanxi, China","institution_ids":["https://openalex.org/I9086337"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020005530","display_name":"Yu Zhang","orcid":"https://orcid.org/0000-0002-1360-6162"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]},{"id":"https://openalex.org/I48780066","display_name":"Shenyang University of Chemical Technology","ror":"https://ror.org/03dbpdh75","country_code":"CN","type":"education","lineage":["https://openalex.org/I48780066"]}],"countries":["CN","MO"],"is_corresponding":false,"raw_author_name":"Yu Zhang","raw_affiliation_strings":["Faculty of Sciences and Technology, University of Macau, Macau, China","Shenyang University of Chemical Technology, Shenyang, Liaoning, China"],"raw_orcid":"https://orcid.org/0000-0002-1360-6162","affiliations":[{"raw_affiliation_string":"Faculty of Sciences and Technology, University of Macau, Macau, China","institution_ids":["https://openalex.org/I204512498"]},{"raw_affiliation_string":"Shenyang University of Chemical Technology, Shenyang, Liaoning, China","institution_ids":["https://openalex.org/I48780066"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100646618","display_name":"Liming Zhang","orcid":"https://orcid.org/0000-0002-2664-8193"},"institutions":[{"id":"https://openalex.org/I204512498","display_name":"University of Macau","ror":"https://ror.org/01r4q9n85","country_code":"MO","type":"education","lineage":["https://openalex.org/I204512498"]}],"countries":["MO"],"is_corresponding":false,"raw_author_name":"Liming Zhang","raw_affiliation_strings":["Faculty of Sciences and Technology, University of Macau, Macau, China"],"raw_orcid":"https://orcid.org/0000-0002-2664-8193","affiliations":[{"raw_affiliation_string":"Faculty of Sciences and Technology, University of Macau, Macau, China","institution_ids":["https://openalex.org/I204512498"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.6428,"has_fulltext":false,"cited_by_count":27,"citation_normalized_percentile":{"value":0.91347561,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"71","issue":null,"first_page":"1","last_page":"12"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998000264167786,"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":0.9998000264167786,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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":0.9961000084877014,"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/pose","display_name":"Pose","score":0.7681173086166382},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6760532855987549},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6630229949951172},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6366695165634155},{"id":"https://openalex.org/keywords/locality","display_name":"Locality","score":0.6214073896408081},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.6002723574638367},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5567377805709839},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.49601373076438904},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4454463720321655},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.43294304609298706},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3485606908798218},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.14469560980796814},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1280239224433899}],"concepts":[{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.7681173086166382},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6760532855987549},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6630229949951172},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6366695165634155},{"id":"https://openalex.org/C2779808786","wikidata":"https://www.wikidata.org/wiki/Q6664603","display_name":"Locality","level":2,"score":0.6214073896408081},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.6002723574638367},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5567377805709839},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.49601373076438904},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4454463720321655},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.43294304609298706},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3485606908798218},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.14469560980796814},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1280239224433899},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"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/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tim.2022.3200438","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tim.2022.3200438","pdf_url":null,"source":{"id":"https://openalex.org/S10892749","display_name":"IEEE Transactions on Instrumentation and Measurement","issn_l":"0018-9456","issn":["0018-9456","1557-9662"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Instrumentation and Measurement","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W602397586","https://openalex.org/W639708223","https://openalex.org/W1861492603","https://openalex.org/W2080873731","https://openalex.org/W2108598243","https://openalex.org/W2161969291","https://openalex.org/W2194775991","https://openalex.org/W2307770531","https://openalex.org/W2549139847","https://openalex.org/W2752782242","https://openalex.org/W2789129057","https://openalex.org/W2798376494","https://openalex.org/W2928165649","https://openalex.org/W2963070890","https://openalex.org/W2963163009","https://openalex.org/W2963402313","https://openalex.org/W2964221239","https://openalex.org/W2964304707","https://openalex.org/W2981601805","https://openalex.org/W3014641072","https://openalex.org/W3034399482","https://openalex.org/W3047772167","https://openalex.org/W3096609285","https://openalex.org/W3110870077","https://openalex.org/W3112359988","https://openalex.org/W3113950706","https://openalex.org/W3121523901","https://openalex.org/W3138516171","https://openalex.org/W3151130473","https://openalex.org/W3156811085","https://openalex.org/W3156988133","https://openalex.org/W3175199633","https://openalex.org/W3176892444","https://openalex.org/W3181955139","https://openalex.org/W4249279051","https://openalex.org/W4289047567","https://openalex.org/W6631190155","https://openalex.org/W6739901393","https://openalex.org/W6757733370","https://openalex.org/W6766978945","https://openalex.org/W6787906798","https://openalex.org/W6788135285","https://openalex.org/W6794906783","https://openalex.org/W6798274885"],"related_works":["https://openalex.org/W1556451512","https://openalex.org/W1555349535","https://openalex.org/W4234091740","https://openalex.org/W4213350282","https://openalex.org/W2230171082","https://openalex.org/W2583128298","https://openalex.org/W2022275305","https://openalex.org/W1604115909","https://openalex.org/W4293226380","https://openalex.org/W2123263858"],"abstract_inverted_index":{"Running":[0],"pose":[1,31,45,74,106,234,247],"in":[2],"the":[3,51,81,95,98,110,113,124,130,134,155,174,183,188,203,207,211,225,232],"crowd":[4],"can":[5,21],"serve":[6],"as":[7],"an":[8,59,68,249],"early":[9],"warning":[10],"of":[11,97,136,191,227,251],"most":[12],"abnormal":[13],"events":[14],"(e.g.,":[15],"chasing,":[16],"fleeing":[17],"and":[18,56,103,170,196,261],"robbing),":[19],"which":[20],"be":[22,265],"achieved":[23,40],"by":[24,84,93,236],"human":[25,30,44,73,114,233],"behavior":[26],"analysis":[27],"based":[28,79,140],"on":[29,43,80,141,194,231],"measurement.":[32,107],"Although":[33],"deep":[34],"convolutional":[35],"neural":[36],"networks":[37],"(CNNs)":[38],"have":[39],"impressive":[41],"progress":[42],"estimation,":[46],"how":[47],"to":[48,100,122,150,167,223,244],"further":[49],"improve":[50],"trade-off":[52,209],"between":[53,112,127],"estimation":[54,75],"accuracy":[55,250],"speed":[57],"remains":[58],"open":[60],"issue.":[61],"In":[62],"this":[63],"work,":[64],"we":[65,176,216,239],"first":[66],"propose":[67,240],"efficient":[69],"local-global":[70],"estimator":[71],"for":[72],"(called":[76],"LGPose).":[77],"Then":[78],"keypoints":[82],"estimated":[83,235],"our":[85,228,237],"LGPose,":[86,238],"a":[87,218,241],"simple":[88],"regression":[89,242],"model":[90,109,243],"is":[91,120,139,161],"defined":[92],"using":[94],"geometry":[96],"joints":[99],"achieve":[101],"fast":[102],"accurate":[104],"running":[105,220,246,262],"To":[108,172],"relationships":[111],"keypoints,":[115],"visual":[116],"transformer":[117,137],"(ViT)":[118],"encoder":[119,138],"adopted":[121],"learn":[123,173],"long-range":[125],"interdependencies":[126],"them":[128],"at":[129],"pixel":[131],"level.":[132],"However,":[133],"operation":[135],"sequence":[142],"processing":[143],"that":[144,202],"linearly":[145],"projects":[146],"2D":[147],"image":[148],"patches":[149],"1D":[151],"tokens.":[152],"It":[153],"loses":[154],"important":[156],"local":[157],"information.":[158],"Yet,":[159],"locality":[160],"crucial":[162],"since":[163],"it":[164],"has":[165],"relevance":[166],"lines,":[168],"edges":[169],"shapes.":[171],"locality,":[175],"design":[177],"effective":[178],"CNN":[179],"modules,":[180],"rather":[181],"than":[182],"original":[184],"fully-connected":[185],"network,":[186],"into":[187],"feedforward":[189],"module":[190],"ViT.":[192],"Experiments":[193],"MPII":[195],"COCO":[197],"Keypoint":[198],"val2017":[199],"dataset":[200,222,263],"show":[201],"proposed":[204],"LGPose":[205],"achieves":[206],"best":[208],"among":[210],"compared":[212],"state-of-the-art":[213],"methods.":[214],"Moreover,":[215],"build":[217],"lightweight":[219],"movement":[221],"verify":[224],"effectiveness":[226],"LGPose.":[229],"Based":[230],"measure":[245],"with":[248],"86.4%":[252],"without":[253],"training":[254],"any":[255],"other":[256],"classifier.":[257],"Our":[258],"source":[259],"codes":[260],"will":[264],"made":[266],"publicly":[267],"available.":[268]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":10}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}