{"id":"https://openalex.org/W3014648643","doi":"https://doi.org/10.1155/2020/4925821","title":"Recognition of Point Sets Objects in Realistic Scenes","display_name":"Recognition of Point Sets Objects in Realistic Scenes","publication_year":2020,"publication_date":"2020-04-04","ids":{"openalex":"https://openalex.org/W3014648643","doi":"https://doi.org/10.1155/2020/4925821","mag":"3014648643"},"language":"en","primary_location":{"id":"doi:10.1155/2020/4925821","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2020/4925821","pdf_url":"https://downloads.hindawi.com/journals/misy/2020/4925821.pdf","source":{"id":"https://openalex.org/S152111507","display_name":"Mobile Information Systems","issn_l":"1574-017X","issn":["1574-017X","1875-905X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Mobile Information Systems","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://downloads.hindawi.com/journals/misy/2020/4925821.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5067063465","display_name":"Ruizhen Gao","orcid":"https://orcid.org/0000-0001-5127-6603"},"institutions":[{"id":"https://openalex.org/I106079672","display_name":"Hebei University of Engineering","ror":"https://ror.org/036h65h05","country_code":"CN","type":"education","lineage":["https://openalex.org/I106079672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruizhen Gao","raw_affiliation_strings":["Hebei University of Engineering, Handan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hebei University of Engineering, Handan, China","institution_ids":["https://openalex.org/I106079672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100338548","display_name":"Xiaohui Li","orcid":"https://orcid.org/0000-0002-7624-3928"},"institutions":[{"id":"https://openalex.org/I106079672","display_name":"Hebei University of Engineering","ror":"https://ror.org/036h65h05","country_code":"CN","type":"education","lineage":["https://openalex.org/I106079672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xiaohui Li","raw_affiliation_strings":["Hebei University of Engineering, Handan, China"],"raw_orcid":"https://orcid.org/0000-0002-7624-3928","affiliations":[{"raw_affiliation_string":"Hebei University of Engineering, Handan, China","institution_ids":["https://openalex.org/I106079672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5039740996","display_name":"Jingjun Zhang","orcid":"https://orcid.org/0000-0001-8553-077X"},"institutions":[{"id":"https://openalex.org/I106079672","display_name":"Hebei University of Engineering","ror":"https://ror.org/036h65h05","country_code":"CN","type":"education","lineage":["https://openalex.org/I106079672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jingjun Zhang","raw_affiliation_strings":["Hebei University of Engineering, Handan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Hebei University of Engineering, Handan, China","institution_ids":["https://openalex.org/I106079672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5100338548"],"corresponding_institution_ids":["https://openalex.org/I106079672"],"apc_list":{"value":2550,"currency":"USD","value_usd":2550},"apc_paid":{"value":2550,"currency":"USD","value_usd":2550},"fwci":0.0,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.03199544,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":"2020","issue":null,"first_page":"1","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9962999820709229,"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":0.9962999820709229,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9937999844551086,"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/T14339","display_name":"Image Processing and 3D Reconstruction","score":0.9814000129699707,"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/point-cloud","display_name":"Point cloud","score":0.9256089925765991},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8792300224304199},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6866304874420166},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5856277346611023},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5452393293380737},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5446677803993225},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5429589152336121},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5216175317764282},{"id":"https://openalex.org/keywords/euclidean-geometry","display_name":"Euclidean geometry","score":0.4461124539375305},{"id":"https://openalex.org/keywords/data-set","display_name":"Data set","score":0.4423838257789612},{"id":"https://openalex.org/keywords/euclidean-distance","display_name":"Euclidean distance","score":0.43691059947013855},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3264913856983185}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.9256089925765991},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8792300224304199},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6866304874420166},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5856277346611023},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5452393293380737},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5446677803993225},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5429589152336121},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5216175317764282},{"id":"https://openalex.org/C129782007","wikidata":"https://www.wikidata.org/wiki/Q162886","display_name":"Euclidean geometry","level":2,"score":0.4461124539375305},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.4423838257789612},{"id":"https://openalex.org/C120174047","wikidata":"https://www.wikidata.org/wiki/Q847073","display_name":"Euclidean distance","level":2,"score":0.43691059947013855},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3264913856983185},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1155/2020/4925821","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2020/4925821","pdf_url":"https://downloads.hindawi.com/journals/misy/2020/4925821.pdf","source":{"id":"https://openalex.org/S152111507","display_name":"Mobile Information Systems","issn_l":"1574-017X","issn":["1574-017X","1875-905X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Mobile Information Systems","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ee04dcb8df524aaf876081243df88415","is_oa":false,"landing_page_url":"https://doaj.org/article/ee04dcb8df524aaf876081243df88415","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Mobile Information Systems, Vol 2020 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1155/2020/4925821","is_oa":true,"landing_page_url":"https://doi.org/10.1155/2020/4925821","pdf_url":"https://downloads.hindawi.com/journals/misy/2020/4925821.pdf","source":{"id":"https://openalex.org/S152111507","display_name":"Mobile Information Systems","issn_l":"1574-017X","issn":["1574-017X","1875-905X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310318577","host_organization_name":"IOS Press","host_organization_lineage":["https://openalex.org/P4310318577"],"host_organization_lineage_names":["IOS Press"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Mobile Information Systems","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G4807668271","display_name":null,"funder_award_id":"ZD2018207","funder_id":"https://openalex.org/F4320322163","funder_display_name":"Natural Science Foundation of Hebei Province"},{"id":"https://openalex.org/G4907004002","display_name":null,"funder_award_id":"F2017402182","funder_id":"https://openalex.org/F4320322163","funder_display_name":"Natural Science Foundation of Hebei Province"}],"funders":[{"id":"https://openalex.org/F4320322163","display_name":"Natural Science Foundation of Hebei Province","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3014648643.pdf","grobid_xml":"https://content.openalex.org/works/W3014648643.grobid-xml"},"referenced_works_count":1,"referenced_works":["https://openalex.org/W2254644702"],"related_works":["https://openalex.org/W2090152127","https://openalex.org/W1965169884","https://openalex.org/W2008939113","https://openalex.org/W3125580510","https://openalex.org/W2033213447","https://openalex.org/W14679004","https://openalex.org/W1566651525","https://openalex.org/W2977652649","https://openalex.org/W2318206461","https://openalex.org/W37157938"],"abstract_inverted_index":{"With":[0],"the":[1,85,119,125,144,148,152,164,187],"emergence":[2],"of":[3,27,46,51,75,87,118,141,189],"new":[4],"intelligent":[5],"sensing":[6],"technologies":[7],"such":[8],"as":[9],"3D":[10,28],"scanners":[11],"and":[12,22,77,147,173,181],"stereo":[13],"vision,":[14],"high-quality":[15],"point":[16,33,120,175,190],"clouds":[17,34,41,191],"have":[18],"become":[19],"very":[20,196],"convenient":[21],"lower":[23],"cost.":[24],"The":[25,159],"research":[26],"object":[29],"recognition":[30],"based":[31],"on":[32,143],"has":[35],"also":[36],"received":[37],"widespread":[38],"attention.":[39],"Point":[40],"are":[42],"an":[43,138],"important":[44],"type":[45],"geometric":[47],"data":[48,59,76,122],"structure.":[49],"Because":[50],"its":[52],"irregular":[53],"format,":[54],"many":[55],"researchers":[56],"convert":[57],"this":[58,69,81,128,168],"into":[60],"regular":[61],"three-dimensional":[62],"voxel":[63],"grids":[64],"or":[65],"image":[66],"collections.":[67],"However,":[68],"can":[70,156,170],"lead":[71],"to":[72,100,114,123],"unnecessary":[73],"bulk":[74],"cause":[78],"problems.":[79],"In":[80,134],"paper,":[82],"we":[83,107],"consider":[84],"problem":[86],"recognizing":[88],"objects":[89,102,177],"in":[90,103,151,167,178],"realistic":[91,104,179],"senses.":[92],"We":[93],"first":[94],"use":[95,108],"Euclidean":[96],"distance":[97],"clustering":[98],"method":[99],"segment":[101],"scenes.":[105],"Then":[106],"a":[109,183],"deep":[110],"learning":[111],"network":[112,129,165],"structure":[113,130,166],"directly":[115],"extract":[116],"features":[117],"cloud":[121,176],"recognize":[124],"objects.":[126],"Theoretically,":[127],"shows":[131],"strong":[132],"performance.":[133],"experiment,":[135],"there":[136],"is":[137,192,195],"accuracy":[139,149,185],"rate":[140,150],"98.8%":[142],"training":[145],"set,":[146],"experimental":[153,160],"test":[154],"set":[155],"reach":[157],"89.7%.":[158],"results":[161],"show":[162],"that":[163],"paper":[169],"accurately":[171],"identify":[172],"classify":[174],"scenes":[180],"maintain":[182],"certain":[184],"when":[186],"number":[188],"small,":[193],"which":[194],"robust.":[197]},"counts_by_year":[{"year":2024,"cited_by_count":2}],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2025-10-10T00:00:00"}