{"id":"https://openalex.org/W2162862985","doi":"https://doi.org/10.1109/lsp.2014.2362553","title":"Accurate Human Pose Estimation by Aggregating Multiple Pose Hypotheses Using Modified Kernel Density Approximation","display_name":"Accurate Human Pose Estimation by Aggregating Multiple Pose Hypotheses Using Modified Kernel Density Approximation","publication_year":2014,"publication_date":"2014-10-09","ids":{"openalex":"https://openalex.org/W2162862985","doi":"https://doi.org/10.1109/lsp.2014.2362553","mag":"2162862985"},"language":"en","primary_location":{"id":"doi:10.1109/lsp.2014.2362553","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2014.2362553","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","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/A5101464856","display_name":"Eunji Cho","orcid":"https://orcid.org/0000-0002-3027-0357"},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Eunji Cho","raw_affiliation_strings":["Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang, Hyoja-dong, Nam-gu, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang, Hyoja-dong, Nam-gu, Korea","institution_ids":["https://openalex.org/I123900574"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101431617","display_name":"Daijin Kim","orcid":"https://orcid.org/0000-0002-8046-8521"},"institutions":[{"id":"https://openalex.org/I123900574","display_name":"Pohang University of Science and Technology","ror":"https://ror.org/04xysgw12","country_code":"KR","type":"education","lineage":["https://openalex.org/I123900574"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Daijin Kim","raw_affiliation_strings":["Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang, Hyoja-dong, Nam-gu, Korea"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Pohang University of Science and Technology, Pohang, Hyoja-dong, Nam-gu, Korea","institution_ids":["https://openalex.org/I123900574"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5101464856"],"corresponding_institution_ids":["https://openalex.org/I123900574"],"apc_list":null,"apc_paid":null,"fwci":0.4877,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.7148108,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"22","issue":"4","first_page":"445","last_page":"449"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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/T10812","display_name":"Human Pose and Action Recognition","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/T11398","display_name":"Hand Gesture Recognition Systems","score":0.9987000226974487,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.995199978351593,"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":0.8986979722976685},{"id":"https://openalex.org/keywords/kernel-density-estimation","display_name":"Kernel density estimation","score":0.7424741983413696},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6524533629417419},{"id":"https://openalex.org/keywords/kernel","display_name":"Kernel (algebra)","score":0.6007568836212158},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5771509408950806},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.552527904510498},{"id":"https://openalex.org/keywords/articulated-body-pose-estimation","display_name":"Articulated body pose estimation","score":0.5493334531784058},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.5420819520950317},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.4782651662826538},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4517683982849121},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.4169086217880249},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3686336278915405},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3346073031425476},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.20773661136627197},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1662110984325409}],"concepts":[{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.8986979722976685},{"id":"https://openalex.org/C71134354","wikidata":"https://www.wikidata.org/wiki/Q458825","display_name":"Kernel density estimation","level":3,"score":0.7424741983413696},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6524533629417419},{"id":"https://openalex.org/C74193536","wikidata":"https://www.wikidata.org/wiki/Q574844","display_name":"Kernel (algebra)","level":2,"score":0.6007568836212158},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5771509408950806},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.552527904510498},{"id":"https://openalex.org/C22100474","wikidata":"https://www.wikidata.org/wiki/Q4800952","display_name":"Articulated body pose estimation","level":4,"score":0.5493334531784058},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.5420819520950317},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.4782651662826538},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4517683982849121},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.4169086217880249},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3686336278915405},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3346073031425476},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.20773661136627197},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1662110984325409},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/lsp.2014.2362553","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lsp.2014.2362553","pdf_url":null,"source":{"id":"https://openalex.org/S120629676","display_name":"IEEE Signal Processing Letters","issn_l":"1070-9908","issn":["1070-9908","1558-2361"],"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 Signal Processing Letters","raw_type":"journal-article"},{"id":"pmh:oai:oasis.postech.ac.kr:2014.oak/13973","is_oa":false,"landing_page_url":"https://oasis.postech.ac.kr/handle/2014.oak/13973","pdf_url":null,"source":{"id":"https://openalex.org/S4306401965","display_name":"Open Access System for Information Sharing (Pohang University of Science and Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I123900574","host_organization_name":"Pohang University of Science and Technology","host_organization_lineage":["https://openalex.org/I123900574"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"No poverty","id":"https://metadata.un.org/sdg/1","score":0.75}],"awards":[{"id":"https://openalex.org/G112030869","display_name":null,"funder_award_id":"10041629","funder_id":"https://openalex.org/F4320321681","funder_display_name":"Ministry of Trade, Industry and Energy"}],"funders":[{"id":"https://openalex.org/F4320321681","display_name":"Ministry of Trade, Industry and Energy","ror":"https://ror.org/008nkqk13"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W16266776","https://openalex.org/W64332451","https://openalex.org/W171061157","https://openalex.org/W2013640163","https://openalex.org/W2022699039","https://openalex.org/W2030536784","https://openalex.org/W2045798786","https://openalex.org/W2057204268","https://openalex.org/W2105990640","https://openalex.org/W2123533187","https://openalex.org/W2131263044","https://openalex.org/W2135533529","https://openalex.org/W2152926413","https://openalex.org/W2158866619","https://openalex.org/W2161969291","https://openalex.org/W2172156083","https://openalex.org/W3005794849","https://openalex.org/W6602608934","https://openalex.org/W6675961540"],"related_works":["https://openalex.org/W2946083937","https://openalex.org/W2798721181","https://openalex.org/W4386075737","https://openalex.org/W2951583186","https://openalex.org/W4299867837","https://openalex.org/W2088028039","https://openalex.org/W4382141741","https://openalex.org/W3165753266","https://openalex.org/W4206633503","https://openalex.org/W4285662725"],"abstract_inverted_index":{"This":[0],"letter":[1],"proposes":[2],"an":[3],"accurate":[4],"human":[5,25,65],"pose":[6,19,26,40,51,76,83,111,121,128,151],"estimation":[7,27,41,52,152],"method":[8,163],"that":[9,106],"uses":[10],"a":[11],"modified":[12,95],"kernel":[13,91],"density":[14,92],"approximation":[15],"(m-KDA)":[16],"to":[17,45,48,62,72,142],"multiple":[18,50],"hypotheses.":[20,77,122],"Existing":[21],"methods":[22],"show":[23],"poor":[24],"because":[28],"of":[29,119,170],"cluttered":[30],"background":[31],"or":[32],"self-occlusion":[33],"by":[34,96,130],"the":[35,39,57,64,69,74,81,86,116,126,132,138,143,161,168,176],"human.":[36],"To":[37],"improve":[38],"accuracy,":[42],"we":[43,55,79,124],"propose":[44],"use":[46,56,68],"m-KDA":[47,134],"aggregate":[49,80],"results.":[53],"First,":[54],"flexible":[58],"mixture-of-parts":[59],"model":[60],"(FMM)":[61],"estimate":[63],"poses":[66],"then":[67],"top-M":[70,82,120],"scores":[71],"choose":[73],"good":[75],"Second,":[78],"hypotheses":[84],"with":[85],"m-KDA,":[87],"in":[88,167],"which":[89],"each":[90,97,102,110],"function":[93,105],"is":[94,113],"pose's":[98,103],"score":[99],"value":[100,118],"and":[101,147,159],"compatibility":[104],"represents":[107],"how":[108],"far":[109],"hypothesis":[112],"departed":[114],"from":[115,137],"nominal":[117],"Third,":[123],"determine":[125],"optimal":[127],"configuration":[129],"repeating":[131],"above":[133],"computation,":[135],"starting":[136],"root":[139],"part":[140],"(head)":[141],"leaf":[144],"parts":[145,173],"(hands":[146],"feet),":[148],"sequentially.":[149],"In":[150],"experiments":[153],"on":[154],"two":[155],"benchmark":[156],"datasets":[157],"(PARSE":[158],"LSP),":[160],"proposed":[162],"achieved":[164],"1.5-4.0%":[165],"improvement":[166],"percentage":[169],"correct":[171],"localized":[172],"(PCP)":[174],"over":[175],"state-of-the-art":[177],"methods.":[178]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
