{"id":"https://openalex.org/W4313417869","doi":"https://doi.org/10.1109/icves56941.2022.9986939","title":"Road Markings Segmentation from LIDAR Point Clouds using Reflectivity Information","display_name":"Road Markings Segmentation from LIDAR Point Clouds using Reflectivity Information","publication_year":2022,"publication_date":"2022-11-14","ids":{"openalex":"https://openalex.org/W4313417869","doi":"https://doi.org/10.1109/icves56941.2022.9986939"},"language":"en","primary_location":{"id":"doi:10.1109/icves56941.2022.9986939","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icves56941.2022.9986939","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","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/A5080110001","display_name":"Novel Certad","orcid":"https://orcid.org/0000-0002-0681-7658"},"institutions":[{"id":"https://openalex.org/I121883995","display_name":"Johannes Kepler University of Linz","ror":"https://ror.org/052r2xn60","country_code":"AT","type":"education","lineage":["https://openalex.org/I121883995"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Novel Certad","raw_affiliation_strings":["Johannes Kepler University Linz,Chair Sustainable Transport Logistics 4.0,Linz,Austria,4040"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Johannes Kepler University Linz,Chair Sustainable Transport Logistics 4.0,Linz,Austria,4040","institution_ids":["https://openalex.org/I121883995"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050144872","display_name":"Walter Morales-Alvarez","orcid":"https://orcid.org/0000-0001-6912-4130"},"institutions":[{"id":"https://openalex.org/I121883995","display_name":"Johannes Kepler University of Linz","ror":"https://ror.org/052r2xn60","country_code":"AT","type":"education","lineage":["https://openalex.org/I121883995"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Walter Morales-Alvarez","raw_affiliation_strings":["Johannes Kepler University Linz,Chair Sustainable Transport Logistics 4.0,Linz,Austria,4040"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Johannes Kepler University Linz,Chair Sustainable Transport Logistics 4.0,Linz,Austria,4040","institution_ids":["https://openalex.org/I121883995"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009941460","display_name":"Cristina Olaverri-Monreal","orcid":"https://orcid.org/0000-0002-5211-3598"},"institutions":[{"id":"https://openalex.org/I121883995","display_name":"Johannes Kepler University of Linz","ror":"https://ror.org/052r2xn60","country_code":"AT","type":"education","lineage":["https://openalex.org/I121883995"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Cristina Olaverri-Monreal","raw_affiliation_strings":["Johannes Kepler University Linz,Chair Sustainable Transport Logistics 4.0,Linz,Austria,4040"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Johannes Kepler University Linz,Chair Sustainable Transport Logistics 4.0,Linz,Austria,4040","institution_ids":["https://openalex.org/I121883995"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I121883995"],"apc_list":null,"apc_paid":null,"fwci":2.8423,"has_fulltext":false,"cited_by_count":8,"citation_normalized_percentile":{"value":0.91995245,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":98},"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9990000128746033,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/lidar","display_name":"Lidar","score":0.8331862688064575},{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.6915178894996643},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6881183385848999},{"id":"https://openalex.org/keywords/thresholding","display_name":"Thresholding","score":0.6505869626998901},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6188355088233948},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6079341173171997},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5719900131225586},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.5486748814582825},{"id":"https://openalex.org/keywords/reflectivity","display_name":"Reflectivity","score":0.5334012508392334},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.502737283706665},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.45459842681884766},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.44300827383995056},{"id":"https://openalex.org/keywords/region-growing","display_name":"Region growing","score":0.4277578294277191},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.2368321716785431},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.19091513752937317},{"id":"https://openalex.org/keywords/scale-space-segmentation","display_name":"Scale-space segmentation","score":0.10884252190589905},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.09234899282455444}],"concepts":[{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.8331862688064575},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6915178894996643},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6881183385848999},{"id":"https://openalex.org/C191178318","wikidata":"https://www.wikidata.org/wiki/Q2256906","display_name":"Thresholding","level":3,"score":0.6505869626998901},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6188355088233948},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6079341173171997},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5719900131225586},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.5486748814582825},{"id":"https://openalex.org/C108597893","wikidata":"https://www.wikidata.org/wiki/Q663650","display_name":"Reflectivity","level":2,"score":0.5334012508392334},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.502737283706665},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.45459842681884766},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.44300827383995056},{"id":"https://openalex.org/C206824153","wikidata":"https://www.wikidata.org/wiki/Q1169834","display_name":"Region growing","level":5,"score":0.4277578294277191},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.2368321716785431},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.19091513752937317},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.10884252190589905},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.09234899282455444},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icves56941.2022.9986939","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icves56941.2022.9986939","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6299999952316284,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G5335978623","display_name":null,"funder_award_id":"P 34485-N","funder_id":"https://openalex.org/F4320321181","funder_display_name":"Austrian Science Fund"}],"funders":[{"id":"https://openalex.org/F4320321181","display_name":"Austrian Science Fund","ror":"https://ror.org/013tf3c58"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W2004573458","https://openalex.org/W2009345891","https://openalex.org/W2075018253","https://openalex.org/W2113556050","https://openalex.org/W2116484457","https://openalex.org/W2133059825","https://openalex.org/W2152864241","https://openalex.org/W2154855001","https://openalex.org/W2771177825","https://openalex.org/W2896793136","https://openalex.org/W2898227465","https://openalex.org/W2903637353","https://openalex.org/W2904663683","https://openalex.org/W2970736851","https://openalex.org/W3093972168","https://openalex.org/W3127342902","https://openalex.org/W3174113711","https://openalex.org/W3205435265","https://openalex.org/W3205933741","https://openalex.org/W4249261707","https://openalex.org/W4319717712"],"related_works":["https://openalex.org/W2953058328","https://openalex.org/W1542224353","https://openalex.org/W2353864504","https://openalex.org/W2350588503","https://openalex.org/W2356573839","https://openalex.org/W2350531285","https://openalex.org/W2551390060","https://openalex.org/W2770357358","https://openalex.org/W2106833984","https://openalex.org/W2786233476"],"abstract_inverted_index":{"Lane":[0],"detection":[1],"algorithms":[2],"are":[3],"crucial":[4],"for":[5],"the":[6,48,70,92,112,130,133,142],"development":[7],"of":[8,51,132,138],"autonomous":[9],"vehicles":[10],"technologies.":[11],"The":[12,95],"more":[13],"extended":[14],"approach":[15],"is":[16],"to":[17,43,68,89,129],"use":[18,131],"cameras":[19,33],"as":[20],"sensors.":[21],"However,":[22],"LIDAR":[23,54,143],"sensors":[24],"can":[25,34],"cope":[26],"with":[27,62],"weather":[28],"and":[29,83,105,116],"light":[30],"conditions":[31],"that":[32],"not.":[35],"In":[36],"this":[37],"paper,":[38],"we":[39,74,85],"introduce":[40],"a":[41,52,57,100,106,120],"method":[42,60,82],"extract":[44,69],"road":[45,71],"markings":[46],"from":[47],"reflectivity":[49,125],"data":[50,126,136],"64-layers":[53],"sensor.":[55,144],"First,":[56],"plane":[58],"segmentation":[59],"along":[61],"region":[63],"grow":[64],"clustering":[65],"was":[66,97,114,119],"used":[67],"plane.":[72],"Then":[73],"applied":[75],"an":[76],"adaptive":[77],"thresholding":[78],"based":[79],"on":[80,99],"Otsu's":[81],"finally,":[84],"fitted":[86],"line":[87],"models":[88],"filter":[90],"out":[91],"remaining":[93],"outliers.":[94],"algorithm":[96,113],"tested":[98],"test":[101],"track":[102],"at":[103,108],"60km/h":[104],"highway":[107],"100km/h.":[109],"Results":[110],"showed":[111],"reliable":[115],"precise.":[117],"There":[118],"clear":[121],"improvement":[122],"when":[123],"using":[124],"in":[127],"comparison":[128],"raw":[134],"intensity":[135],"both":[137],"them":[139],"provided":[140],"by":[141]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}