{"id":"https://openalex.org/W2908971035","doi":"https://doi.org/10.1109/dicta.2018.8615794","title":"Image Analytics for Train Crowd Estimation","display_name":"Image Analytics for Train Crowd Estimation","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2908971035","doi":"https://doi.org/10.1109/dicta.2018.8615794","mag":"2908971035"},"language":"en","primary_location":{"id":"doi:10.1109/dicta.2018.8615794","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2018.8615794","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Digital Image Computing: Techniques and Applications (DICTA)","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/A5077158605","display_name":"Choon Giap Goh","orcid":null},"institutions":[{"id":"https://openalex.org/I168639165","display_name":"Singapore Institute of Technology","ror":"https://ror.org/01v2c2791","country_code":"SG","type":"education","lineage":["https://openalex.org/I168639165"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Choon Giap Goh","raw_affiliation_strings":["Singapore Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Singapore Institute of Technology","institution_ids":["https://openalex.org/I168639165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000359384","display_name":"Wee Han Lim","orcid":null},"institutions":[{"id":"https://openalex.org/I168639165","display_name":"Singapore Institute of Technology","ror":"https://ror.org/01v2c2791","country_code":"SG","type":"education","lineage":["https://openalex.org/I168639165"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Wee Han Lim","raw_affiliation_strings":["Singapore Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Singapore Institute of Technology","institution_ids":["https://openalex.org/I168639165"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5049094614","display_name":"Justus Chua","orcid":null},"institutions":[{"id":"https://openalex.org/I168639165","display_name":"Singapore Institute of Technology","ror":"https://ror.org/01v2c2791","country_code":"SG","type":"education","lineage":["https://openalex.org/I168639165"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Justus Chua","raw_affiliation_strings":["Singapore Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Singapore Institute of Technology","institution_ids":["https://openalex.org/I168639165"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058777060","display_name":"Indriyati Atmosukarto","orcid":"https://orcid.org/0000-0002-8338-3734"},"institutions":[{"id":"https://openalex.org/I168639165","display_name":"Singapore Institute of Technology","ror":"https://ror.org/01v2c2791","country_code":"SG","type":"education","lineage":["https://openalex.org/I168639165"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Indriyati Atmosukarto","raw_affiliation_strings":["Singapore Institute of Technology"],"affiliations":[{"raw_affiliation_string":"Singapore Institute of Technology","institution_ids":["https://openalex.org/I168639165"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5077158605"],"corresponding_institution_ids":["https://openalex.org/I168639165"],"apc_list":null,"apc_paid":null,"fwci":0.3134,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.63865654,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9979000091552734,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9979000091552734,"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/T11344","display_name":"Traffic Prediction and Management Techniques","score":0.9922000169754028,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T11500","display_name":"Evacuation and Crowd Dynamics","score":0.9857000112533569,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/train","display_name":"Train","score":0.886507511138916},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7056814432144165},{"id":"https://openalex.org/keywords/queue","display_name":"Queue","score":0.6656290292739868},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5575853586196899},{"id":"https://openalex.org/keywords/doors","display_name":"Doors","score":0.47542718052864075},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4449050724506378},{"id":"https://openalex.org/keywords/elevator","display_name":"Elevator","score":0.4194445013999939},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4089314937591553},{"id":"https://openalex.org/keywords/simulation","display_name":"Simulation","score":0.36698755621910095},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17231491208076477},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.15034833550453186}],"concepts":[{"id":"https://openalex.org/C190839683","wikidata":"https://www.wikidata.org/wiki/Q2448197","display_name":"Train","level":2,"score":0.886507511138916},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7056814432144165},{"id":"https://openalex.org/C160403385","wikidata":"https://www.wikidata.org/wiki/Q220543","display_name":"Queue","level":2,"score":0.6656290292739868},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5575853586196899},{"id":"https://openalex.org/C125209513","wikidata":"https://www.wikidata.org/wiki/Q4037520","display_name":"Doors","level":2,"score":0.47542718052864075},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4449050724506378},{"id":"https://openalex.org/C147021018","wikidata":"https://www.wikidata.org/wiki/Q252451","display_name":"Elevator","level":2,"score":0.4194445013999939},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4089314937591553},{"id":"https://openalex.org/C44154836","wikidata":"https://www.wikidata.org/wiki/Q45045","display_name":"Simulation","level":1,"score":0.36698755621910095},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17231491208076477},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.15034833550453186},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"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/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C66938386","wikidata":"https://www.wikidata.org/wiki/Q633538","display_name":"Structural engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dicta.2018.8615794","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dicta.2018.8615794","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 Digital Image Computing: Techniques and Applications (DICTA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.6000000238418579,"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1910776219","https://openalex.org/W2143043044","https://openalex.org/W2729018917","https://openalex.org/W2748454020","https://openalex.org/W2895807188","https://openalex.org/W4244518386","https://openalex.org/W6739846767"],"related_works":["https://openalex.org/W4241837227","https://openalex.org/W1507618586","https://openalex.org/W3016239942","https://openalex.org/W2487340859","https://openalex.org/W2486091485","https://openalex.org/W1992739161","https://openalex.org/W4293365988","https://openalex.org/W2990197615","https://openalex.org/W4296481904","https://openalex.org/W2388571181"],"abstract_inverted_index":{"Overcrowding":[0],"is":[1,79],"a":[2,82,136,142],"common":[3],"problem":[4],"faced":[5],"by":[6],"train":[7,16,99,104,116,147,185,193],"commuters":[8,20,109,119],"in":[9,46,52],"many":[10],"countries.":[11],"While":[12],"waiting":[13,112],"for":[14,113,145],"the":[15,18,38,69,72,86,97,103,114,118,129,146,156,165,168,173,177,181],"at":[17,26],"stations,":[19],"tend":[21,63],"to":[22,31,64,80,84,108,120,125,163,192,205],"cluster":[23],"and":[24,33,41,175,194],"queue":[25],"doors":[27],"that":[28,35],"are":[29,111,203],"closest":[30],"escalators":[32],"elevators":[34],"lead":[36],"towards":[37],"station":[39],"entrances":[40],"exits.":[42],"This":[43,133],"scenario":[44],"results":[45],"trains":[47,174],"not":[48],"being":[49],"fully":[50],"utilized":[51],"terms":[53],"of":[54,71,76,91,158,184,212],"their":[55],"capacity.":[56],"As":[57],"cabins":[58,90],"with":[59,208],"certain":[60],"door":[61],"positions":[62],"be":[65],"more":[66],"crowded":[67],"than":[68],"rest":[70],"cabins.":[73,186],"The":[74],"objective":[75],"this":[77,151],"paper":[78],"provide":[81],"methodology":[83],"estimate":[85],"crowd":[87,182],"density":[88,106,131],"within":[89],"incoming":[92,115],"trains,":[93],"while":[94],"leveraging":[95],"on":[96,128],"existing":[98,169],"CCTV":[100],"infrastructures.":[101],"Providing":[102],"cabin":[105,124],"information":[107],"who":[110],"allows":[117],"better":[121,137],"select":[122],"which":[123],"board":[126],"based":[127,180],"provided":[130],"information.":[132],"will":[134],"facilitate":[135],"commuting":[138],"experience":[139],"without":[140],"incurring":[141],"high":[143],"cost":[144],"operator.":[148],"To":[149],"achieve":[150],"objective,":[152],"we":[153],"have":[154],"adopted":[155],"usage":[157],"deep":[159],"convolutional":[160,197],"neural":[161,198],"networks":[162],"analyze":[164],"footage":[166],"from":[167],"security":[170],"camera":[171],"inside":[172],"classify":[176],"images":[178],"frames":[179],"level":[183],"Three":[187],"different":[188,196],"experiments":[189],"were":[190],"conducted":[191],"test":[195],"network":[199],"models.":[200],"All":[201],"models":[202],"able":[204],"make":[206],"classification":[207],"an":[209],"accuracy":[210],"rate":[211],"over":[213],"90%.":[214]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
