{"id":"https://openalex.org/W2019842267","doi":"https://doi.org/10.1109/iros.2010.5650813","title":"Incremental learning of human behaviors using hierarchical hidden Markov models","display_name":"Incremental learning of human behaviors using hierarchical hidden Markov models","publication_year":2010,"publication_date":"2010-10-01","ids":{"openalex":"https://openalex.org/W2019842267","doi":"https://doi.org/10.1109/iros.2010.5650813","mag":"2019842267"},"language":"en","primary_location":{"id":"doi:10.1109/iros.2010.5650813","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2010.5650813","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE/RSJ International Conference on Intelligent Robots and Systems","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/A5072377971","display_name":"Dana Kuli\u0107","orcid":"https://orcid.org/0000-0002-4169-2141"},"institutions":[{"id":"https://openalex.org/I151746483","display_name":"University of Waterloo","ror":"https://ror.org/01aff2v68","country_code":"CA","type":"education","lineage":["https://openalex.org/I151746483"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"D Kulic\u0301","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada","Department of Electrical and Computer Engineering , University of Waterloo , ON , Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Waterloo, Waterloo, ON, Canada","institution_ids":["https://openalex.org/I151746483"]},{"raw_affiliation_string":"Department of Electrical and Computer Engineering , University of Waterloo , ON , Canada","institution_ids":["https://openalex.org/I151746483"]}]},{"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":"Y Nakamura","raw_affiliation_strings":["The Department of Mechano-Informatics, University of Tokyo, Tokyo, Japan","Department of Mechano-Informatics, University of Tokyo, Japan#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Department of Mechano-Informatics, University of Tokyo, Tokyo, Japan","institution_ids":["https://openalex.org/I74801974"]},{"raw_affiliation_string":"Department of Mechano-Informatics, University of Tokyo, Japan#TAB#","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":31,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"21","issue":null,"first_page":"4649","last_page":"4655"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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":0.9998999834060669,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.998199999332428,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9958999752998352,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/hidden-markov-model","display_name":"Hidden Markov model","score":0.8090341687202454},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7880129218101501},{"id":"https://openalex.org/keywords/abstraction","display_name":"Abstraction","score":0.7009365558624268},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.688995897769928},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.657447338104248},{"id":"https://openalex.org/keywords/movement","display_name":"Movement (music)","score":0.5945308208465576},{"id":"https://openalex.org/keywords/markov-model","display_name":"Markov model","score":0.5450175404548645},{"id":"https://openalex.org/keywords/markov-chain","display_name":"Markov chain","score":0.4966662526130676},{"id":"https://openalex.org/keywords/markov-process","display_name":"Markov process","score":0.45785582065582275},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4470055103302002},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.4278584420681},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3500669598579407},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10760959982872009}],"concepts":[{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.8090341687202454},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7880129218101501},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.7009365558624268},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.688995897769928},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.657447338104248},{"id":"https://openalex.org/C2780226923","wikidata":"https://www.wikidata.org/wiki/Q929848","display_name":"Movement (music)","level":2,"score":0.5945308208465576},{"id":"https://openalex.org/C163836022","wikidata":"https://www.wikidata.org/wiki/Q6771326","display_name":"Markov model","level":3,"score":0.5450175404548645},{"id":"https://openalex.org/C98763669","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov chain","level":2,"score":0.4966662526130676},{"id":"https://openalex.org/C159886148","wikidata":"https://www.wikidata.org/wiki/Q176645","display_name":"Markov process","level":2,"score":0.45785582065582275},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4470055103302002},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.4278584420681},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3500669598579407},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10760959982872009},{"id":"https://openalex.org/C107038049","wikidata":"https://www.wikidata.org/wiki/Q35986","display_name":"Aesthetics","level":1,"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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iros.2010.5650813","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros.2010.5650813","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2010 IEEE/RSJ International Conference on Intelligent Robots and Systems","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.379.8801","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.379.8801","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/KulicNakamuraIROS2010.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","display_name":"Reduced inequalities","score":0.4399999976158142}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W130216483","https://openalex.org/W1491100250","https://openalex.org/W1982486572","https://openalex.org/W1992419399","https://openalex.org/W2030991373","https://openalex.org/W2037461669","https://openalex.org/W2043152589","https://openalex.org/W2045317647","https://openalex.org/W2089619576","https://openalex.org/W2098516422","https://openalex.org/W2100469802","https://openalex.org/W2103560566","https://openalex.org/W2109385289","https://openalex.org/W2109485196","https://openalex.org/W2110304639","https://openalex.org/W2114938622","https://openalex.org/W2125459459","https://openalex.org/W2125838338","https://openalex.org/W2128103053","https://openalex.org/W2135858662","https://openalex.org/W2154124367","https://openalex.org/W2155307968","https://openalex.org/W2158164339","https://openalex.org/W2160429843","https://openalex.org/W2160625746","https://openalex.org/W2168743227","https://openalex.org/W2169253318","https://openalex.org/W2303345904","https://openalex.org/W3141842851","https://openalex.org/W6680176085","https://openalex.org/W6683128514"],"related_works":["https://openalex.org/W1510894296","https://openalex.org/W2134386692","https://openalex.org/W2082284720","https://openalex.org/W2194396582","https://openalex.org/W2116722627","https://openalex.org/W2379938888","https://openalex.org/W2537260108","https://openalex.org/W4233405330","https://openalex.org/W2176285001","https://openalex.org/W2792905593"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"a":[3,8,46,72,115],"novel":[4],"approach":[5,96,111],"for":[6,97],"extracting":[7],"model":[9,52,104],"of":[10,20,100,117],"movement":[11,27,61,119],"primitives":[12],"and":[13,37,75],"their":[14],"sequential":[15],"relationships":[16],"during":[17,40,105],"online":[18,106],"observation":[19,77,107],"human":[21],"motion.":[22],"In":[23],"the":[24,43,57,60,64,76,82,85,91,101],"proposed":[25],"approach,":[26],"primitives,":[28],"modeled":[29],"as":[30],"hidden":[31,50,69],"Markov":[32,51],"models,":[33],"are":[34],"autonomously":[35],"segmented":[36],"learned":[38],"incrementally":[39],"observation.":[41],"At":[42],"same":[44],"time,":[45],"higher":[47,65,102],"abstraction":[48],"level":[49,66],"is":[53,79,88,108,112],"also":[54],"learned,":[55],"encapsulating":[56],"relationship":[58],"between":[59],"primitives.":[62],"For":[63],"model,":[67],"each":[68],"state":[70],"represents":[71],"motion":[73,92],"primitive,":[74],"function":[78],"based":[80],"on":[81,114],"likelihood":[83],"that":[84],"observed":[86],"data":[87],"generated":[89],"by":[90],"primitive":[93],"model.":[94],"An":[95],"incremental":[98],"training":[99],"order":[103],"developed.":[109],"The":[110],"validated":[113],"dataset":[116],"continuous":[118],"data.":[120]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":2},{"year":2016,"cited_by_count":2},{"year":2015,"cited_by_count":1},{"year":2014,"cited_by_count":5},{"year":2013,"cited_by_count":5},{"year":2012,"cited_by_count":8}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
