{"id":"https://openalex.org/W2957108464","doi":"https://doi.org/10.1109/tvcg.2019.2934335","title":"Void-and-Cluster Sampling of Large Scattered Data and Trajectories","display_name":"Void-and-Cluster Sampling of Large Scattered Data and Trajectories","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2957108464","doi":"https://doi.org/10.1109/tvcg.2019.2934335","mag":"2957108464","pmid":"https://pubmed.ncbi.nlm.nih.gov/31425103"},"language":"en","primary_location":{"id":"doi:10.1109/tvcg.2019.2934335","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvcg.2019.2934335","pdf_url":null,"source":{"id":"https://openalex.org/S84775595","display_name":"IEEE Transactions on Visualization and Computer Graphics","issn_l":"1077-2626","issn":["1077-2626","1941-0506","2160-9306"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Visualization and Computer Graphics","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","pubmed"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/1907.05073","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5055311360","display_name":"Tobias Rapp","orcid":"https://orcid.org/0000-0002-5436-5553"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Tobias Rapp","raw_affiliation_strings":["Karlsruhe Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033421842","display_name":"Christoph Peters","orcid":"https://orcid.org/0000-0001-8140-1516"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christoph Peters","raw_affiliation_strings":["Karlsruhe Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology","institution_ids":["https://openalex.org/I102335020"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5026357260","display_name":"Carsten Dachsbacher","orcid":"https://orcid.org/0000-0003-4690-3574"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Carsten Dachsbacher","raw_affiliation_strings":["Karlsruhe Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Karlsruhe Institute of Technology","institution_ids":["https://openalex.org/I102335020"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5055311360"],"corresponding_institution_ids":["https://openalex.org/I102335020"],"apc_list":null,"apc_paid":null,"fwci":2.1699,"has_fulltext":false,"cited_by_count":25,"citation_normalized_percentile":{"value":0.90650388,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":"26","issue":"1","first_page":"1","last_page":"1"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9763000011444092,"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"}},"topics":[{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.9763000011444092,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9616000056266785,"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/T10057","display_name":"Face and Expression Recognition","score":0.9549000263214111,"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":0.749443531036377},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.5820075869560242},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.5813100337982178},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5300692319869995},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.48800864815711975},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.452340304851532},{"id":"https://openalex.org/keywords/importance-sampling","display_name":"Importance sampling","score":0.4187774658203125},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2348773181438446},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.2220541536808014},{"id":"https://openalex.org/keywords/monte-carlo-method","display_name":"Monte Carlo method","score":0.11662223935127258},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.10981887578964233}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.749443531036377},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.5820075869560242},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.5813100337982178},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5300692319869995},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.48800864815711975},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.452340304851532},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.4187774658203125},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2348773181438446},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.2220541536808014},{"id":"https://openalex.org/C19499675","wikidata":"https://www.wikidata.org/wiki/Q232207","display_name":"Monte Carlo method","level":2,"score":0.11662223935127258},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.10981887578964233},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tvcg.2019.2934335","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tvcg.2019.2934335","pdf_url":null,"source":{"id":"https://openalex.org/S84775595","display_name":"IEEE Transactions on Visualization and Computer Graphics","issn_l":"1077-2626","issn":["1077-2626","1941-0506","2160-9306"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Visualization and Computer Graphics","raw_type":"journal-article"},{"id":"pmid:31425103","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/31425103","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on visualization and computer graphics","raw_type":null},{"id":"pmh:oai:arXiv.org:1907.05073","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1907.05073","pdf_url":"https://arxiv.org/pdf/1907.05073","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:1907.05073","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1907.05073","pdf_url":"https://arxiv.org/pdf/1907.05073","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":28,"referenced_works":["https://openalex.org/W1753847782","https://openalex.org/W1984609374","https://openalex.org/W1994982193","https://openalex.org/W1995224664","https://openalex.org/W1999498941","https://openalex.org/W2005010120","https://openalex.org/W2006045909","https://openalex.org/W2009886804","https://openalex.org/W2034901941","https://openalex.org/W2061987443","https://openalex.org/W2072495471","https://openalex.org/W2073037495","https://openalex.org/W2088009038","https://openalex.org/W2088803423","https://openalex.org/W2098492528","https://openalex.org/W2099272828","https://openalex.org/W2122595030","https://openalex.org/W2141827635","https://openalex.org/W2509745984","https://openalex.org/W2534227439","https://openalex.org/W2754777568","https://openalex.org/W2755764088","https://openalex.org/W2770844691","https://openalex.org/W2794996660","https://openalex.org/W2807138665","https://openalex.org/W2888277127","https://openalex.org/W2899673449","https://openalex.org/W3021622851"],"related_works":["https://openalex.org/W4255837520","https://openalex.org/W2389214306","https://openalex.org/W4235240664","https://openalex.org/W2965083567","https://openalex.org/W2387011115","https://openalex.org/W3151146928","https://openalex.org/W2742914308","https://openalex.org/W2330004501","https://openalex.org/W2017089693","https://openalex.org/W2703295919"],"abstract_inverted_index":{"We":[0,83,125],"propose":[1],"a":[2,18,42,79,95,107,117],"data":[3,8,76],"reduction":[4],"technique":[5,16,65,86],"for":[6,91],"scattered":[7],"based":[9],"on":[10,70],"statistical":[11],"sampling.":[12],"Our":[13],"void-and-cluster":[14],"sampling":[15,64,131],"finds":[17],"representative":[19],"subset":[20],"that":[21,73,138],"is":[22],"optimally":[23],"distributed":[24],"in":[25,55,94],"the":[26,32,56,71,122,134,152],"spatial":[27],"domain":[28,59],"with":[29],"respect":[30],"to":[31,41,49,87,113,132,150],"blue":[33],"noise":[34],"property.":[35],"In":[36],"addition,":[37],"it":[38],"can":[39],"adapt":[40],"given":[43],"density":[44],"function,":[45],"which":[46],"we":[47,105,142],"use":[48,143],"sample":[50,88],"regions":[51],"of":[52,119,136,157],"high":[53],"complexity":[54],"multivariate":[57],"value":[58],"more":[60],"densely.":[61],"Moreover,":[62],"our":[63,85,158],"implicitly":[66],"defines":[67],"an":[68,99],"ordering":[69],"samples":[72,120,137],"enables":[74],"progressive":[75],"loading":[77],"and":[78,101,109,147,155],"continuous":[80,110],"level-of-detail":[81],"representation.":[82],"extend":[84],"time-dependent":[89],"trajectories,":[90],"example":[92],"pathlines":[93],"time":[96],"interval,":[97],"using":[98],"efficient":[100],"iterative":[102],"approach.":[103],"Furthermore,":[104],"introduce":[106],"local":[108],"error":[111,128,145],"measure":[112,129,146],"quantify":[114],"how":[115],"well":[116],"set":[118],"represents":[121],"original":[123],"dataset.":[124],"apply":[126],"this":[127,144],"during":[130],"guide":[133],"number":[135],"are":[139],"taken.":[140],"Finally,":[141],"other":[148],"quantities":[149],"evaluate":[151],"quality,":[153],"performance,":[154],"scalability":[156],"algorithm.":[159]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":5}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}