{"id":"https://openalex.org/W2098051036","doi":"https://doi.org/10.1109/cvpr.2008.4587795","title":"View-invariant recognition of body pose from space-time templates","display_name":"View-invariant recognition of body pose from space-time templates","publication_year":2008,"publication_date":"2008-06-01","ids":{"openalex":"https://openalex.org/W2098051036","doi":"https://doi.org/10.1109/cvpr.2008.4587795","mag":"2098051036"},"language":"en","primary_location":{"id":"doi:10.1109/cvpr.2008.4587795","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2008.4587795","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://stars.library.ucf.edu/scopus2000/10211","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5089344406","display_name":"Yuping Shen","orcid":"https://orcid.org/0000-0002-0732-8450"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yuping Shen","raw_affiliation_strings":["Computational Imaging Laboratory, University of Central Florida, Orlando, FL, USA","Comput. Imaging Lab., Univ. of Central Florida, Orlando, FL"],"affiliations":[{"raw_affiliation_string":"Computational Imaging Laboratory, University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]},{"raw_affiliation_string":"Comput. Imaging Lab., Univ. of Central Florida, Orlando, FL","institution_ids":["https://openalex.org/I106165777"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076117344","display_name":"Hassan Foroosh","orcid":"https://orcid.org/0000-0002-7601-8165"},"institutions":[{"id":"https://openalex.org/I106165777","display_name":"University of Central Florida","ror":"https://ror.org/036nfer12","country_code":"US","type":"education","lineage":["https://openalex.org/I106165777"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hassan Foroosh","raw_affiliation_strings":["Computational Imaging Laboratory, University of Central Florida, Orlando, FL, USA","Comput. Imaging Lab., Univ. of Central Florida, Orlando, FL"],"affiliations":[{"raw_affiliation_string":"Computational Imaging Laboratory, University of Central Florida, Orlando, FL, USA","institution_ids":["https://openalex.org/I106165777"]},{"raw_affiliation_string":"Comput. Imaging Lab., Univ. of Central Florida, Orlando, FL","institution_ids":["https://openalex.org/I106165777"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5089344406"],"corresponding_institution_ids":["https://openalex.org/I106165777"],"apc_list":null,"apc_paid":null,"fwci":0.7099,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.73834541,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"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":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/T10531","display_name":"Advanced Vision and Imaging","score":0.9980999827384949,"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/T12290","display_name":"Human Motion and Animation","score":0.9980000257492065,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.6913392543792725},{"id":"https://openalex.org/keywords/template","display_name":"Template","score":0.6884307861328125},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6628003120422363},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6139980554580688},{"id":"https://openalex.org/keywords/viewpoints","display_name":"Viewpoints","score":0.5973684191703796},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5930061340332031},{"id":"https://openalex.org/keywords/rigid-body","display_name":"Rigid body","score":0.5639551877975464},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.5488213300704956},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4494733512401581},{"id":"https://openalex.org/keywords/eigenvalues-and-eigenvectors","display_name":"Eigenvalues and eigenvectors","score":0.44814959168434143},{"id":"https://openalex.org/keywords/articulated-body-pose-estimation","display_name":"Articulated body pose estimation","score":0.41694989800453186},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.41561439633369446},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.351618230342865},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.3098182678222656},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.2548786401748657},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10345104336738586}],"concepts":[{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.6913392543792725},{"id":"https://openalex.org/C82714645","wikidata":"https://www.wikidata.org/wiki/Q438331","display_name":"Template","level":2,"score":0.6884307861328125},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6628003120422363},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6139980554580688},{"id":"https://openalex.org/C2776035091","wikidata":"https://www.wikidata.org/wiki/Q7928819","display_name":"Viewpoints","level":2,"score":0.5973684191703796},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5930061340332031},{"id":"https://openalex.org/C145980571","wikidata":"https://www.wikidata.org/wiki/Q192788","display_name":"Rigid body","level":2,"score":0.5639551877975464},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.5488213300704956},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4494733512401581},{"id":"https://openalex.org/C158693339","wikidata":"https://www.wikidata.org/wiki/Q190524","display_name":"Eigenvalues and eigenvectors","level":2,"score":0.44814959168434143},{"id":"https://openalex.org/C22100474","wikidata":"https://www.wikidata.org/wiki/Q4800952","display_name":"Articulated body pose estimation","level":4,"score":0.41694989800453186},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.41561439633369446},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.351618230342865},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3098182678222656},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.2548786401748657},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10345104336738586},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C24890656","wikidata":"https://www.wikidata.org/wiki/Q82811","display_name":"Acoustics","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/cvpr.2008.4587795","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvpr.2008.4587795","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE Conference on Computer Vision and Pattern Recognition","raw_type":"proceedings-article"},{"id":"pmh:oai:stars.library.ucf.edu:scopus2000-11210","is_oa":true,"landing_page_url":"https://stars.library.ucf.edu/scopus2000/10211","pdf_url":null,"source":{"id":"https://openalex.org/S4210172555","display_name":"Journal of International Crisis and Risk Communication Research","issn_l":"2576-0017","issn":["2576-0017","2576-0025"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Scopus Export 2000s","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.330.3760","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.330.3760","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://cil.cs.ucf.edu/pdf/Shen_Foroosh_Pose_CVPR2008.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.408.531","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.408.531","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://mplab.ucsd.edu/wp-content/uploads/cvpr2008/conference/data/papers/455.pdf","raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:stars.library.ucf.edu:scopus2000-11210","is_oa":true,"landing_page_url":"https://stars.library.ucf.edu/scopus2000/10211","pdf_url":null,"source":{"id":"https://openalex.org/S4210172555","display_name":"Journal of International Crisis and Risk Communication Research","issn_l":"2576-0017","issn":["2576-0017","2576-0025"],"is_oa":true,"is_in_doaj":false,"is_core":true,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Scopus Export 2000s","raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1643263348","https://openalex.org/W1829866624","https://openalex.org/W2006178360","https://openalex.org/W2033819227","https://openalex.org/W2098813977","https://openalex.org/W2104941942","https://openalex.org/W2106503382","https://openalex.org/W2118025528","https://openalex.org/W2121005842","https://openalex.org/W2131432112","https://openalex.org/W2136024719","https://openalex.org/W2145399221","https://openalex.org/W2148522623","https://openalex.org/W2154903520","https://openalex.org/W2158268505","https://openalex.org/W2158638750","https://openalex.org/W2158866619","https://openalex.org/W2161657986","https://openalex.org/W2165715280","https://openalex.org/W4285719527","https://openalex.org/W6636836683","https://openalex.org/W6638522503","https://openalex.org/W6674775138","https://openalex.org/W6679414539","https://openalex.org/W6681286204"],"related_works":["https://openalex.org/W2946083937","https://openalex.org/W2798721181","https://openalex.org/W1968783203","https://openalex.org/W2951583186","https://openalex.org/W4299867837","https://openalex.org/W4298878995","https://openalex.org/W4285662725","https://openalex.org/W2574567538","https://openalex.org/W2088028039","https://openalex.org/W4226064411"],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,44,48,54,78,95],"new":[3],"template-based":[4],"approach":[5],"for":[6],"view":[7],"invariant":[8],"recognition":[9],"of":[10,21,35,56,77,80,94,101,103,112],"body":[11,22,36,45,57,81,86],"poses,":[12],"based":[13],"on":[14,109],"geometric":[15],"constraints":[16,108],"derived":[17],"from":[18,125,140,147],"the":[19,68,71,75,91,99,110,113],"motion":[20,76],"point":[23,58],"triplets.":[24],"In":[25],"addition":[26],"to":[27,64,90,106],"spatial":[28],"information":[29,34],"our":[30,65,133],"templates":[31],"encode":[32],"temporal":[33],"pose":[37,46,87,114],"transitions.":[38],"Unlike":[39],"existing":[40],"methods":[41],"that":[42,70,132],"study":[43],"as":[47],"whole,":[49],"we":[50,97],"decompose":[51],"it":[52],"into":[53],"number":[55],"triplets,":[59],"and":[60,124],"compare":[61],"their":[62],"motions":[63],"templates.":[66],"Using":[67],"fact":[69],"homography":[72],"induced":[73],"by":[74,120],"triplet":[79],"points":[82],"in":[83],"two":[84,102,117],"identical":[85],"transitions":[88,115],"reduces":[89],"special":[92],"case":[93],"homology,":[96],"exploit":[98],"equality":[100],"its":[104],"eigenvalues":[105],"impose":[107],"similarity":[111],"between":[116],"subjects,":[118],"observed":[119,146],"different":[121,126,149,152],"perspective":[122],"cameras":[123],"viewpoints.":[127],"Extensive":[128],"experimental":[129],"results":[130],"show":[131],"method":[134],"can":[135],"accurately":[136],"identify":[137],"human":[138],"poses":[139],"video":[141],"sequences":[142],"when":[143],"they":[144],"are":[145],"totally":[148],"viewpoints":[150],"with":[151],"camera":[153],"parameters.":[154]},"counts_by_year":[{"year":2017,"cited_by_count":11},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}