{"id":"https://openalex.org/W2171582973","doi":"https://doi.org/10.1109/icassp.2010.5495462","title":"A Bayesian framework for 3D human motion tracking from monocular image","display_name":"A Bayesian framework for 3D human motion tracking from monocular image","publication_year":2010,"publication_date":"2010-01-01","ids":{"openalex":"https://openalex.org/W2171582973","doi":"https://doi.org/10.1109/icassp.2010.5495462","mag":"2171582973"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2010.5495462","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2010.5495462","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"},"type":"conference-paper","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/A5100414715","display_name":"Jian Liu","orcid":"https://orcid.org/0000-0003-0268-2941"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jian Liu","raw_affiliation_strings":["Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087158377","display_name":"Junchi Yan","orcid":"https://orcid.org/0000-0001-9639-7679"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Junchi Yan","raw_affiliation_strings":["Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015433638","display_name":"Minglei Tong","orcid":"https://orcid.org/0000-0003-2589-5755"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minglei Tong","raw_affiliation_strings":["Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061110835","display_name":"Yuncai Liu","orcid":"https://orcid.org/0000-0002-4040-4478"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuncai Liu","raw_affiliation_strings":["Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Image Processing and Pattern Recognition, Shanghai Jiaotong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"ii","issue":null,"first_page":"1398","last_page":"1401"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9994999766349792,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9994999766349792,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9994000196456909,"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":0.9939000010490417,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.792014479637146},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7187212705612183},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6293193101882935},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.5788866877555847},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.539486289024353},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.5306654572486877},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.5233144760131836},{"id":"https://openalex.org/keywords/gaussian-process","display_name":"Gaussian process","score":0.5070264339447021},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.43975627422332764},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.42039090394973755},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4144745469093323},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.41323596239089966},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.34705957770347595},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2333105504512787},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.18312790989875793}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.792014479637146},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7187212705612183},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6293193101882935},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.5788866877555847},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.539486289024353},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.5306654572486877},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.5233144760131836},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.5070264339447021},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.43975627422332764},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.42039090394973755},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4144745469093323},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.41323596239089966},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.34705957770347595},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2333105504512787},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.18312790989875793},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","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/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2010.5495462","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2010.5495462","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE International Conference on Acoustics, Speech and Signal Processing","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6399999856948853,"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W1541388462","https://openalex.org/W1651266332","https://openalex.org/W2109026452","https://openalex.org/W2121005842","https://openalex.org/W2124609748","https://openalex.org/W2143516773","https://openalex.org/W2144124341","https://openalex.org/W2158866619","https://openalex.org/W2165363188","https://openalex.org/W3140968660","https://openalex.org/W4213262319","https://openalex.org/W6632348356","https://openalex.org/W6637159134","https://openalex.org/W7048060829"],"related_works":["https://openalex.org/W2580650124","https://openalex.org/W4386190339","https://openalex.org/W2968424575","https://openalex.org/W3142333283","https://openalex.org/W3122088529","https://openalex.org/W3041320102","https://openalex.org/W2111669074","https://openalex.org/W2085259108","https://openalex.org/W3123087812","https://openalex.org/W2063076820"],"abstract_inverted_index":{"This":[0],"paper":[1],"addresses":[2],"a":[3,45,56,92,97],"strategy":[4],"for":[5,23,30],"3D":[6,31],"human":[7,25],"motion":[8,28],"recovery":[9],"from":[10,38],"monocular":[11],"image.":[12],"We":[13],"advocate":[14],"the":[15,35,52,59,73,77,83,87,112],"use":[16],"of":[17,49],"Gaussian":[18],"Process":[19],"Dynamical":[20],"Model":[21],"(GPDM)":[22],"learning":[24],"pose":[26,68],"and":[27,66,70,86,111],"priors":[29],"people":[32],"tracking.":[33],"With":[34],"prior":[36],"learned":[37],"GPDM,":[39],"we":[40],"integrate":[41],"our":[42,109,117],"approach":[43,105],"into":[44],"Bayesian":[46],"tracking":[47,75],"framework":[48],"condensation.":[50],"During":[51],"off-line":[53],"training":[54],"step,":[55],"GPDM":[57],"provides":[58],"reversible":[60],"mappings":[61],"between":[62],"low-dimensional":[63],"latent":[64,78],"space":[65],"high-dimensional":[67],"space,":[69],"then":[71],"in":[72],"online":[74],"process,":[76],"variables":[79],"are":[80],"estimated":[81],"via":[82],"particle":[84],"filtering,":[85],"observation":[88],"is":[89,106],"designed":[90],"as":[91],"energy":[93],"function":[94],"based":[95],"on":[96,108],"Markov":[98],"Random":[99],"Field":[100],"(MRF)":[101],"theory.":[102],"The":[103],"proposed":[104],"demonstrated":[107],"database,":[110],"experimental":[113],"results":[114],"show":[115],"that":[116],"method":[118],"performs":[119],"promisingly.":[120]},"counts_by_year":[{"year":2021,"cited_by_count":3},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
