{"id":"https://openalex.org/W4417251981","doi":"https://doi.org/10.1109/lra.2025.3643266","title":"SGE-GLoc: Semantic Gaussian Ellipsoid Scene Graphs for Efficient LiDAR Global Localization","display_name":"SGE-GLoc: Semantic Gaussian Ellipsoid Scene Graphs for Efficient LiDAR Global Localization","publication_year":2025,"publication_date":"2025-12-11","ids":{"openalex":"https://openalex.org/W4417251981","doi":"https://doi.org/10.1109/lra.2025.3643266"},"language":null,"primary_location":{"id":"doi:10.1109/lra.2025.3643266","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2025.3643266","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-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":null,"display_name":"Ximeng Cai","orcid":null},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ximeng Cai","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China","School of Computer Science"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Computer Science","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100649665","display_name":"Ji Wu","orcid":"https://orcid.org/0000-0001-8140-2201"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ji Wu","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China","School of Computer Science"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Computer Science","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100856496","display_name":"Shu Han","orcid":"https://orcid.org/0009-0003-0933-4234"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shu Han","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China","School of Computer Science"],"raw_orcid":"https://orcid.org/0009-0003-0933-4234","affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Computer Science","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100736939","display_name":"Yu Li","orcid":"https://orcid.org/0009-0009-3734-9744"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Yu","raw_affiliation_strings":["School of Computer Science, Wuhan University, Wuhan, China","School of Computer Science"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Computer Science","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069540177","display_name":"Wen Yang","orcid":"https://orcid.org/0000-0002-3263-8768"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wen Yang","raw_affiliation_strings":["School of Electronic Information, Wuhan University, Wuhan, China","School of Electronic Information"],"raw_orcid":"https://orcid.org/0000-0002-3263-8768","affiliations":[{"raw_affiliation_string":"School of Electronic Information, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Electronic Information","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076179689","display_name":"Huai Yu","orcid":"https://orcid.org/0000-0001-6043-3412"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huai Yu","raw_affiliation_strings":["School of Electronic Information, Wuhan University, Wuhan, China","School of Electronic Information"],"raw_orcid":"https://orcid.org/0000-0001-6043-3412","affiliations":[{"raw_affiliation_string":"School of Electronic Information, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Electronic Information","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5073032922","display_name":"Gui-Song Xia","orcid":"https://orcid.org/0000-0001-7660-6090"},"institutions":[{"id":"https://openalex.org/I37461747","display_name":"Wuhan University","ror":"https://ror.org/033vjfk17","country_code":"CN","type":"education","lineage":["https://openalex.org/I37461747"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Gui-Song Xia","raw_affiliation_strings":["School of Artificial Intelligence, Wuhan University, Wuhan, China","School of Artificial Intelligence"],"raw_orcid":"https://orcid.org/0000-0001-7660-6090","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Wuhan University, Wuhan, China","institution_ids":["https://openalex.org/I37461747"]},{"raw_affiliation_string":"School of Artificial Intelligence","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I37461747"],"apc_list":null,"apc_paid":null,"fwci":3.3626,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.94340003,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":"11","issue":"2","first_page":"1498","last_page":"1505"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9732000231742859,"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":0.9732000231742859,"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":0.00839999970048666,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.0017000000225380063,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/minimum-bounding-box","display_name":"Minimum bounding box","score":0.5044999718666077},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5008999705314636},{"id":"https://openalex.org/keywords/semantic-mapping","display_name":"Semantic mapping","score":0.49410000443458557},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.4578999876976013},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.44339999556541443},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.4223000109195709},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.40619999170303345},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4009000062942505},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4004000127315521},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.39079999923706055}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7088000178337097},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6481999754905701},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5609999895095825},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.5044999718666077},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5008999705314636},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.49410000443458557},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.4578999876976013},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.44339999556541443},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.4223000109195709},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.40619999170303345},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4009000062942505},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4004000127315521},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.39079999923706055},{"id":"https://openalex.org/C32990609","wikidata":"https://www.wikidata.org/wiki/Q306542","display_name":"Transformation geometry","level":2,"score":0.38940000534057617},{"id":"https://openalex.org/C190470478","wikidata":"https://www.wikidata.org/wiki/Q2370229","display_name":"Invariant (physics)","level":2,"score":0.38089999556541443},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.3804999887943268},{"id":"https://openalex.org/C86369673","wikidata":"https://www.wikidata.org/wiki/Q1203659","display_name":"Simultaneous localization and mapping","level":4,"score":0.3741999864578247},{"id":"https://openalex.org/C57489055","wikidata":"https://www.wikidata.org/wiki/Q190046","display_name":"Ellipsoid","level":2,"score":0.3504999876022339},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3280999958515167},{"id":"https://openalex.org/C114744707","wikidata":"https://www.wikidata.org/wiki/Q218533","display_name":"RANSAC","level":3,"score":0.3228999972343445},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3019999861717224},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.30160000920295715},{"id":"https://openalex.org/C56435381","wikidata":"https://www.wikidata.org/wiki/Q1196371","display_name":"Geometric transformation","level":3,"score":0.2969000041484833},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.2930999994277954},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.29120001196861267},{"id":"https://openalex.org/C5799516","wikidata":"https://www.wikidata.org/wiki/Q4110915","display_name":"Visual odometry","level":3,"score":0.28870001435279846},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.28760001063346863},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.27489998936653137},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2720000147819519},{"id":"https://openalex.org/C2779188883","wikidata":"https://www.wikidata.org/wiki/Q82446","display_name":"Global Map","level":3,"score":0.2581999897956848},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.25769999623298645},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.2531999945640564},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.25189998745918274}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/lra.2025.3643266","is_oa":false,"landing_page_url":"https://doi.org/10.1109/lra.2025.3643266","pdf_url":null,"source":{"id":"https://openalex.org/S4210169774","display_name":"IEEE Robotics and Automation Letters","issn_l":"2377-3766","issn":["2377-3766"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Robotics and Automation Letters","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4100670194","display_name":null,"funder_award_id":"62301370","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W1968315983","https://openalex.org/W2150066425","https://openalex.org/W2153504150","https://openalex.org/W2296228853","https://openalex.org/W2910489334","https://openalex.org/W2955544543","https://openalex.org/W2981566147","https://openalex.org/W3111598592","https://openalex.org/W3132982513","https://openalex.org/W3159849251","https://openalex.org/W3168086592","https://openalex.org/W3171433839","https://openalex.org/W3177271542","https://openalex.org/W3201256746","https://openalex.org/W3203597819","https://openalex.org/W4312275786","https://openalex.org/W4312419284","https://openalex.org/W4385245566","https://openalex.org/W4385975620","https://openalex.org/W4391216062","https://openalex.org/W4392515775","https://openalex.org/W4393864935","https://openalex.org/W4396629506","https://openalex.org/W4408780413","https://openalex.org/W4411948482"],"related_works":[],"abstract_inverted_index":{"Global":[0],"localization,":[1],"encompassing":[2],"robust":[3],"place":[4,93,166],"recognition":[5,167],"and":[6,36,88,101,111,138,159,169],"precise":[7],"transformation":[8,127,142],"estimation,":[9,128],"is":[10,23],"crucial":[11],"for":[12,30,120],"mobile":[13],"robot":[14],"navigation":[15,19],"when":[16],"the":[17,141,192],"global":[18,65,112],"satellite":[20],"system":[21,199],"(GNSS)":[22],"unavailable.":[24],"While":[25],"LiDAR-based":[26,64],"approaches":[27],"are":[28,78],"favored":[29],"their":[31],"accuracy":[32,168],"in":[33,55,204],"3D":[34],"perception":[35],"resilience":[37],"to":[38,108],"illumination":[39],"changes,":[40],"existing":[41],"methods":[42],"often":[43],"suffer":[44],"from":[45],"complex":[46],"scene":[47,72,121,178],"representations":[48],"or":[49],"computationally":[50],"intensive":[51],"processes,":[52],"hindering":[53],"scalability":[54],"large-scale":[56],"applications.":[57],"This":[58],"paper":[59],"introduces":[60],"SGE-GLoc,":[61],"a":[62,70,103,116,175,197],"novel":[63],"localization":[66,171],"framework,":[67],"which":[68],"utilizes":[69],"compact":[71,177],"graph":[73,179],"representation":[74,180],"where":[75],"individual":[76],"objects":[77],"modeled":[79],"as":[80],"Semantic":[81],"Gaussian":[82],"Ellipsoids":[83],"(SGEs),":[84],"encapsulating":[85],"both":[86],"geometric":[87,145],"semantic":[89],"attributes.":[90],"For":[91,124],"efficient":[92],"recognition,":[94],"we":[95,129],"encode":[96],"SGE":[97,136],"features":[98],"into":[99,196],"histograms":[100],"employ":[102],"Graph":[104],"Neural":[105],"Network":[106],"(GNN)":[107],"learn":[109],"local":[110],"topological":[113],"information,":[114],"generating":[115],"discriminative":[117],"two-stage":[118],"descriptor":[119],"similarity":[122],"scoring.":[123],"accurate":[125],"6-DoF":[126],"first":[130],"establish":[131],"initial":[132],"correspondences":[133],"based":[134],"on":[135,151],"matching":[137],"subsequently":[139],"refine":[140],"by":[143],"exploiting":[144],"constraints":[146],"between":[147],"SGEs.":[148],"Extensive":[149],"evaluations":[150],"four":[152],"public":[153],"datasets,":[154],"including":[155],"KITTI,":[156],"KITTI-360,":[157],"Apollo,":[158],"HeLiPR,":[160],"demonstrate":[161],"that":[162],"SGE-GLoc":[163,195],"achieves":[164],"high":[165],"low":[170],"error,":[172],"while":[173],"maintaining":[174],"highly":[176],"with":[181],"an":[182],"average":[183],"storage":[184],"of":[185,194],"only":[186],"1.28":[187],"KB":[188],"per":[189],"scene.":[190],"Furthermore,":[191],"integration":[193],"SLAM":[198],"showcases":[200],"its":[201],"practical":[202],"efficacy":[203],"real-world":[205],"scenarios.":[206]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2025-12-19T19:40:27.379048","created_date":"2025-12-11T00:00:00"}