{"id":"https://openalex.org/W2783528938","doi":"https://doi.org/10.1109/bigdata.2017.8258329","title":"Optimal viewpoint finding for 3D visualization of spatio-temporal vehicle trajectories on caution crossroads detected from vehicle recorder big data","display_name":"Optimal viewpoint finding for 3D visualization of spatio-temporal vehicle trajectories on caution crossroads detected from vehicle recorder big data","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2783528938","doi":"https://doi.org/10.1109/bigdata.2017.8258329","mag":"2783528938"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2017.8258329","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2017.8258329","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Big Data (Big Data)","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/A5072400997","display_name":"Masahiko Itoh","orcid":"https://orcid.org/0000-0002-1604-0715"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]},{"id":"https://openalex.org/I90023481","display_name":"National Institute of Information and Communications Technology","ror":"https://ror.org/016bgq349","country_code":"JP","type":"facility","lineage":["https://openalex.org/I90023481"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Masahiko Itoh","raw_affiliation_strings":["The University of Tokyo, National Institute of Information and Communications Technology"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo, National Institute of Information and Communications Technology","institution_ids":["https://openalex.org/I90023481","https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109280433","display_name":"Daisaku Yokoyama","orcid":null},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Daisaku Yokoyama","raw_affiliation_strings":["The University of Tokyo"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005790090","display_name":"Masashi Toyoda","orcid":"https://orcid.org/0000-0001-9473-5531"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masashi Toyoda","raw_affiliation_strings":["The University of Tokyo"],"affiliations":[{"raw_affiliation_string":"The University of Tokyo","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056438865","display_name":"Masaru Kitsuregawa","orcid":"https://orcid.org/0000-0003-4027-2994"},"institutions":[{"id":"https://openalex.org/I184597095","display_name":"National Institute of Informatics","ror":"https://ror.org/04ksd4g47","country_code":"JP","type":"facility","lineage":["https://openalex.org/I1319490839","https://openalex.org/I184597095","https://openalex.org/I4210158934"]},{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Masaru Kitsuregawa","raw_affiliation_strings":["National Institute of Informatics, The University of Tokyo"],"affiliations":[{"raw_affiliation_string":"National Institute of Informatics, The University of Tokyo","institution_ids":["https://openalex.org/I184597095","https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5072400997"],"corresponding_institution_ids":["https://openalex.org/I74801974","https://openalex.org/I90023481"],"apc_list":null,"apc_paid":null,"fwci":0.091,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.50119008,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"3426","last_page":"3434"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","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"}},"topics":[{"id":"https://openalex.org/T10799","display_name":"Data Visualization and Analytics","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/T11106","display_name":"Data Management and Algorithms","score":0.9886999726295471,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9848999977111816,"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":0.7498315572738647},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.6066327095031738},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.6035802364349365},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.5886150598526001},{"id":"https://openalex.org/keywords/viewpoints","display_name":"Viewpoints","score":0.5584474205970764},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5487646460533142},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5473206639289856},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.457535058259964},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4499911367893219},{"id":"https://openalex.org/keywords/entropy","display_name":"Entropy (arrow of time)","score":0.4369284510612488},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.42078158259391785},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.344768226146698},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3400135636329651}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7498315572738647},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.6066327095031738},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.6035802364349365},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.5886150598526001},{"id":"https://openalex.org/C2776035091","wikidata":"https://www.wikidata.org/wiki/Q7928819","display_name":"Viewpoints","level":2,"score":0.5584474205970764},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5487646460533142},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5473206639289856},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.457535058259964},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4499911367893219},{"id":"https://openalex.org/C106301342","wikidata":"https://www.wikidata.org/wiki/Q4117933","display_name":"Entropy (arrow of time)","level":2,"score":0.4369284510612488},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.42078158259391785},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.344768226146698},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3400135636329651},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata.2017.8258329","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2017.8258329","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.44999998807907104,"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W1695704110","https://openalex.org/W1967994289","https://openalex.org/W1988726303","https://openalex.org/W1989797507","https://openalex.org/W2005948381","https://openalex.org/W2009658718","https://openalex.org/W2027444103","https://openalex.org/W2029129133","https://openalex.org/W2045434147","https://openalex.org/W2056638635","https://openalex.org/W2088938045","https://openalex.org/W2097728763","https://openalex.org/W2102493509","https://openalex.org/W2128769229","https://openalex.org/W2141834649","https://openalex.org/W2143203329","https://openalex.org/W2147038605","https://openalex.org/W2147545324","https://openalex.org/W2151412512","https://openalex.org/W2152935971","https://openalex.org/W2154046714","https://openalex.org/W2210119327","https://openalex.org/W3148562542","https://openalex.org/W4210813334","https://openalex.org/W4237453232","https://openalex.org/W4248980853","https://openalex.org/W6678755304"],"related_works":["https://openalex.org/W2385368906","https://openalex.org/W2902924992","https://openalex.org/W2626642044","https://openalex.org/W2619807045","https://openalex.org/W2388758053","https://openalex.org/W93537448","https://openalex.org/W2949734191","https://openalex.org/W2017333877","https://openalex.org/W2048332520","https://openalex.org/W4233821346"],"abstract_inverted_index":{"Traffic":[0],"accidents":[1],"are":[2,148],"still":[3],"troubling":[4],"our":[5,184],"society.":[6],"The":[7,80],"number":[8],"of":[9,44,92,115,131,138,145,163,172,224],"drive":[10],"recorders":[11],"sold":[12],"has":[13],"increased,":[14],"and":[15,50,56,72,90,237],"therefore":[16],"we":[17,120],"can":[18,186],"collect":[19],"large-scale":[20],"vehicle":[21,45,93,132,231],"recorder":[22,46,232],"data":[23,76,234],"to":[24,27,70,84,106,189,201,235],"be":[25,187],"used":[26],"support":[28],"traffic":[29],"safety.":[30],"We":[31,152,182,195,210,219],"have":[32],"developed":[33],"a":[34,59,63,135,166,170,173,177],"system":[35],"for":[36,104,111,127,206],"detecting":[37],"potentially":[38,225],"risky":[39,226],"crossroads":[40,139,190,227],"on":[41,77,134,157,176],"the":[42,198,212],"basis":[43],"data,":[47],"road":[48],"shapes,":[49],"weather":[51],"information.":[52],"Visualization":[53],"combining":[54],"space":[55],"time":[57,65],"in":[58],"single":[60],"display":[61],"called":[62],"\u201cspace":[64],"cube":[66],"(STC)\u201d":[67],"helps":[68],"us":[69,83],"understand":[71],"analyze":[73,238],"spatio-temporal":[74,129],"mobility":[75],"caution":[78],"crossroads.":[79,208],"STC":[81],"enables":[82],"simultaneously":[85],"explore":[86],"not":[87],"only":[88],"shapes":[89],"positions":[91],"trajectories":[94,133,164],"but":[95],"also":[96,196],"their":[97],"temporal":[98],"distributions.":[99],"However,":[100],"it":[101],"is":[102],"difficult":[103],"users":[105],"manually":[107],"find":[108,202],"good":[109],"viewpoints":[110],"understanding":[112],"such":[113],"characteristics":[114,130],"trajectories.":[116],"In":[117],"this":[118,146],"paper,":[119],"propose":[121],"an":[122,141,154,203,221],"optimal":[123,204],"viewpoint":[124,158,174,205],"selection":[125],"method":[126,200,214],"visualizing":[128],"large":[136],"set":[137],"using":[140],"STC.":[142],"Major":[143],"contributions":[144],"paper":[147],"as":[149,169],"follows:":[150],"(1)":[151],"provide":[153],"algorithm":[155],"based":[156],"entropy":[159],"weighted":[160],"by":[161],"angles":[162],"with":[165,191,240],"horizontal":[167],"line":[168],"measure":[171],"quality":[175],"projected":[178],"2D":[179],"image.":[180],"(2)":[181],"demonstrate":[183],"solution":[185],"adapted":[188],"different":[192],"trajectory":[193],"shapes.":[194],"extend":[197],"proposed":[199,213],"multiple":[207],"(3)":[209],"verify":[211],"through":[215],"users'":[216],"evaluations.":[217],"(4)":[218],"construct":[220],"overviewing":[222],"catalog":[223],"detected":[228],"from":[229],"real":[230],"big":[233],"discuss":[236],"them":[239],"stakeholders.":[241]},"counts_by_year":[{"year":2021,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
