{"id":"https://openalex.org/W2118214853","doi":"https://doi.org/10.1109/mlsp.2011.6064580","title":"Putting poses on manifold for action recognition","display_name":"Putting poses on manifold for action recognition","publication_year":2011,"publication_date":"2011-09-01","ids":{"openalex":"https://openalex.org/W2118214853","doi":"https://doi.org/10.1109/mlsp.2011.6064580","mag":"2118214853"},"language":"en","primary_location":{"id":"doi:10.1109/mlsp.2011.6064580","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2011.6064580","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Workshop on Machine Learning for Signal Processing","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/A5038809760","display_name":"Xianbin Cao","orcid":"https://orcid.org/0000-0002-5042-7884"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]},{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xianbin Cao","raw_affiliation_strings":["BeiHang University, Beijing, China","Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"BeiHang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]},{"raw_affiliation_string":"Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009377108","display_name":"Bo Ning","orcid":"https://orcid.org/0000-0001-5256-6418"},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bo Ning","raw_affiliation_strings":["Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054075262","display_name":"Pingkun Yan","orcid":"https://orcid.org/0000-0002-9779-2141"},"institutions":[{"id":"https://openalex.org/I4210144662","display_name":"Xi'an Institute of Optics and Precision Mechanics","ror":"https://ror.org/0444j5556","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210144662"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pingkun Yan","raw_affiliation_strings":["Center for OPTical IMagery Analysis and Learning (OPTIMAL), State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences (CAS), Xi'an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"Center for OPTical IMagery Analysis and Learning (OPTIMAL), State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences (CAS), Xi'an, Shaanxi, China","institution_ids":["https://openalex.org/I4210144662"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100740143","display_name":"Xuelong Li","orcid":"https://orcid.org/0000-0002-0019-4197"},"institutions":[{"id":"https://openalex.org/I4210144662","display_name":"Xi'an Institute of Optics and Precision Mechanics","ror":"https://ror.org/0444j5556","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210144662"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuelong Li","raw_affiliation_strings":["Center for OPTical IMagery Analysis and Learning (OPTIMAL), State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences (CAS), Xi'an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"Center for OPTical IMagery Analysis and Learning (OPTIMAL), State Key Laboratory of Transient Optics and Photonics, Xi'an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences (CAS), Xi'an, Shaanxi, China","institution_ids":["https://openalex.org/I4210144662"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5038809760"],"corresponding_institution_ids":["https://openalex.org/I126520041","https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16265352,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"4","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":1.0,"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":1.0,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9979000091552734,"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":0.9972000122070312,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/codebook","display_name":"Codebook","score":0.9615929126739502},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.7140411138534546},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6791148781776428},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6689850091934204},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6188316941261292},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5383535027503967},{"id":"https://openalex.org/keywords/manifold","display_name":"Manifold (fluid mechanics)","score":0.46840474009513855},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.43989092111587524},{"id":"https://openalex.org/keywords/manifold-alignment","display_name":"Manifold alignment","score":0.4332418143749237},{"id":"https://openalex.org/keywords/nonlinear-dimensionality-reduction","display_name":"Nonlinear dimensionality reduction","score":0.4051283299922943},{"id":"https://openalex.org/keywords/dimensionality-reduction","display_name":"Dimensionality reduction","score":0.15758955478668213}],"concepts":[{"id":"https://openalex.org/C127759330","wikidata":"https://www.wikidata.org/wiki/Q637416","display_name":"Codebook","level":2,"score":0.9615929126739502},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.7140411138534546},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6791148781776428},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6689850091934204},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6188316941261292},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5383535027503967},{"id":"https://openalex.org/C529865628","wikidata":"https://www.wikidata.org/wiki/Q1790740","display_name":"Manifold (fluid mechanics)","level":2,"score":0.46840474009513855},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.43989092111587524},{"id":"https://openalex.org/C153120616","wikidata":"https://www.wikidata.org/wiki/Q17068315","display_name":"Manifold alignment","level":4,"score":0.4332418143749237},{"id":"https://openalex.org/C151876577","wikidata":"https://www.wikidata.org/wiki/Q7049464","display_name":"Nonlinear dimensionality reduction","level":3,"score":0.4051283299922943},{"id":"https://openalex.org/C70518039","wikidata":"https://www.wikidata.org/wiki/Q16000077","display_name":"Dimensionality reduction","level":2,"score":0.15758955478668213},{"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/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mlsp.2011.6064580","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mlsp.2011.6064580","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Workshop on Machine Learning for Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7200000286102295}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1487355806","https://openalex.org/W1625255723","https://openalex.org/W2034328688","https://openalex.org/W2066636486","https://openalex.org/W2068576236","https://openalex.org/W2108333036","https://openalex.org/W2110142955","https://openalex.org/W2130843763","https://openalex.org/W2158169396","https://openalex.org/W2163273012","https://openalex.org/W2165095705","https://openalex.org/W2533739470","https://openalex.org/W2538361501","https://openalex.org/W3141200356","https://openalex.org/W4249279051","https://openalex.org/W4285719527","https://openalex.org/W6629068734","https://openalex.org/W6636494156","https://openalex.org/W6676671045","https://openalex.org/W7034449035"],"related_works":["https://openalex.org/W2387045723","https://openalex.org/W117517268","https://openalex.org/W2573981081","https://openalex.org/W2397338926","https://openalex.org/W2085003924","https://openalex.org/W2384392227","https://openalex.org/W2380477800","https://openalex.org/W2142781195","https://openalex.org/W2888431323","https://openalex.org/W2365774975"],"abstract_inverted_index":{"In":[0,71,93],"action":[1,99],"recognition,":[2],"bag":[3],"of":[4,18,48,90,97],"words":[5],"based":[6,59],"approaches":[7],"have":[8],"been":[9],"shown":[10],"to":[11,28,43,64,85,125],"be":[12,110],"successful,":[13],"for":[14,32,112],"which":[15,35],"the":[16,33,37,45,49,69,80,87,95,130],"quality":[17],"codebook":[19],"is":[20,62,77,83,101,123],"critical.":[21],"This":[22],"paper":[23],"proposes":[24],"a":[25,52,74],"novel":[26],"approach":[27],"select":[29,65],"key":[30,66,75],"poses":[31,67],"codebook,":[34],"models":[36],"descriptor":[38],"space":[39],"utilizing":[40],"manifold":[41,55],"learning":[42],"recover":[44],"geometric":[46],"structure":[47],"descriptors":[50],"on":[51,68,116],"lower":[53],"dimensional":[54],"space.":[56],"A":[57],"PageRank":[58],"centrality":[60],"measure":[61],"developed":[63],"manifold.":[70],"each":[72,98],"step,":[73],"pose":[76],"selected":[78,91],"and":[79],"remaining":[81],"model":[82],"modified":[84],"maximize":[86],"discriminative":[88],"power":[89],"codebook.":[92],"classification,":[94],"ambiguity":[96],"couple":[100],"evaluated":[102],"through":[103],"cross":[104],"validation.":[105],"An":[106],"additional":[107],"subdivision":[108],"will":[109],"executed":[111],"ambiguous":[113],"pairs.":[114],"Experiments":[115],"ut-tower":[117],"dataset":[118],"showed":[119],"that":[120],"our":[121],"method":[122],"able":[124],"obtain":[126],"better":[127],"performance":[128],"than":[129],"state-of-the-art":[131],"methods.":[132]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}