{"id":"https://openalex.org/W4413917887","doi":"https://doi.org/10.1109/icra55743.2025.11128417","title":"RE-TRIP: Reflectivity Instance Augmented Triangle Descriptor for 3D Place Recognition","display_name":"RE-TRIP: Reflectivity Instance Augmented Triangle Descriptor for 3D Place Recognition","publication_year":2025,"publication_date":"2025-05-19","ids":{"openalex":"https://openalex.org/W4413917887","doi":"https://doi.org/10.1109/icra55743.2025.11128417"},"language":"en","primary_location":{"id":"doi:10.1109/icra55743.2025.11128417","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra55743.2025.11128417","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Robotics and Automation (ICRA)","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/A5063861251","display_name":"Yechan Park","orcid":"https://orcid.org/0000-0002-6030-4108"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Yechan Park","raw_affiliation_strings":["Yonsei University,Department of Vehicle Convergence Engineering,Seoul,South Korea,03722"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yonsei University,Department of Vehicle Convergence Engineering,Seoul,South Korea,03722","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054766842","display_name":"Gyuhyeon Pak","orcid":"https://orcid.org/0009-0007-7589-4730"},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Gyuhyeon Pak","raw_affiliation_strings":["Yonsei University,Department of Electrical and Electronic Engineering,Seoul,South Korea,03722"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yonsei University,Department of Electrical and Electronic Engineering,Seoul,South Korea,03722","institution_ids":["https://openalex.org/I193775966"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113683771","display_name":"Euntai Kim","orcid":null},"institutions":[{"id":"https://openalex.org/I193775966","display_name":"Yonsei University","ror":"https://ror.org/01wjejq96","country_code":"KR","type":"education","lineage":["https://openalex.org/I193775966"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Euntai Kim","raw_affiliation_strings":["Yonsei University,Department of Electrical and Electronic Engineering,Seoul,South Korea,03722"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yonsei University,Department of Electrical and Electronic Engineering,Seoul,South Korea,03722","institution_ids":["https://openalex.org/I193775966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I193775966"],"apc_list":null,"apc_paid":null,"fwci":3.6972,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.93563949,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"2226","last_page":"2232"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9997000098228455,"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":0.9997000098228455,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9973999857902527,"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"}},{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9948999881744385,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/reflectivity","display_name":"Reflectivity","score":0.7362500429153442},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.651046633720398},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5537581443786621},{"id":"https://openalex.org/keywords/augmented-reality","display_name":"Augmented reality","score":0.5450369119644165},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5179508924484253},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.39624178409576416},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics (images)","score":0.38151636719703674},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.1037224531173706},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06980764865875244}],"concepts":[{"id":"https://openalex.org/C108597893","wikidata":"https://www.wikidata.org/wiki/Q663650","display_name":"Reflectivity","level":2,"score":0.7362500429153442},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.651046633720398},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5537581443786621},{"id":"https://openalex.org/C153715457","wikidata":"https://www.wikidata.org/wiki/Q254183","display_name":"Augmented reality","level":2,"score":0.5450369119644165},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5179508924484253},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.39624178409576416},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.38151636719703674},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.1037224531173706},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06980764865875244}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra55743.2025.11128417","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra55743.2025.11128417","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Robotics and Automation (ICRA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G8442633346","display_name":null,"funder_award_id":"20023455","funder_id":"https://openalex.org/F4320321681","funder_display_name":"Ministry of Trade, Industry and Energy"}],"funders":[{"id":"https://openalex.org/F4320321681","display_name":"Ministry of Trade, Industry and Energy","ror":"https://ror.org/008nkqk13"},{"id":"https://openalex.org/F4320334879","display_name":"Korea Evaluation Institute of Industrial Technology","ror":"https://ror.org/03z9cwa38"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":36,"referenced_works":["https://openalex.org/W1482825550","https://openalex.org/W1491719799","https://openalex.org/W1612997784","https://openalex.org/W1972485825","https://openalex.org/W1989484209","https://openalex.org/W2029449100","https://openalex.org/W2033574012","https://openalex.org/W2108333036","https://openalex.org/W2117228865","https://openalex.org/W2119605622","https://openalex.org/W2151103935","https://openalex.org/W2152864241","https://openalex.org/W2284029970","https://openalex.org/W2565998037","https://openalex.org/W2910489334","https://openalex.org/W2914921243","https://openalex.org/W3002242011","https://openalex.org/W3011465262","https://openalex.org/W3091337047","https://openalex.org/W3127368595","https://openalex.org/W3129245057","https://openalex.org/W3138171450","https://openalex.org/W3206411252","https://openalex.org/W3211389689","https://openalex.org/W4312492713","https://openalex.org/W4319663799","https://openalex.org/W4383066341","https://openalex.org/W4383108920","https://openalex.org/W4390778110","https://openalex.org/W4393864935","https://openalex.org/W4394820411","https://openalex.org/W4396604988","https://openalex.org/W4401414466","https://openalex.org/W4401415409","https://openalex.org/W4401415917","https://openalex.org/W4401416545"],"related_works":["https://openalex.org/W2172197285","https://openalex.org/W2991048842","https://openalex.org/W2750280393","https://openalex.org/W2355696739","https://openalex.org/W3158001554","https://openalex.org/W2771909920","https://openalex.org/W2957704286","https://openalex.org/W2028936041","https://openalex.org/W2179141964","https://openalex.org/W4382054174"],"abstract_inverted_index":{"While":[0],"most":[1,44],"people":[2],"associate":[3],"LiDAR":[4,22,34,61],"primarily":[5],"with":[6],"its":[7],"ability":[8],"to":[9,37,89,144,151],"measure":[10],"distances":[11],"and":[12,87,102,130,166,189],"provide":[13],"geometric":[14,53,85,97,100],"information":[15,59],"about":[16],"the":[17,56,103,146,174],"environment":[18],"(via":[19],"point":[20],"clouds),":[21],"also":[23],"captures":[24],"additional":[25,57],"data,":[26],"including":[27],"reflectivity":[28,58,88,132],"or":[29],"intensity":[30],"values.":[31],"Unfortunately,":[32],"when":[33],"is":[35,193],"applied":[36],"Place":[38],"Recognition":[39],"(PR)":[40],"in":[41,92,111,181],"mobile":[42],"robotics,":[43],"previous":[45],"works":[46],"on":[47,52],"LiDAR-based":[48],"PR":[49],"rely":[50],"only":[51],"measurements,":[54],"neglecting":[55],"that":[60,173],"provides.":[62],"In":[63],"this":[64],"paper,":[65],"we":[66,114,138],"propose":[67,116],"a":[68,140],"novel":[69],"descriptor":[70,82],"for":[71],"3D":[72],"PR,":[73],"named":[74],"RE-TRIP":[75,110,127],"(REflectivity-instance":[76],"augmented":[77],"TRIangle":[78],"descriPtor).":[79],"This":[80],"new":[81],"leverages":[83],"both":[84],"measurements":[86],"enhance":[90],"robustness":[91],"challenging":[93],"scenarios":[94],"such":[95],"as":[96],"degeneracy,":[98],"high":[99],"similarity,":[101],"presence":[104],"of":[105,142,148,183],"dynamic":[106,168],"objects.":[107],"To":[108],"implement":[109],"real-world":[112],"applications,":[113],"further":[115],"(1)":[117],"keypoint":[118],"extraction":[119],"method,":[120,125,129],"(2)":[121],"key":[122],"instance":[123],"segmentation":[124],"(3)":[126],"matching":[128],"(4)":[131],"combined":[133],"loop":[134],"verification":[135],"method.":[136],"Finally,":[137],"conduct":[139],"series":[141],"experiments":[143],"demonstrate":[145],"effectiveness":[147],"RE-TRIP.":[149],"Applied":[150],"public":[152],"datasets":[153],"(i.e.,":[154],"HELIPR,":[155],"FusionPortable)":[156],"containing":[157],"diverse":[158],"scenarios-including":[159],"long":[160],"corridors,":[161],"bridges,":[162],"large-scale":[163],"urban":[164],"areas,":[165],"highly":[167],"environments-our":[169],"experimental":[170],"results":[171],"show":[172],"proposed":[175],"method":[176],"outperforms":[177],"existing":[178],"state-of-the-art":[179],"methods":[180],"terms":[182],"Scan":[184,187],"Context,":[185],"Intensity":[186],"Context":[188],"STD.":[190],"Our":[191],"code":[192],"available":[194],"at:":[195],"https://github.com/pycS714IRE-TRIP.":[196]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
