{"id":"https://openalex.org/W3093007847","doi":"https://doi.org/10.1145/3394171.3413713","title":"Concept Drift Detection for Multivariate Data Streams and Temporal Segmentation of Daylong Egocentric Videos","display_name":"Concept Drift Detection for Multivariate Data Streams and Temporal Segmentation of Daylong Egocentric Videos","publication_year":2020,"publication_date":"2020-10-12","ids":{"openalex":"https://openalex.org/W3093007847","doi":"https://doi.org/10.1145/3394171.3413713","mag":"3093007847"},"language":"en","primary_location":{"id":"doi:10.1145/3394171.3413713","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3413713","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Multimedia","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/A5031815035","display_name":"Pravin Nagar","orcid":"https://orcid.org/0000-0002-8419-3481"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Pravin Nagar","raw_affiliation_strings":["Indian Institute of Technology Delhi, New Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Delhi, New Delhi, India","institution_ids":["https://openalex.org/I68891433"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056667053","display_name":"Mansi Khemka","orcid":null},"institutions":[{"id":"https://openalex.org/I78577930","display_name":"Columbia University","ror":"https://ror.org/00hj8s172","country_code":"US","type":"education","lineage":["https://openalex.org/I78577930"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mansi Khemka","raw_affiliation_strings":["Columbia University, New York City, NY, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Columbia University, New York City, NY, USA","institution_ids":["https://openalex.org/I78577930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5101532736","display_name":"Chetan Arora","orcid":"https://orcid.org/0000-0003-0155-0250"},"institutions":[{"id":"https://openalex.org/I68891433","display_name":"Indian Institute of Technology Delhi","ror":"https://ror.org/049tgcd06","country_code":"IN","type":"education","lineage":["https://openalex.org/I68891433"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Chetan Arora","raw_affiliation_strings":["Indian Institute of Technology Delhi, New Delhi, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Indian Institute of Technology Delhi, New Delhi, India","institution_ids":["https://openalex.org/I68891433"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.6834,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.77979149,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"9","issue":null,"first_page":"1065","last_page":"1074"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.9972000122070312,"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/T11439","display_name":"Video Analysis and Summarization","score":0.9972000122070312,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9958000183105469,"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/T12761","display_name":"Data Stream Mining Techniques","score":0.9958000183105469,"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":0.8161871433258057},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7165125608444214},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6973543763160706},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5193511247634888},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.45721885561943054},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.4569878578186035},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4507113993167877},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.4267970025539398},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.42477384209632874},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.39868879318237305}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8161871433258057},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7165125608444214},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6973543763160706},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5193511247634888},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.45721885561943054},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.4569878578186035},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4507113993167877},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.4267970025539398},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.42477384209632874},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.39868879318237305},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3394171.3413713","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3413713","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.5099999904632568},{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.4300000071525574}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":48,"referenced_works":["https://openalex.org/W658559791","https://openalex.org/W854053868","https://openalex.org/W1948812921","https://openalex.org/W2016776918","https://openalex.org/W2018068650","https://openalex.org/W2031765333","https://openalex.org/W2044248322","https://openalex.org/W2070999216","https://openalex.org/W2120645068","https://openalex.org/W2130126195","https://openalex.org/W2143991132","https://openalex.org/W2147806277","https://openalex.org/W2163605009","https://openalex.org/W2214946242","https://openalex.org/W2233620181","https://openalex.org/W2287077125","https://openalex.org/W2341342588","https://openalex.org/W2430293125","https://openalex.org/W2432964524","https://openalex.org/W2519015518","https://openalex.org/W2519328139","https://openalex.org/W2550143307","https://openalex.org/W2570848768","https://openalex.org/W2593737669","https://openalex.org/W2736877958","https://openalex.org/W2740268464","https://openalex.org/W2755876276","https://openalex.org/W2768019018","https://openalex.org/W2769743454","https://openalex.org/W2775282868","https://openalex.org/W2785568478","https://openalex.org/W2793037070","https://openalex.org/W2884002012","https://openalex.org/W2891270996","https://openalex.org/W2891502390","https://openalex.org/W2951866553","https://openalex.org/W2962876901","https://openalex.org/W2963825147","https://openalex.org/W2963909176","https://openalex.org/W2963916161","https://openalex.org/W2964214371","https://openalex.org/W2964347220","https://openalex.org/W2982035676","https://openalex.org/W2997314266","https://openalex.org/W3098401379","https://openalex.org/W3100110387","https://openalex.org/W4234552385","https://openalex.org/W4244531973"],"related_works":["https://openalex.org/W2055243143","https://openalex.org/W4233585817","https://openalex.org/W1522196789","https://openalex.org/W2016045932","https://openalex.org/W1675950995","https://openalex.org/W2188882668","https://openalex.org/W2088323302","https://openalex.org/W2004379491","https://openalex.org/W2021544484","https://openalex.org/W2083140487"],"abstract_inverted_index":{"The":[0,65],"long":[1],"and":[2,37,59,217],"unconstrained":[3],"nature":[4,67],"of":[5,26,48,68,138,184,196],"egocentric":[6,31,105,122,202],"videos":[7],"makes":[8,70],"it":[9,71,175],"imperative":[10],"to":[11,52,73,145,180],"use":[12],"temporal":[13,83,115],"segmentation":[14,116],"as":[15,128,205,207],"an":[16,30],"important":[17],"pre-processing":[18],"step":[19],"for":[20,104,120,200],"many":[21],"higher-level":[22],"inference":[23],"tasks.":[24],"Activities":[25],"the":[27,46,53,126,167,173,182,185,197],"wearer":[28],"in":[29,132,172],"video":[32,203],"typically":[33],"span":[34],"over":[35],"hours":[36],"are":[38,143],"often":[39],"separated":[40],"by":[41],"slow,":[42],"gradual":[43],"changes.":[44,64],"Furthermore,":[45],"change":[47],"camera":[49],"viewpoint":[50],"due":[51],"wearer's":[54],"head":[55],"motion":[56],"causes":[57],"frequent":[58],"extreme,":[60],"but,":[61],"spurious":[62],"scene":[63],"continuous":[66],"boundaries":[69],"difficult":[72],"apply":[74],"traditional":[75],"Markov":[76],"Random":[77],"Field":[78],"(MRF)":[79],"pipelines":[80],"relying":[81],"on":[82,163],"discontinuity,":[84],"whereas":[85],"deep":[86],"Long":[87],"Short":[88],"Term":[89],"Memory":[90],"(LSTM)":[91],"networks":[92],"gather":[93],"context":[94],"only":[95],"upto":[96],"a":[97,112,133],"few":[98],"hundred":[99],"frames,":[100],"rendering":[101],"them":[102],"ineffective":[103],"videos.":[106,123],"In":[107],"this":[108],"paper,":[109],"we":[110,191],"present":[111],"novel":[113],"unsupervised":[114],"technique":[117],"especially":[118],"suited":[119],"day-long":[121],"We":[124],"formulate":[125],"problem":[127],"detecting":[129],"concept":[130,147],"drift":[131,148],"time-varying,":[134],"non":[135],"i.i.d.":[136],"sequence":[137],"frames.":[139],"Statistically":[140],"bounded":[141],"thresholds":[142],"calculated":[144],"detect":[146],"between":[149],"two":[150],"temporally":[151],"adjacent":[152],"multivariate":[153],"data":[154],"segments":[155],"with":[156],"different":[157],"underlying":[158],"distributions":[159],"while":[160],"establishing":[161],"guarantees":[162],"false":[164],"positives.":[165],"Since":[166],"derived":[168,210],"threshold":[169],"indicates":[170],"confidence":[171],"prediction,":[174],"can":[176],"also":[177],"be":[178],"used":[179],"control":[181],"granularity":[183],"output":[186],"segmentation.":[187],"Using":[188],"our":[189],"technique,":[190],"report":[192],"significantly":[193],"improved":[194],"state":[195],"art":[198],"f-measure":[199],"daylong":[201],"datasets,":[204],"well":[206],"photostream":[208],"datasets":[209],"from":[211],"them:":[212],"HUJI~(73.01%,":[213],"59.44%),":[214],"UTEgo~(58.41%,":[215],"60.61%)":[216],"Disney~(67.63%,":[218],"68.83%).":[219]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}