{"id":"https://openalex.org/W4200491439","doi":"https://doi.org/10.1109/gcce53005.2021.9621903","title":"LSTM-Based Prediction Method of Crowd Behavior for Robust to Pedestrian Detection Error","display_name":"LSTM-Based Prediction Method of Crowd Behavior for Robust to Pedestrian Detection Error","publication_year":2021,"publication_date":"2021-10-12","ids":{"openalex":"https://openalex.org/W4200491439","doi":"https://doi.org/10.1109/gcce53005.2021.9621903"},"language":"en","primary_location":{"id":"doi:10.1109/gcce53005.2021.9621903","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce53005.2021.9621903","pdf_url":null,"source":{"id":"https://openalex.org/S4363607807","display_name":"2021 IEEE 10th Global Conference on Consumer Electronics (GCCE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 10th Global Conference on Consumer Electronics (GCCE)","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/A5070427170","display_name":"Isamu Kamoto","orcid":null},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Isamu Kamoto","raw_affiliation_strings":["Graduate School of Engineering, Hokkaido University, Sapporo, Hokkaido, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering, Hokkaido University, Sapporo, Hokkaido, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080388789","display_name":"Takayuki Abe","orcid":"https://orcid.org/0000-0002-2295-7458"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Takayuki Abe","raw_affiliation_strings":["Graduate School of Engineering, Hokkaido University, Sapporo, Hokkaido, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering, Hokkaido University, Sapporo, Hokkaido, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073197671","display_name":"Sho Takahashi","orcid":"https://orcid.org/0000-0002-5338-5990"},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Sho Takahashi","raw_affiliation_strings":["Faculty of Engineering, Hokkaido University, Sapporo, Hokkaido, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, Hokkaido University, Sapporo, Hokkaido, Japan","institution_ids":["https://openalex.org/I205349734"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113963450","display_name":"Toru Hagiwara","orcid":null},"institutions":[{"id":"https://openalex.org/I205349734","display_name":"Hokkaido University","ror":"https://ror.org/02e16g702","country_code":"JP","type":"education","lineage":["https://openalex.org/I205349734"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Toru Hagiwara","raw_affiliation_strings":["Faculty of Engineering, Hokkaido University, Sapporo, Hokkaido, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Engineering, Hokkaido University, Sapporo, Hokkaido, Japan","institution_ids":["https://openalex.org/I205349734"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I205349734"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"218","last_page":"219"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9623000025749207,"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":0.9623000025749207,"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":0.9578999876976013,"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/T13924","display_name":"Internet of Things and Social Network Interactions","score":0.9527999758720398,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/pedestrian","display_name":"Pedestrian","score":0.8986756205558777},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7758824825286865},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.5857318639755249},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5704143047332764},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5268769860267639},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4435029923915863},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.30022940039634705},{"id":"https://openalex.org/keywords/transport-engineering","display_name":"Transport engineering","score":0.1731264889240265},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12660512328147888}],"concepts":[{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.8986756205558777},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7758824825286865},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.5857318639755249},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5704143047332764},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5268769860267639},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4435029923915863},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30022940039634705},{"id":"https://openalex.org/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.1731264889240265},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12660512328147888}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/gcce53005.2021.9621903","is_oa":false,"landing_page_url":"https://doi.org/10.1109/gcce53005.2021.9621903","pdf_url":null,"source":{"id":"https://openalex.org/S4363607807","display_name":"2021 IEEE 10th Global Conference on Consumer Electronics (GCCE)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE 10th Global Conference on Consumer Electronics (GCCE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.49000000953674316,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W1861492603","https://openalex.org/W2064675550","https://openalex.org/W2603203130","https://openalex.org/W2889508143","https://openalex.org/W3018757597","https://openalex.org/W6639102338","https://openalex.org/W6777046832"],"related_works":["https://openalex.org/W2972620127","https://openalex.org/W2981141433","https://openalex.org/W2802018156","https://openalex.org/W4313315626","https://openalex.org/W2101531944","https://openalex.org/W2922437833","https://openalex.org/W2100052226","https://openalex.org/W4312696271","https://openalex.org/W4223892596","https://openalex.org/W2933098581"],"abstract_inverted_index":{"The":[0,113,129],"traffic":[1],"accidents":[2],"at":[3],"crossing":[4],"the":[5,10,14,27,37,48,51,59,62,81,86,94,106,132,139],"road":[6,96],"occur":[7],"due":[8],"to":[9,25,42],"impossibility":[11],"of":[12,16,29,39,47,50,58,64,85,108,131],"predicting":[13,36],"behavior":[15,38,53],"pedestrians":[17,40,70,125],"from":[18],"vehicles":[19],"or":[20,76],"their":[21],"drivers.":[22],"In":[23,98],"order":[24],"reduce":[26],"number":[28],"these":[30],"accidents,":[31],"a":[32,101,127],"novel":[33],"method":[34,104,115,134],"for":[35,105],"needs":[41],"be":[43],"constructed.":[44],"Basic":[45],"elements":[46],"prediction":[49,103],"pedestrian":[52,65,109,120],"are":[54,71],"detecting":[55],"and":[56],"tracking":[57],"pedestrians.":[60],"However,":[61],"accuracy":[63],"detection":[66,89,110],"is":[67,91,111],"reduced":[68],"because":[69],"hidden":[72],"by":[73,77,137],"each":[74,119],"other":[75],"various":[78],"objects":[79],"on":[80],"road.":[82],"Therefore,":[83],"utilization":[84],"conventional":[87],"object":[88],"methods":[90],"limited":[92],"in":[93],"actual":[95,140],"space.":[97],"this":[99],"paper,":[100],"robust":[102],"errors":[107],"proposed.":[112],"proposed":[114,133],"does":[116],"not":[117],"track":[118],"individually,":[121],"but":[122],"tracks":[123],"multiple":[124],"as":[126],"crowd.":[128],"effectiveness":[130],"was":[135],"confirmed":[136],"utilizing":[138],"crowd":[141],"video.":[142]},"counts_by_year":[{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
