{"id":"https://openalex.org/W7131903795","doi":"https://doi.org/10.1109/sii64115.2026.11404445","title":"3D Object Segmentation Considering Density Variation and Scanning Order of Point Clouds","display_name":"3D Object Segmentation Considering Density Variation and Scanning Order of Point Clouds","publication_year":2026,"publication_date":"2026-01-11","ids":{"openalex":"https://openalex.org/W7131903795","doi":"https://doi.org/10.1109/sii64115.2026.11404445"},"language":null,"primary_location":{"id":"doi:10.1109/sii64115.2026.11404445","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sii64115.2026.11404445","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/SICE International Symposium on System Integration (SII)","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/A5100999796","display_name":"Takuma Tanaka","orcid":null},"institutions":[{"id":"https://openalex.org/I16656306","display_name":"Meiji University","ror":"https://ror.org/02rqvrp93","country_code":"JP","type":"education","lineage":["https://openalex.org/I16656306"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Takuma Tanaka","raw_affiliation_strings":["Meiji University,Graduate School of Science and Technology,Kanagawa,Japan"],"affiliations":[{"raw_affiliation_string":"Meiji University,Graduate School of Science and Technology,Kanagawa,Japan","institution_ids":["https://openalex.org/I16656306"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057146219","display_name":"Yoshitaka Hara","orcid":"https://orcid.org/0000-0002-8667-1061"},"institutions":[{"id":"https://openalex.org/I8488066","display_name":"Chiba Institute of Technology","ror":"https://ror.org/00qwnam72","country_code":"JP","type":"education","lineage":["https://openalex.org/I8488066"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoshitaka Hara","raw_affiliation_strings":["Chiba Institute of Technology,Future Robotics Technology Center(fuRo),Chiba,Japan"],"affiliations":[{"raw_affiliation_string":"Chiba Institute of Technology,Future Robotics Technology Center(fuRo),Chiba,Japan","institution_ids":["https://openalex.org/I8488066"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5127360095","display_name":"Yoji Kuroda","orcid":null},"institutions":[{"id":"https://openalex.org/I16656306","display_name":"Meiji University","ror":"https://ror.org/02rqvrp93","country_code":"JP","type":"education","lineage":["https://openalex.org/I16656306"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoji Kuroda","raw_affiliation_strings":["Meiji University,School of Science and Technology,Kanagawa,Japan"],"affiliations":[{"raw_affiliation_string":"Meiji University,School of Science and Technology,Kanagawa,Japan","institution_ids":["https://openalex.org/I16656306"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100999796"],"corresponding_institution_ids":["https://openalex.org/I16656306"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.55528075,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1386","last_page":"1391"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.17880000174045563,"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"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.17880000174045563,"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"}},{"id":"https://openalex.org/T10052","display_name":"Medical Image Segmentation Techniques","score":0.16220000386238098,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.08139999955892563,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.8999999761581421},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.8259000182151794},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6197999715805054},{"id":"https://openalex.org/keywords/laser-scanning","display_name":"Laser scanning","score":0.5885000228881836},{"id":"https://openalex.org/keywords/ranging","display_name":"Ranging","score":0.445499986410141},{"id":"https://openalex.org/keywords/dbscan","display_name":"DBSCAN","score":0.4287000000476837},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.4074000120162964}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8999999761581421},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.8259000182151794},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6197999715805054},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6168000102043152},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6150000095367432},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6136000156402588},{"id":"https://openalex.org/C141349535","wikidata":"https://www.wikidata.org/wiki/Q1361664","display_name":"Laser scanning","level":3,"score":0.5885000228881836},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.445499986410141},{"id":"https://openalex.org/C46576248","wikidata":"https://www.wikidata.org/wiki/Q1114630","display_name":"DBSCAN","level":5,"score":0.4287000000476837},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.4074000120162964},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.3878999948501587},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.3855000138282776},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.36480000615119934},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.35429999232292175},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.3483999967575073},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3458999991416931},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.32519999146461487},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.27250000834465027},{"id":"https://openalex.org/C138827492","wikidata":"https://www.wikidata.org/wiki/Q6661985","display_name":"Data processing","level":2,"score":0.2531999945640564},{"id":"https://openalex.org/C65885262","wikidata":"https://www.wikidata.org/wiki/Q7429708","display_name":"Scale-space segmentation","level":4,"score":0.2526000142097473}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sii64115.2026.11404445","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sii64115.2026.11404445","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2026 IEEE/SICE International Symposium on System Integration (SII)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Climate action","id":"https://metadata.un.org/sdg/13","score":0.4777791202068329}],"awards":[],"funders":[{"id":"https://openalex.org/F4320315052","display_name":"Meiji University","ror":"https://ror.org/02rqvrp93"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":7,"referenced_works":["https://openalex.org/W2152864241","https://openalex.org/W2908286182","https://openalex.org/W2968296999","https://openalex.org/W3167095230","https://openalex.org/W4284892716","https://openalex.org/W4312501532","https://openalex.org/W4402667891"],"related_works":[],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"a":[5,32,116,182],"novel":[6],"DBSCAN":[7,62],"method":[8,154,168,194],"for":[9,84],"3D":[10],"object":[11,199],"segmentation":[12,200],"that":[13,65,80,156,170],"considers":[14],"point":[15,45,77,149,207],"cloud":[16,150,208],"density":[17,74,108,209],"based":[18,146],"on":[19,147],"lidar":[20,33,50,104,212],"range":[21],"and":[22,39,70,79,124,159,197,214],"scanning":[23,55,119,184,217],"order":[24,56],"of":[25,57,76,138,186],"laser":[26],"beams.":[27,188],"Point":[28],"clouds":[29,46],"obtained":[30,47],"by":[31,48,176,201],"are":[34,51,68,87,100],"dense":[35],"at":[36,41],"short":[37],"ranges":[38,105,213],"sparse":[40],"long":[42],"ranges.":[43],"Furthermore,":[44,110],"the":[49,54,81,96,136,139,148,152,187,192,204,215],"organized":[52],"in":[53,90,95,131,206],"each":[58],"beam.":[59],"However,":[60],"conventional":[61],"has":[63],"issues":[64],"its":[66],"parameters":[67,99,145],"fixed":[69],"cannot":[71],"adapt":[72],"to":[73,103,106,134,211],"variation":[75],"clouds,":[78],"computational":[82,122],"costs":[83,123],"neighborhood":[85,112,178],"search":[86,113,179],"high,":[88],"resulting":[89],"significant":[91],"processing":[92,126,171],"time.":[93,127],"Therefore,":[94],"proposed":[97,140,153,193],"method,":[98],"adjusted":[101],"according":[102],"accommodate":[107],"differences.":[109],"executing":[111,177],"within":[114,180],"only":[115,181],"specific":[117,183],"beam":[118,216],"area":[120,185],"reduces":[121],"shortens":[125],"We":[128],"conducted":[129],"experiments":[130],"multiple":[132],"environments":[133],"verify":[135],"effectiveness":[137],"method.":[141],"By":[142],"automatically":[143],"determining":[144],"density,":[151],"demonstrated":[155,169],"both":[157,203],"nearby":[158],"distant":[160],"objects":[161],"can":[162,173],"be":[163,174],"correctly":[164],"segmented.":[165],"Additionally,":[166],"our":[167],"time":[172],"reduced":[175],"As":[189],"described":[190],"above,":[191],"achieves":[195],"adaptive":[196],"high-speed":[198],"considering":[202],"differences":[205],"due":[210],"order.":[218]},"counts_by_year":[],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2026-02-28T00:00:00"}
