{"id":"https://openalex.org/W2171030261","doi":"https://doi.org/10.1145/1014052.1014144","title":"Rotation invariant distance measures for trajectories","display_name":"Rotation invariant distance measures for trajectories","publication_year":2004,"publication_date":"2004-08-22","ids":{"openalex":"https://openalex.org/W2171030261","doi":"https://doi.org/10.1145/1014052.1014144","mag":"2171030261"},"language":"en","primary_location":{"id":"doi:10.1145/1014052.1014144","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1014052.1014144","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining","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/A5091785745","display_name":"Michail Vlachos","orcid":"https://orcid.org/0000-0003-1008-5290"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Michail Vlachos","raw_affiliation_strings":["UCR"],"affiliations":[{"raw_affiliation_string":"UCR","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063685438","display_name":"Dimitrios Gunopulos","orcid":"https://orcid.org/0000-0001-6339-1879"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"D. Gunopulos","raw_affiliation_strings":["UCR"],"affiliations":[{"raw_affiliation_string":"UCR","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5002203026","display_name":"Gautam Das","orcid":"https://orcid.org/0000-0002-4627-9065"},"institutions":[{"id":"https://openalex.org/I4210164937","display_name":"Microsoft Research (United Kingdom)","ror":"https://ror.org/05k87vq12","country_code":"GB","type":"company","lineage":["https://openalex.org/I1290206253","https://openalex.org/I4210164937"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Gautam Das","raw_affiliation_strings":["Microsoft Research"],"affiliations":[{"raw_affiliation_string":"Microsoft Research","institution_ids":["https://openalex.org/I4210164937"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5091785745"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":5.1425,"has_fulltext":false,"cited_by_count":94,"citation_normalized_percentile":{"value":0.96062252,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"707","last_page":"712"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9991000294685364,"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":0.9991000294685364,"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/T11309","display_name":"Music and Audio Processing","score":0.9958000183105469,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9944999814033508,"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/computer-science","display_name":"Computer science","score":0.7023333311080933},{"id":"https://openalex.org/keywords/normalization","display_name":"Normalization (sociology)","score":0.649956226348877},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5735284090042114},{"id":"https://openalex.org/keywords/rotation","display_name":"Rotation (mathematics)","score":0.5501455068588257},{"id":"https://openalex.org/keywords/invariant","display_name":"Invariant (physics)","score":0.514963686466217},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.47545549273490906},{"id":"https://openalex.org/keywords/bounded-function","display_name":"Bounded function","score":0.4494134187698364},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43674662709236145},{"id":"https://openalex.org/keywords/dynamic-time-warping","display_name":"Dynamic time warping","score":0.41799840331077576},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.36209115386009216},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.23573940992355347}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7023333311080933},{"id":"https://openalex.org/C136886441","wikidata":"https://www.wikidata.org/wiki/Q926129","display_name":"Normalization (sociology)","level":2,"score":0.649956226348877},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5735284090042114},{"id":"https://openalex.org/C74050887","wikidata":"https://www.wikidata.org/wiki/Q848368","display_name":"Rotation (mathematics)","level":2,"score":0.5501455068588257},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.514963686466217},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47545549273490906},{"id":"https://openalex.org/C34388435","wikidata":"https://www.wikidata.org/wiki/Q2267362","display_name":"Bounded function","level":2,"score":0.4494134187698364},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43674662709236145},{"id":"https://openalex.org/C88516994","wikidata":"https://www.wikidata.org/wiki/Q1268863","display_name":"Dynamic time warping","level":2,"score":0.41799840331077576},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.36209115386009216},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.23573940992355347},{"id":"https://openalex.org/C37914503","wikidata":"https://www.wikidata.org/wiki/Q156495","display_name":"Mathematical physics","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C19165224","wikidata":"https://www.wikidata.org/wiki/Q23404","display_name":"Anthropology","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/1014052.1014144","is_oa":false,"landing_page_url":"https://doi.org/10.1145/1014052.1014144","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.64.3167","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.64.3167","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://www.cs.ucr.edu/~mvlachos/pubs/kdd04.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.96.1113","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.96.1113","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://ranger.uta.edu/~gdas/websitepages/preprints-papers/p707-vlachos.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W116902681","https://openalex.org/W1548836129","https://openalex.org/W2001141328","https://openalex.org/W2012171749","https://openalex.org/W2034528422","https://openalex.org/W2044104836","https://openalex.org/W2048985799","https://openalex.org/W2064597564","https://openalex.org/W2066796814","https://openalex.org/W2066834853","https://openalex.org/W2077501305","https://openalex.org/W2116793329","https://openalex.org/W2133184712","https://openalex.org/W2133584444","https://openalex.org/W2147880780","https://openalex.org/W2151465245","https://openalex.org/W2160533343","https://openalex.org/W2788204165","https://openalex.org/W4232428446","https://openalex.org/W6679786028"],"related_works":["https://openalex.org/W2030799363","https://openalex.org/W2950183183","https://openalex.org/W2341338763","https://openalex.org/W2288425735","https://openalex.org/W2349923317","https://openalex.org/W2894081631","https://openalex.org/W2986063033","https://openalex.org/W2040439981","https://openalex.org/W2472888994","https://openalex.org/W1791724651"],"abstract_inverted_index":{"For":[0],"the":[1,18,26,94,114,168,171,174],"discovery":[2],"of":[3,17,97,173],"similar":[4,66],"patterns":[5,41,68],"in":[6,47,59,113,152,161],"1D":[7],"time-series,":[8,55],"it":[9],"is":[10,77,104,117],"very":[11,44],"typical":[12],"to":[13,80,119,138,141],"perform":[14],"a":[15,22,29,101],"normalization":[16],"data":[19,27],"(for":[20],"example":[21],"transformation":[23],"so":[24],"that":[25,103],"follow":[28],"zero":[30],"mean":[31],"and":[32,42,107,123,143,158,170,178],"unit":[33],"standard":[34],"deviation).":[35],"Such":[36],"transformations":[37],"can":[38,69,124,144],"reveal":[39],"latent":[40],"are":[43,136],"commonly":[45],"used":[46],"datamining":[48],"applications.":[49],"However,":[50],"when":[51],"dealing":[52],"with":[53],"multidimensional":[54],"which":[56],"appear":[57],"naturally":[58],"applications":[60,147],"such":[61,86,154],"as":[62,87,155],"video-tracking,":[63],"motion-capture":[64,162],"etc,":[65],"motion":[67],"also":[70],"be":[71,125],"expressed":[72],"at":[73],"different":[74],"orientations.":[75],"It":[76],"therefore":[78],"imperative":[79],"provide":[81],"support":[82],"for":[83,148],"additional":[84],"transformations,":[85],"rotation.":[88],"In":[89],"this":[90],"work,":[91],"we":[92,165],"transform":[93],"positional":[95],"information":[96],"moving":[98],"data,":[99],"into":[100],"space":[102,116],"translation,":[105],"scale":[106],"rotation":[108],"invariant.":[109],"Our":[110],"distance":[111],"measure":[112],"new":[115],"able":[118],"detect":[120],"elastic":[121],"matches":[122],"efficiently":[126],"lower":[127],"bounded,":[128],"thus":[129],"being":[130],"computationally":[131],"tractable.":[132],"The":[133],"proposed":[134],"methods":[135],"easy":[137],"implement,":[139],"fast":[140],"compute":[142],"have":[145],"many":[146],"real":[149,177],"world":[150],"problems,":[151],"areas":[153],"handwriting":[156,180],"recognition":[157],"posture":[159],"estimation":[160],"data.":[163,181],"Finally,":[164],"empirically":[166],"demonstrate":[167],"accuracy":[169],"efficiency":[172],"technique,":[175],"using":[176],"synthetic":[179]},"counts_by_year":[{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":10},{"year":2017,"cited_by_count":4},{"year":2016,"cited_by_count":6},{"year":2015,"cited_by_count":4},{"year":2014,"cited_by_count":6},{"year":2013,"cited_by_count":2},{"year":2012,"cited_by_count":6}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
