{"id":"https://openalex.org/W2134243564","doi":"https://doi.org/10.1109/cvprw.2008.4563176","title":"Distributed segmentation and classification of human actions using a wearable motion sensor network","display_name":"Distributed segmentation and classification of human actions using a wearable motion sensor network","publication_year":2008,"publication_date":"2008-06-01","ids":{"openalex":"https://openalex.org/W2134243564","doi":"https://doi.org/10.1109/cvprw.2008.4563176","mag":"2134243564"},"language":"en","primary_location":{"id":"doi:10.1109/cvprw.2008.4563176","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw.2008.4563176","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops","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/A5107790029","display_name":"Allen Y. Yang","orcid":null},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Allen Y. Yang","raw_affiliation_strings":["Department of EECS, University of California, Berkeley, USA","[Department of EECS, University of California, Berkeley, CA]"],"affiliations":[{"raw_affiliation_string":"Department of EECS, University of California, Berkeley, USA","institution_ids":["https://openalex.org/I95457486"]},{"raw_affiliation_string":"[Department of EECS, University of California, Berkeley, CA]","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066693898","display_name":"Sameer Iyengar","orcid":null},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Sameer Iyengar","raw_affiliation_strings":["Department of EECS, University of California, Berkeley, USA","[Department of EECS, University of California, Berkeley, CA]"],"affiliations":[{"raw_affiliation_string":"Department of EECS, University of California, Berkeley, USA","institution_ids":["https://openalex.org/I95457486"]},{"raw_affiliation_string":"[Department of EECS, University of California, Berkeley, CA]","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042250331","display_name":"Philip Kuryloski","orcid":null},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Philip Kuryloski","raw_affiliation_strings":["Department of ECE, Cornell University, USA"],"affiliations":[{"raw_affiliation_string":"Department of ECE, Cornell University, USA","institution_ids":["https://openalex.org/I205783295"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5011769350","display_name":"Roozbeh Jafari","orcid":"https://orcid.org/0000-0002-6358-0458"},"institutions":[{"id":"https://openalex.org/I205783295","display_name":"Cornell University","ror":"https://ror.org/05bnh6r87","country_code":"US","type":"education","lineage":["https://openalex.org/I205783295"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Roozbeh Jafari","raw_affiliation_strings":["Department of ECE, Cornell University, USA"],"affiliations":[{"raw_affiliation_string":"Department of ECE, Cornell University, USA","institution_ids":["https://openalex.org/I205783295"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5107790029"],"corresponding_institution_ids":["https://openalex.org/I95457486"],"apc_list":null,"apc_paid":null,"fwci":5.2441,"has_fulltext":false,"cited_by_count":89,"citation_normalized_percentile":{"value":0.95628946,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9994000196456909,"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"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9987000226974487,"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":0.9987000226974487,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6808170676231384},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6390939950942993},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5707416534423828},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5492522716522217},{"id":"https://openalex.org/keywords/subspace-topology","display_name":"Subspace topology","score":0.5314981341362},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.5310445427894592},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5228170156478882},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4371647238731384},{"id":"https://openalex.org/keywords/test-set","display_name":"Test set","score":0.42750874161720276},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.4145801067352295},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3859255313873291}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6808170676231384},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6390939950942993},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5707416534423828},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5492522716522217},{"id":"https://openalex.org/C32834561","wikidata":"https://www.wikidata.org/wiki/Q660730","display_name":"Subspace topology","level":2,"score":0.5314981341362},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.5310445427894592},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5228170156478882},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4371647238731384},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.42750874161720276},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.4145801067352295},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3859255313873291},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/cvprw.2008.4563176","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cvprw.2008.4563176","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops","raw_type":"proceedings-article"},{"id":"pmh:oai:berkeley.edu:28722-bk0000m3x9h","is_oa":false,"landing_page_url":"http://techreports.lib.berkeley.edu/accessPages/EECS-2007-143.html","pdf_url":null,"source":{"id":"https://openalex.org/S7407050879","display_name":"UC Berkeley","issn_l":null,"issn":[],"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"technical reports"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W94937181","https://openalex.org/W118040084","https://openalex.org/W1484678121","https://openalex.org/W1527911497","https://openalex.org/W1735711190","https://openalex.org/W1762028752","https://openalex.org/W1979613719","https://openalex.org/W2039761202","https://openalex.org/W2073364774","https://openalex.org/W2080815943","https://openalex.org/W2105046342","https://openalex.org/W2107106521","https://openalex.org/W2114868488","https://openalex.org/W2129638195","https://openalex.org/W2129812935","https://openalex.org/W2143364815","https://openalex.org/W2152364474","https://openalex.org/W2156243282","https://openalex.org/W2534335869","https://openalex.org/W2970930377","https://openalex.org/W4285719527","https://openalex.org/W6631658523","https://openalex.org/W6637464354","https://openalex.org/W6675583992","https://openalex.org/W6682831935","https://openalex.org/W6767511011"],"related_works":["https://openalex.org/W1980381208","https://openalex.org/W2364594919","https://openalex.org/W1861706286","https://openalex.org/W2219338811","https://openalex.org/W2167092671","https://openalex.org/W2149583853","https://openalex.org/W2143002539","https://openalex.org/W2130386332","https://openalex.org/W1120847856","https://openalex.org/W4293472652"],"abstract_inverted_index":{"We":[0,62,100,128,163],"propose":[1],"a":[2,11,18,58,72,83,157],"distributed":[3,184],"recognition":[4,168],"method":[5],"to":[6,111,134,146],"classify":[7],"human":[8,33],"actions":[9,40],"using":[10,173],"low-bandwidth":[12],"wearable":[13],"motion":[14,22],"sensor":[15,55],"network.":[16],"Given":[17,82],"set":[19,158],"of":[20,67,93,115,159,176,182],"pre-segmented":[21],"sequences":[23],"as":[24],"training":[25,46,98],"examples,":[26],"the":[27,45,65,89,94,103,107,112,116,126,150,167,180,183],"algorithm":[28,151],"simultaneously":[29],"segments":[30],"and":[31,35,57,119],"classifies":[32],"actions,":[34],"it":[36],"also":[37],"rejects":[38],"outlying":[39],"that":[41,64,102,166],"are":[42],"not":[43],"in":[44,106,125],"set.":[47],"The":[48],"classification":[49],"is":[50,123],"distributedly":[51],"operated":[52],"on":[53,156],"individual":[54],"nodes":[56],"base":[59],"station":[60],"computer.":[61],"show":[63,101],"distribution":[66],"multiple":[68],"action":[69,80,113,161],"classes":[70],"satisfies":[71],"mixture":[73],"subspace":[74],"model,":[75],"one":[76],"sub-space":[77],"for":[78],"each":[79],"class.":[81],"new":[84],"test":[85,117],"sample,":[86,118],"we":[87],"seek":[88],"sparsest":[90],"linear":[91,132],"representation":[92,108,137],"sample":[95],"w.r.t.":[96],"all":[97],"examples.":[99],"dominant":[104],"coefficients":[105],"only":[109,170],"correspond":[110],"class":[114],"hence":[120],"its":[121],"membership":[122],"encoded":[124],"representation.":[127],"further":[129,164],"provide":[130],"fast":[131],"solvers":[133],"compute":[135],"such":[136],"via":[138],"l":[139],"<sup":[140],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[141],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">1</sup>":[142],"-minimization.":[143],"Using":[144],"up":[145],"eight":[147],"body":[148],"sensors,":[149,177],"achieves":[152],"state-of-the-art":[153],"98.8%":[154],"accuracy":[155],"12":[160],"categories.":[162],"demonstrate":[165],"precision":[169],"decreases":[171],"gracefully":[172],"smaller":[174],"subsets":[175],"which":[178],"validates":[179],"robustness":[181],"framework.":[185]},"counts_by_year":[{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3},{"year":2020,"cited_by_count":8},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":5},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":9},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":6},{"year":2012,"cited_by_count":11}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}