{"id":"https://openalex.org/W4402474860","doi":"https://doi.org/10.1109/ccece59415.2024.10667223","title":"A Comparison of Point Cloud Segmentation Models for Road Unevenness Detection and Smooth Autonomous Driving","display_name":"A Comparison of Point Cloud Segmentation Models for Road Unevenness Detection and Smooth Autonomous Driving","publication_year":2024,"publication_date":"2024-08-06","ids":{"openalex":"https://openalex.org/W4402474860","doi":"https://doi.org/10.1109/ccece59415.2024.10667223"},"language":"en","primary_location":{"id":"doi:10.1109/ccece59415.2024.10667223","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccece59415.2024.10667223","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)","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/A5018181018","display_name":"Matthew Sharpe","orcid":"https://orcid.org/0000-0002-8165-5775"},"institutions":[{"id":"https://openalex.org/I204722609","display_name":"Queen's University","ror":"https://ror.org/02y72wh86","country_code":"CA","type":"education","lineage":["https://openalex.org/I204722609"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Matthew Sharpe","raw_affiliation_strings":["Queen&#x2019;s University,School of Computing,Kingston,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Queen&#x2019;s University,School of Computing,Kingston,Canada","institution_ids":["https://openalex.org/I204722609"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107157362","display_name":"Logan Fleck","orcid":null},"institutions":[{"id":"https://openalex.org/I204722609","display_name":"Queen's University","ror":"https://ror.org/02y72wh86","country_code":"CA","type":"education","lineage":["https://openalex.org/I204722609"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Logan Fleck","raw_affiliation_strings":["Queen&#x2019;s University,School of Computing,Kingston,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Queen&#x2019;s University,School of Computing,Kingston,Canada","institution_ids":["https://openalex.org/I204722609"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107157363","display_name":"Andrew Mun-Shimoda","orcid":null},"institutions":[{"id":"https://openalex.org/I204722609","display_name":"Queen's University","ror":"https://ror.org/02y72wh86","country_code":"CA","type":"education","lineage":["https://openalex.org/I204722609"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Andrew Mun-Shimoda","raw_affiliation_strings":["Queen&#x2019;s University,School of Computing,Kingston,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Queen&#x2019;s University,School of Computing,Kingston,Canada","institution_ids":["https://openalex.org/I204722609"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022582952","display_name":"Naveed Ejaz","orcid":"https://orcid.org/0000-0003-1295-4787"},"institutions":[{"id":"https://openalex.org/I204722609","display_name":"Queen's University","ror":"https://ror.org/02y72wh86","country_code":"CA","type":"education","lineage":["https://openalex.org/I204722609"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Naveed Ejaz","raw_affiliation_strings":["Queen&#x2019;s University,School of Computing,Kingston,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Queen&#x2019;s University,School of Computing,Kingston,Canada","institution_ids":["https://openalex.org/I204722609"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032858073","display_name":"Salimur Choudhury","orcid":"https://orcid.org/0000-0002-3187-112X"},"institutions":[{"id":"https://openalex.org/I204722609","display_name":"Queen's University","ror":"https://ror.org/02y72wh86","country_code":"CA","type":"education","lineage":["https://openalex.org/I204722609"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Salimur Choudhury","raw_affiliation_strings":["Queen&#x2019;s University,School of Computing,Kingston,Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Queen&#x2019;s University,School of Computing,Kingston,Canada","institution_ids":["https://openalex.org/I204722609"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I204722609"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"565","last_page":"569"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9977999925613403,"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":0.9977999925613403,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9966999888420105,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9934999942779541,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/point-cloud","display_name":"Point cloud","score":0.7645401954650879},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6978820562362671},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6203328371047974},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6143531203269958},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5375487804412842},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5124924182891846},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.49036455154418945},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4373672306537628},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13493233919143677},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.10097432136535645}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.7645401954650879},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6978820562362671},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6203328371047974},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6143531203269958},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5375487804412842},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5124924182891846},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.49036455154418945},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4373672306537628},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13493233919143677},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.10097432136535645},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ccece59415.2024.10667223","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ccece59415.2024.10667223","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Canadian Conference on Electrical and Computer Engineering (CCECE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/13","display_name":"Climate action","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":12,"referenced_works":["https://openalex.org/W4236965008","https://openalex.org/W4238505098","https://openalex.org/W4281732104","https://openalex.org/W4284994123","https://openalex.org/W4307347603","https://openalex.org/W4321014138","https://openalex.org/W4361802179","https://openalex.org/W4365420262","https://openalex.org/W4384928384","https://openalex.org/W4389076543","https://openalex.org/W6763422710","https://openalex.org/W6839446344"],"related_works":["https://openalex.org/W4244478748","https://openalex.org/W4223488648","https://openalex.org/W2134969820","https://openalex.org/W2251605416","https://openalex.org/W2560439919","https://openalex.org/W4389340727","https://openalex.org/W3150465815","https://openalex.org/W4399442168","https://openalex.org/W2114282491","https://openalex.org/W1522196789"],"abstract_inverted_index":{"Detecting":[0],"uneven":[1],"and":[2,15,32,52,67,72,81,89,116],"imperfect":[3],"road":[4,41,100,150],"segments":[5],"is":[6],"crucial":[7],"for":[8,99,134,148,155],"self-driving":[9],"vehicles":[10],"to":[11,23,40],"ensure":[12],"a":[13,109,117],"safe":[14],"comfortable":[16],"autonomous":[17,160],"driving":[18,161],"experience.":[19],"This":[20],"paper":[21],"aims":[22],"explore":[24],"the":[25,125,144],"PointNet":[26,66,88,129],"architecture":[27],"across":[28,128],"its":[29,61],"many":[30],"evolutions":[31],"examine":[33],"how":[34,57],"each":[35,58,74],"generation":[36],"performs":[37],"when":[38,132],"applied":[39],"irregularity":[42],"point":[43,136],"cloud":[44,137],"segmentation.":[45],"The":[46],"architectural":[47],"differences":[48],"between":[49],"PointNet,":[50],"PointNet++,":[51],"PointNeXt":[53,68,90,106,147],"are":[54,69,91],"explored,":[55],"highlighting":[56],"improves":[59],"upon":[60],"predecessor.":[62],"Customized":[63],"versions":[64],"of":[65,79,87,146],"then":[70,92],"developed":[71],"discussed,":[73],"obtaining":[75],"overall":[76],"training":[77],"accuracies":[78],"91%":[80],"99.1%,":[82],"respectively.":[83],"These":[84],"tailored":[85],"implementations":[86],"compared":[93],"with":[94,103],"an":[95],"existing":[96],"PointNet++":[97],"model":[98,107,114],"unevenness":[101,151],"segmentation,":[102],"our":[104],"custom":[105],"demonstrating":[108],"dramatic":[110],"76%":[111],"decrease":[112],"in":[113,120],"size":[115],"0.7%":[118],"jump":[119],"accuracy.":[121],"Our":[122],"findings":[123],"highlight":[124],"significant":[126],"improvements":[127],"generations,":[130],"especially":[131],"used":[133],"LiDAR":[135],"segmentation":[138],"tasks.":[139],"Moreover,":[140],"this":[141],"study":[142],"demonstrates":[143],"superiority":[145],"real-time":[149],"detection,":[152],"opening":[153],"avenues":[154],"further":[156],"research":[157],"into":[158],"better":[159],"solutions.":[162]},"counts_by_year":[{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
