{"id":"https://openalex.org/W2330561809","doi":"https://doi.org/10.18293/dms2015-004","title":"A Symbolic Representation of Motion Capture Data for Behavioral Segmentation","display_name":"A Symbolic Representation of Motion Capture Data for Behavioral Segmentation","publication_year":2015,"publication_date":"2015-09-01","ids":{"openalex":"https://openalex.org/W2330561809","doi":"https://doi.org/10.18293/dms2015-004","mag":"2330561809"},"language":"en","primary_location":{"id":"doi:10.18293/dms2015-004","is_oa":false,"landing_page_url":"https://doi.org/10.18293/dms2015-004","pdf_url":null,"source":{"id":"https://openalex.org/S4386872205","display_name":"Proceedings","issn_l":"2326-3261","issn":["2326-3261"],"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Conferences on Distributed Multimedia Systems","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/A5019462040","display_name":"Ruxiang Wei","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ruxiang Wei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101917066","display_name":"Weibin Liu","orcid":"https://orcid.org/0000-0001-6246-0051"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weibin Liu","raw_affiliation_strings":["Beijing Jiaotong University"],"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5007723033","display_name":"Weiwei Xing","orcid":"https://orcid.org/0000-0002-6378-926X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Weiwei Xing","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5019462040"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9009,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.72299465,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"2015","issue":null,"first_page":"78","last_page":"84"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12290","display_name":"Human Motion and Animation","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T12290","display_name":"Human Motion and Animation","score":0.9997000098228455,"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"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9994999766349792,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9991000294685364,"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/motion-capture","display_name":"Motion capture","score":0.7655539512634277},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7313339114189148},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6888898611068726},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.6545888185501099},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6538384556770325},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6260055899620056},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.522501528263092},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.4960192143917084},{"id":"https://openalex.org/keywords/motion-field","display_name":"Motion field","score":0.45807692408561707},{"id":"https://openalex.org/keywords/quarter-pixel-motion","display_name":"Quarter-pixel motion","score":0.44444775581359863},{"id":"https://openalex.org/keywords/structure-from-motion","display_name":"Structure from motion","score":0.42726439237594604},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.34514516592025757}],"concepts":[{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.7655539512634277},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7313339114189148},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6888898611068726},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.6545888185501099},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6538384556770325},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6260055899620056},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.522501528263092},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.4960192143917084},{"id":"https://openalex.org/C124774092","wikidata":"https://www.wikidata.org/wiki/Q6917782","display_name":"Motion field","level":3,"score":0.45807692408561707},{"id":"https://openalex.org/C174493125","wikidata":"https://www.wikidata.org/wiki/Q1073461","display_name":"Quarter-pixel motion","level":3,"score":0.44444775581359863},{"id":"https://openalex.org/C146159030","wikidata":"https://www.wikidata.org/wiki/Q7625099","display_name":"Structure from motion","level":3,"score":0.42726439237594604},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.34514516592025757}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18293/dms2015-004","is_oa":false,"landing_page_url":"https://doi.org/10.18293/dms2015-004","pdf_url":null,"source":{"id":"https://openalex.org/S4386872205","display_name":"Proceedings","issn_l":"2326-3261","issn":["2326-3261"],"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":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Conferences on Distributed Multimedia Systems","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":13,"referenced_works":["https://openalex.org/W1696716473","https://openalex.org/W1978383016","https://openalex.org/W1985059397","https://openalex.org/W1991359796","https://openalex.org/W1991942383","https://openalex.org/W2002068647","https://openalex.org/W2054502547","https://openalex.org/W2098326400","https://openalex.org/W2165835468","https://openalex.org/W2168729417","https://openalex.org/W2249800031","https://openalex.org/W2539912446","https://openalex.org/W3023033790"],"related_works":["https://openalex.org/W1541334882","https://openalex.org/W2120943489","https://openalex.org/W1501297619","https://openalex.org/W1997997397","https://openalex.org/W2108243766","https://openalex.org/W2140220292","https://openalex.org/W2053820737","https://openalex.org/W2026674073","https://openalex.org/W1484667368","https://openalex.org/W2012241496"],"abstract_inverted_index":{"For":[0],"building":[1],"and":[2,34,95,130,161],"understanding":[3],"computational":[4],"models":[5],"of":[6,11,46,133,159,165],"human":[7,12,47,66,73,120],"motion,":[8],"behavioral":[9,149,176],"segmentation":[10,63,150],"motion":[13,30,32,35,48,62,67,74,110,121,134,152,160,163,172,179],"into":[14,100,126],"actions":[15],"is":[16,70,77,98,106,124],"a":[17,42,60,80,101,145],"crucial":[18],"step,":[19],"which":[20,85],"plays":[21],"an":[22,89],"important":[23],"part":[24],"in":[25,148],"many":[26],"domains":[27],"such":[28],"as":[29,79],"compression,":[31],"classification":[33],"analysis.":[36],"In":[37],"this":[38],"paper,":[39],"we":[40],"present":[41],"novel":[43],"symbolic":[44],"representation":[45],"capture":[49,68,75,122,153,180],"data,":[50,154],"called":[51],"the":[52,58,104,109,117,119,131,162,166],"Behavior":[53],"String":[54],"(BS).":[55],"Based":[56],"on":[57,93],"BS,":[59,118],"further":[61],"algorithm":[64,91],"for":[65,108,151],"data":[69,76,83,111,123],"proposed.":[71],"The":[72],"treated":[78],"high-dimensional":[81],"discrete":[82],"points,":[84],"are":[86,135],"clustered":[87],"by":[88,112],"alternative":[90],"based":[92],"density,":[94],"each":[96],"cluster":[97],"divided":[99],"character.":[102],"Then,":[103],"BS":[105],"produced":[107],"temporal":[113],"reverting.":[114],"By":[115],"analyzing":[116],"segmented":[125],"distinct":[127],"behavior":[128],"segments":[129],"cycles":[132,158],"found.":[136],"Experiments":[137],"show":[138],"that":[139],"our":[140],"method":[141],"not":[142],"only":[143],"has":[144],"good":[146],"performance":[147],"but":[155],"also":[156],"finds":[157],"clips":[164],"same":[167],"behaviors":[168],"from":[169],"long":[170],"original":[171],"sequence.":[173],"Keywords-motion":[174],"analysis;":[175],"segmentation;":[177],"clustering;":[178],"data;":[181],"cycle":[182]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
