{"id":"https://openalex.org/W2295214711","doi":"https://doi.org/10.1109/icip.2015.7350975","title":"Adaptive appearance learning for human pose estimation","display_name":"Adaptive appearance learning for human pose estimation","publication_year":2015,"publication_date":"2015-09-01","ids":{"openalex":"https://openalex.org/W2295214711","doi":"https://doi.org/10.1109/icip.2015.7350975","mag":"2295214711"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2015.7350975","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2015.7350975","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Image Processing (ICIP)","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/A5100435829","display_name":"Lei Wang","orcid":"https://orcid.org/0000-0002-0296-8993"},"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":"Lei Wang","raw_affiliation_strings":["Key Laboratory of System Control and Information Processing Department of Automation, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of System Control and Information Processing Department of Automation, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100440525","display_name":"Xu Zhao","orcid":"https://orcid.org/0000-0002-8176-623X"},"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":"Xu Zhao","raw_affiliation_strings":["Key Laboratory of System Control and Information Processing Department of Automation, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of System Control and Information Processing Department of Automation, Shanghai Jiao Tong 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":["Key Laboratory of System Control and Information Processing Department of Automation, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of System Control and Information Processing Department of Automation, Shanghai Jiao Tong 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":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"1","issue":null,"first_page":"1125","last_page":"1129"},"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9993000030517578,"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":0.9944999814033508,"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":0.8271110653877258},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7928736209869385},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7421290874481201},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.6560959815979004},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5770215392112732},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.567148745059967},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5352225303649902},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5178749561309814},{"id":"https://openalex.org/keywords/articulated-body-pose-estimation","display_name":"Articulated body pose estimation","score":0.4961460530757904},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4865962266921997},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.474776953458786},{"id":"https://openalex.org/keywords/active-appearance-model","display_name":"Active appearance model","score":0.4622381329536438},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.4622153639793396},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4531548023223877},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.11813122034072876}],"concepts":[{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.8271110653877258},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7928736209869385},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7421290874481201},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.6560959815979004},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5770215392112732},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.567148745059967},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5352225303649902},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5178749561309814},{"id":"https://openalex.org/C22100474","wikidata":"https://www.wikidata.org/wiki/Q4800952","display_name":"Articulated body pose estimation","level":4,"score":0.4961460530757904},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4865962266921997},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.474776953458786},{"id":"https://openalex.org/C83248878","wikidata":"https://www.wikidata.org/wiki/Q344000","display_name":"Active appearance model","level":3,"score":0.4622381329536438},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.4622153639793396},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4531548023223877},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.11813122034072876},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2015.7350975","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2015.7350975","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.8999999761581421}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1997691213","https://openalex.org/W2013640163","https://openalex.org/W2018793343","https://openalex.org/W2022699039","https://openalex.org/W2030536784","https://openalex.org/W2045798786","https://openalex.org/W2073246097","https://openalex.org/W2074587583","https://openalex.org/W2093949207","https://openalex.org/W2099305880","https://openalex.org/W2101194540","https://openalex.org/W2105990640","https://openalex.org/W2131263044","https://openalex.org/W2161969291","https://openalex.org/W2168356304","https://openalex.org/W6675961540"],"related_works":["https://openalex.org/W2946083937","https://openalex.org/W2798721181","https://openalex.org/W2951583186","https://openalex.org/W4299867837","https://openalex.org/W2088028039","https://openalex.org/W4382141741","https://openalex.org/W4386075737","https://openalex.org/W1968783203","https://openalex.org/W4206633503","https://openalex.org/W2148535645"],"abstract_inverted_index":{"We":[0,35,61,108],"address":[1],"the":[2,30,57,76,83,131,134],"problem":[3],"of":[4,21,40,51,72,104,122,133],"pose":[5,26,74,123],"estimation":[6,27,124],"in":[7,33],"videos.":[8],"The":[9,48],"part":[10],"detectors":[11,18],"play":[12],"important":[13],"roles,":[14],"but":[15],"traditional":[16],"template-based":[17],"(e.g.":[19],"Histogram":[20],"Gradient,":[22],"HoG)":[23],"fail":[24],"at":[25],"due":[28],"to":[29,67],"high":[31],"variability":[32],"appearance.":[34],"present":[36],"an":[37,87],"adaptive":[38],"representation":[39,50],"appearance":[41,89],"and":[42,80],"shape":[43],"for":[44,100,117],"articulated":[45],"human":[46,52],"body.":[47],"full":[49],"body":[53],"is":[54],"based":[55,81],"on":[56,82,126],"flexible":[58],"mixture-of-parts":[59],"model.":[60,90],"train":[62],"a":[63,69,96,113],"Naive":[64],"Bayes":[65],"classifier":[66],"obtain":[68],"confidence":[70,84],"score":[71],"estimated":[73],"by":[75],"basic":[77],"mixture":[78],"model,":[79],"we":[85,94],"learn":[86],"instance-specific":[88],"For":[91],"between-frame":[92],"consistency,":[93],"design":[95],"time-efficient":[97],"energy":[98],"function":[99],"motion":[101,106],"cues":[102],"instead":[103],"complex":[105],"models.":[107],"incorporate":[109],"these":[110],"models":[111],"into":[112],"framework":[114],"that":[115],"allows":[116],"efficient":[118],"inference.":[119],"Quantitative":[120],"evaluation":[121],"conducted":[125],"two":[127],"video":[128],"datasets":[129],"demonstrates":[130],"effectiveness":[132],"proposed":[135],"method.":[136]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
