{"id":"https://openalex.org/W2293633825","doi":"https://doi.org/10.1109/icip.2015.7350971","title":"Sequential non-rigid point registration for 3D human pose tracking","display_name":"Sequential non-rigid point registration for 3D human pose tracking","publication_year":2015,"publication_date":"2015-09-01","ids":{"openalex":"https://openalex.org/W2293633825","doi":"https://doi.org/10.1109/icip.2015.7350971","mag":"2293633825"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2015.7350971","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2015.7350971","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":"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/A5100619503","display_name":"Ge Song","orcid":"https://orcid.org/0000-0002-9740-2959"},"institutions":[{"id":"https://openalex.org/I115475287","display_name":"Oklahoma State University","ror":"https://ror.org/01g9vbr38","country_code":"US","type":"education","lineage":["https://openalex.org/I115475287"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Song Ge","raw_affiliation_strings":["School of Electrical and Computer Engineering Oklahoma State University, Stillwater, OK, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering Oklahoma State University, Stillwater, OK, USA","institution_ids":["https://openalex.org/I115475287"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5016996180","display_name":"Guoliang Fan","orcid":"https://orcid.org/0000-0002-8584-9040"},"institutions":[{"id":"https://openalex.org/I115475287","display_name":"Oklahoma State University","ror":"https://ror.org/01g9vbr38","country_code":"US","type":"education","lineage":["https://openalex.org/I115475287"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Guoliang Fan","raw_affiliation_strings":["School of Electrical and Computer Engineering Oklahoma State University, Stillwater, OK, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electrical and Computer Engineering Oklahoma State University, Stillwater, OK, USA","institution_ids":["https://openalex.org/I115475287"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3744,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.70919472,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1105","last_page":"1109"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9995999932289124,"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":0.9995999932289124,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9968000054359436,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.996399998664856,"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/point-cloud","display_name":"Point cloud","score":0.8059837818145752},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.7754265069961548},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.765730619430542},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7368252277374268},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.732288122177124},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.6618908643722534},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6310204863548279},{"id":"https://openalex.org/keywords/rigid-transformation","display_name":"Rigid transformation","score":0.6224673986434937},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5384917259216309},{"id":"https://openalex.org/keywords/image-registration","display_name":"Image registration","score":0.502683162689209},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.47741973400115967},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4645167887210846},{"id":"https://openalex.org/keywords/generative-model","display_name":"Generative model","score":0.46009913086891174},{"id":"https://openalex.org/keywords/point-set-registration","display_name":"Point set registration","score":0.44961801171302795},{"id":"https://openalex.org/keywords/generative-grammar","display_name":"Generative grammar","score":0.34423375129699707},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.18051910400390625},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14299637079238892},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.08823153376579285}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8059837818145752},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.7754265069961548},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.765730619430542},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7368252277374268},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.732288122177124},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.6618908643722534},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6310204863548279},{"id":"https://openalex.org/C126795593","wikidata":"https://www.wikidata.org/wiki/Q7333813","display_name":"Rigid transformation","level":2,"score":0.6224673986434937},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5384917259216309},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.502683162689209},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.47741973400115967},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4645167887210846},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.46009913086891174},{"id":"https://openalex.org/C200336642","wikidata":"https://www.wikidata.org/wiki/Q15058706","display_name":"Point set registration","level":3,"score":0.44961801171302795},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.34423375129699707},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.18051910400390625},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14299637079238892},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.08823153376579285},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2015.7350971","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2015.7350971","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":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1554663460","https://openalex.org/W1581135849","https://openalex.org/W1968027100","https://openalex.org/W1977039804","https://openalex.org/W1984632210","https://openalex.org/W1989191365","https://openalex.org/W2009629245","https://openalex.org/W2012655811","https://openalex.org/W2049381231","https://openalex.org/W2053186076","https://openalex.org/W2082809978","https://openalex.org/W2092146246","https://openalex.org/W2114354851","https://openalex.org/W2121717885","https://openalex.org/W2134236847","https://openalex.org/W2136340340","https://openalex.org/W2156094778","https://openalex.org/W2157938685","https://openalex.org/W2168415715","https://openalex.org/W2172156083","https://openalex.org/W3136515919","https://openalex.org/W4388297464","https://openalex.org/W7010160137"],"related_works":["https://openalex.org/W4253893311","https://openalex.org/W2798721181","https://openalex.org/W3201205132","https://openalex.org/W4287600488","https://openalex.org/W4312694060","https://openalex.org/W4386075737","https://openalex.org/W4281696776","https://openalex.org/W4387967917","https://openalex.org/W4299867837","https://openalex.org/W2008497570"],"abstract_inverted_index":{"We":[0],"proposes":[1],"a":[2,18,27,33],"new":[3,81],"generative":[4],"framework":[5,46],"for":[6,57,67],"3D":[7],"human":[8],"pose":[9,42,68],"tracking":[10],"based":[11],"on":[12,73],"point":[13,53],"cloud":[14],"sequences":[15],"captured":[16],"by":[17,49],"single":[19],"depth":[20,76],"sensor.":[21],"The":[22,44,70],"problem":[23],"is":[24,37,47],"formulated":[25],"as":[26],"sequential":[28],"non-rigid":[29,55],"registration":[30,56,66],"process":[31],"where":[32],"subject-specific":[34],"shape/skeleton":[35],"model":[36],"involved":[38],"and":[39,64],"updated":[40],"during":[41],"tracking.":[43],"proposed":[45],"featured":[48],"four":[50],"steps,":[51],"visible":[52],"extraction,":[54],"body":[58],"segment":[59,61],"labeling,":[60],"volume":[62],"validation":[63],"articulated":[65],"estimation.":[69],"experimental":[71],"results":[72,86],"the":[74,80,89],"benchmark":[75],"dataset":[77],"demonstrate":[78],"that":[79],"method":[82],"can":[83],"achieve":[84],"competitive":[85],"compared":[87],"with":[88],"states-of-the-art":[90],"ones.":[91]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}