{"id":"https://openalex.org/W2991156746","doi":"https://doi.org/10.1109/itsc.2019.8917525","title":"GRAIL: A Gradients-of-Intensities-based Local Descriptor for Map-based Localization Using LiDAR Sensors","display_name":"GRAIL: A Gradients-of-Intensities-based Local Descriptor for Map-based Localization Using LiDAR Sensors","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2991156746","doi":"https://doi.org/10.1109/itsc.2019.8917525","mag":"2991156746"},"language":"en","primary_location":{"id":"doi:10.1109/itsc.2019.8917525","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2019.8917525","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","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/A5080777079","display_name":"Constanze Hungar","orcid":null},"institutions":[{"id":"https://openalex.org/I8659980","display_name":"Volkswagen Group (United States)","ror":"https://ror.org/034e5n787","country_code":"US","type":"company","lineage":["https://openalex.org/I1319473763","https://openalex.org/I8659980"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Constanze Hungar","raw_affiliation_strings":["Volkswagen AG, Group Innovation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Volkswagen AG, Group Innovation","institution_ids":["https://openalex.org/I8659980"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055958146","display_name":"Sara Brakemeier","orcid":null},"institutions":[{"id":"https://openalex.org/I114112103","display_name":"Leibniz University Hannover","ror":"https://ror.org/0304hq317","country_code":"DE","type":"education","lineage":["https://openalex.org/I114112103"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Sara Brakemeier","raw_affiliation_strings":["Institute of Photogrammetry and GeoInformation, Leibniz University Hannover"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Photogrammetry and GeoInformation, Leibniz University Hannover","institution_ids":["https://openalex.org/I114112103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083027973","display_name":"Stefan J\u00fcrgens","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stefan Jurgens","raw_affiliation_strings":["MAN Truck & Bus AG"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MAN Truck & Bus AG","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073402824","display_name":"Frank K\u00f6ster","orcid":"https://orcid.org/0000-0001-8684-3698"},"institutions":[{"id":"https://openalex.org/I129877168","display_name":"Carl von Ossietzky Universit\u00e4t Oldenburg","ror":"https://ror.org/033n9gh91","country_code":"DE","type":"education","lineage":["https://openalex.org/I129877168"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Frank Koster","raw_affiliation_strings":["Institute of Transportation Systems, DLR e. V., Carl von Ossietzky University of Oldenburg"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Transportation Systems, DLR e. V., Carl von Ossietzky University of Oldenburg","institution_ids":["https://openalex.org/I129877168"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":1.0,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9984999895095825,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9972000122070312,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.8031697273254395},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7301925420761108},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.7274607419967651},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6882384419441223},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6702401638031006},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6001254320144653},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5858297348022461},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.5358544588088989},{"id":"https://openalex.org/keywords/simultaneous-localization-and-mapping","display_name":"Simultaneous localization and mapping","score":0.5010449886322021},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.4919585883617401},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4790724217891693},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.4458405375480652},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4118986427783966},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.40135782957077026},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.19558373093605042},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.15827429294586182},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.15513333678245544}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8031697273254395},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7301925420761108},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.7274607419967651},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6882384419441223},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6702401638031006},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6001254320144653},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5858297348022461},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.5358544588088989},{"id":"https://openalex.org/C86369673","wikidata":"https://www.wikidata.org/wiki/Q1203659","display_name":"Simultaneous localization and mapping","level":4,"score":0.5010449886322021},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.4919585883617401},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4790724217891693},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.4458405375480652},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4118986427783966},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.40135782957077026},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.19558373093605042},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.15827429294586182},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.15513333678245544},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/itsc.2019.8917525","is_oa":false,"landing_page_url":"https://doi.org/10.1109/itsc.2019.8917525","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.6100000143051147}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1564871316","https://openalex.org/W1735588541","https://openalex.org/W1972485825","https://openalex.org/W1986522259","https://openalex.org/W2005089716","https://openalex.org/W2099346911","https://openalex.org/W2099606917","https://openalex.org/W2104853049","https://openalex.org/W2115579991","https://openalex.org/W2130558599","https://openalex.org/W2133098875","https://openalex.org/W2139114878","https://openalex.org/W2152864241","https://openalex.org/W2160643963","https://openalex.org/W2160821342","https://openalex.org/W2295130602","https://openalex.org/W2296228853","https://openalex.org/W2467214650","https://openalex.org/W2567552762","https://openalex.org/W2617419288","https://openalex.org/W2892028890","https://openalex.org/W2902610326","https://openalex.org/W2967222368","https://openalex.org/W3101921002","https://openalex.org/W6637923771","https://openalex.org/W6651554573","https://openalex.org/W6719881089","https://openalex.org/W6738814344","https://openalex.org/W6756736939"],"related_works":["https://openalex.org/W4319317934","https://openalex.org/W2901265155","https://openalex.org/W2956374172","https://openalex.org/W4293094720","https://openalex.org/W2739701376","https://openalex.org/W4212966960","https://openalex.org/W3196708299","https://openalex.org/W3126674423","https://openalex.org/W1750372561","https://openalex.org/W1501082329"],"abstract_inverted_index":{"Localization":[0],"with":[1,110],"respect":[2,111],"to":[3,57,67,112,118,123],"a":[4,44,83,113,136],"map":[5,114],"is":[6,80],"an":[7],"essential":[8],"objective":[9],"for":[10,107],"the":[11,74,97,104,125,145,158,165,178],"development":[12],"of":[13,22,50,60,94,96,167,174],"highly":[14],"automated":[15],"and":[16,115,144],"autonomous":[17],"vehicles":[18],"as":[19,21],"well":[20],"mobile":[23],"robots.":[24],"Commonly,":[25],"localization":[26,109,126],"solutions":[27],"rely":[28],"on":[29,135],"static,":[30],"semantic":[31,55,62],"objects,":[32],"like":[33],"road":[34],"signs":[35],"or":[36],"house":[37],"corners.":[38],"In":[39,65],"this":[40,154],"paper,":[41],"we":[42],"introduce":[43],"novel":[45,84],"local":[46,86,100],"descriptor":[47,69,91,106,169],"characterizing":[48],"neighborhoods":[49],"LiDAR":[51,75],"point":[52,98],"clouds":[53],"without":[54],"information":[56,78],"be":[58],"independent":[59],"those":[61],"infrastructure":[63],"elements.":[64],"contrast":[66],"other":[68,119],"methods,":[70],"our":[71,142],"system":[72],"uses":[73],"sensors'":[76],"intensity":[77],"which":[79],"encoded":[81],"into":[82],"gradients-of-intensities-based":[85],"descriptor,":[87],"called":[88],"GRAIL.":[89],"The":[90,128,150],"represents":[92],"shapes":[93],"intensities":[95],"clouds'":[99],"neighborhoods.":[101],"We":[102],"use":[103,177],"proposed":[105,159],"global":[108],"compare":[116],"it":[117],"well-known":[120],"geometry-based":[121],"descriptors":[122,176],"complete":[124],"framework.":[127],"introduced":[129],"method":[130,160],"has":[131],"been":[132],"thoroughly":[133],"evaluated":[134],"large":[137],"data":[138,148],"set":[139],"including":[140],"both,":[141],"own":[143],"KITTI":[146],"raw":[147],"benchmark.":[149],"experiments":[151],"presented":[152],"in":[153],"paper":[155],"show":[156],"that":[157],"can":[161],"achieve":[162],"accuracy":[163],"at":[164],"level":[166],"stateof-the-art":[168],"algorithms,":[170],"even":[171],"though":[172],"most":[173],"these":[175],"more":[179],"informative":[180],"geometry":[181],"information.":[182]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
