{"id":"https://openalex.org/W2127494100","doi":"https://doi.org/10.1109/robot.2008.4543603","title":"Combining automated on-line segmentation and incremental clustering for whole body motions","display_name":"Combining automated on-line segmentation and incremental clustering for whole body motions","publication_year":2008,"publication_date":"2008-05-01","ids":{"openalex":"https://openalex.org/W2127494100","doi":"https://doi.org/10.1109/robot.2008.4543603","mag":"2127494100"},"language":"en","primary_location":{"id":"doi:10.1109/robot.2008.4543603","is_oa":false,"landing_page_url":"https://doi.org/10.1109/robot.2008.4543603","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Robotics and Automation","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/A5072377971","display_name":"Dana Kuli\u0107","orcid":"https://orcid.org/0000-0002-4169-2141"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Dana Kulic","raw_affiliation_strings":["Department of Mechano-Informatics, University of Tokyo, Tokyo, Japan","Dept. of Mechano-Inf., Univ. of Tokyo, Tokyo"],"affiliations":[{"raw_affiliation_string":"Department of Mechano-Informatics, University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"Dept. of Mechano-Inf., Univ. of Tokyo, Tokyo","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5019765580","display_name":"Wataru Takano","orcid":"https://orcid.org/0000-0002-4846-3552"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Wataru Takano","raw_affiliation_strings":["Department of Mechano-Informatics, University of Tokyo, Tokyo, Japan","Dept. of Mechano-Inf., Univ. of Tokyo, Tokyo"],"affiliations":[{"raw_affiliation_string":"Department of Mechano-Informatics, University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"Dept. of Mechano-Inf., Univ. of Tokyo, Tokyo","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5040633710","display_name":"Yoshihiko Nakamura","orcid":"https://orcid.org/0000-0001-7162-5102"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoshihiko Nakamura","raw_affiliation_strings":["Department of Mechano-Informatics, University of Tokyo, Tokyo, Japan","Dept. of Mechano-Inf., Univ. of Tokyo, Tokyo"],"affiliations":[{"raw_affiliation_string":"Department of Mechano-Informatics, University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"Dept. of Mechano-Inf., Univ. of Tokyo, Tokyo","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5072377971"],"corresponding_institution_ids":["https://openalex.org/I74801974"],"apc_list":null,"apc_paid":null,"fwci":6.4563,"has_fulltext":false,"cited_by_count":30,"citation_normalized_percentile":{"value":0.97041574,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"2","issue":null,"first_page":"2591","last_page":"2598"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9977999925613403,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9966999888420105,"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":0.991100013256073,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7325153946876526},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7212923169136047},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.7195960879325867},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.670708954334259},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.6179305911064148},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6084575057029724},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5876725316047668},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5696422457695007},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.5094118714332581},{"id":"https://openalex.org/keywords/motion-capture","display_name":"Motion capture","score":0.5057206153869629},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4604739248752594},{"id":"https://openalex.org/keywords/tree-structure","display_name":"Tree structure","score":0.45875808596611023},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.44320523738861084},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3232665956020355},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2579731345176697},{"id":"https://openalex.org/keywords/binary-tree","display_name":"Binary tree","score":0.09962916374206543}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7325153946876526},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7212923169136047},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.7195960879325867},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.670708954334259},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.6179305911064148},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6084575057029724},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5876725316047668},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5696422457695007},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.5094118714332581},{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.5057206153869629},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4604739248752594},{"id":"https://openalex.org/C163797641","wikidata":"https://www.wikidata.org/wiki/Q2067937","display_name":"Tree structure","level":3,"score":0.45875808596611023},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.44320523738861084},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3232665956020355},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2579731345176697},{"id":"https://openalex.org/C197855036","wikidata":"https://www.wikidata.org/wiki/Q380172","display_name":"Binary tree","level":2,"score":0.09962916374206543},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/robot.2008.4543603","is_oa":false,"landing_page_url":"https://doi.org/10.1109/robot.2008.4543603","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Robotics and Automation","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.379.6841","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.379.6841","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"https://ece.uwaterloo.ca/~dkulic/pubs/KulicTakanoNakamuraICRA2008.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1491100250","https://openalex.org/W1934413089","https://openalex.org/W1992419399","https://openalex.org/W2021628196","https://openalex.org/W2032382874","https://openalex.org/W2037461669","https://openalex.org/W2125838338","https://openalex.org/W2128103053","https://openalex.org/W2130726249","https://openalex.org/W2135858662","https://openalex.org/W2143406978","https://openalex.org/W2154482673","https://openalex.org/W2161491846","https://openalex.org/W2162103415","https://openalex.org/W2252953085","https://openalex.org/W2253907359","https://openalex.org/W2543074387","https://openalex.org/W2543386152","https://openalex.org/W2546143719","https://openalex.org/W6680176085","https://openalex.org/W6682756744","https://openalex.org/W6683788672"],"related_works":["https://openalex.org/W2093885745","https://openalex.org/W2351266481","https://openalex.org/W2132547887","https://openalex.org/W2071459461","https://openalex.org/W2516987005","https://openalex.org/W2907786475","https://openalex.org/W2963447120","https://openalex.org/W4289082820","https://openalex.org/W2092152400","https://openalex.org/W2963196945"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"a":[3,61,98,159],"novel":[4],"approach":[5],"for":[6],"incremental":[7],"learning":[8],"of":[9,17,93,139,146,161,174],"human":[10,18,163],"motion":[11,22,33,46,55,72,124,141,164,168],"pattern":[12],"primitives":[13,142],"through":[14,167],"on-line":[15],"observation":[16],"motion.":[19],"The":[20,54,90,115,153],"observed":[21],"time":[23],"series":[24],"data":[25,41,165],"stream":[26],"is":[27,97,156],"first":[28],"stochastically":[29],"segmented":[30],"into":[31,60],"potential":[32],"primitive":[34,47],"segments,":[35],"based":[36,81],"on":[37,82,158],"the":[38,44,50,87,94,105,113,120,131,137,144,147,172,175],"assumption":[39],"that":[40,135],"belonging":[42],"to":[43,112,130],"same":[45,51],"will":[48],"have":[49],"underlying":[52],"distribution.":[53],"segments":[56],"are":[57,74,77,126],"then":[58,127],"abstracted":[59],"stochastic":[62],"model":[63,88],"representation,":[64],"and":[65,68,108,170],"automatically":[66],"clustered":[67],"organized.":[69],"As":[70],"new":[71],"patterns":[73],"observed,":[75],"they":[76],"incrementally":[78],"grouped":[79],"together":[80],"their":[83],"relative":[84],"distance":[85],"in":[86],"space.":[89],"resulting":[91],"representation":[92],"knowledge":[95],"domain":[96],"tree":[99,106,116],"structure,":[100],"with":[101],"specialized":[102,122],"motions":[103,110],"at":[104],"leaves,":[107,117],"generalized":[109],"closer":[111],"root.":[114],"which":[118],"represent":[119],"most":[121],"learned":[123],"primitives,":[125],"passed":[128],"back":[129],"segmentation":[132,148],"algorithm,":[133],"so":[134],"as":[136],"number":[138],"known":[140],"increases,":[143],"accuracy":[145],"can":[149],"also":[150],"be":[151],"improved.":[152],"combined":[154],"algorithm":[155],"tested":[157],"sequence":[160],"continuous":[162],"obtained":[166],"capture,":[169],"demonstrates":[171],"performance":[173],"proposed":[176],"approach.":[177]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2014,"cited_by_count":1},{"year":2013,"cited_by_count":5},{"year":2012,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}