{"id":"https://openalex.org/W2922396397","doi":"https://doi.org/10.3390/rs11060635","title":"Major Orientation Estimation-Based Rock Surface Extraction for 3D Rock-Mass Point Clouds","display_name":"Major Orientation Estimation-Based Rock Surface Extraction for 3D Rock-Mass Point Clouds","publication_year":2019,"publication_date":"2019-03-15","ids":{"openalex":"https://openalex.org/W2922396397","doi":"https://doi.org/10.3390/rs11060635","mag":"2922396397"},"language":"en","primary_location":{"id":"doi:10.3390/rs11060635","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11060635","pdf_url":"https://www.mdpi.com/2072-4292/11/6/635/pdf?version=1552644110","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/11/6/635/pdf?version=1552644110","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5027716561","display_name":"Lupeng Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lupeng Liu","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, No. 19 Yuquan Road, Shijingshan District, Beijing 100049, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, No. 19 Yuquan Road, Shijingshan District, Beijing 100049, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076518693","display_name":"Jun Xiao","orcid":"https://orcid.org/0000-0002-1799-3948"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jun Xiao","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, No. 19 Yuquan Road, Shijingshan District, Beijing 100049, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, No. 19 Yuquan Road, Shijingshan District, Beijing 100049, China","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100347250","display_name":"Ying Wang","orcid":"https://orcid.org/0000-0003-4121-1675"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ying Wang","raw_affiliation_strings":["School of Artificial Intelligence, University of Chinese Academy of Sciences, No. 19 Yuquan Road, Shijingshan District, Beijing 100049, China"],"affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, University of Chinese Academy of Sciences, No. 19 Yuquan Road, Shijingshan District, Beijing 100049, China","institution_ids":["https://openalex.org/I4210165038"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5076518693"],"corresponding_institution_ids":["https://openalex.org/I4210165038"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":7.0142,"has_fulltext":true,"cited_by_count":24,"citation_normalized_percentile":{"value":0.96641198,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"11","issue":"6","first_page":"635","last_page":"635"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9998999834060669,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9994999766349792,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9990000128746033,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/point-cloud","display_name":"Point cloud","score":0.8722960948944092},{"id":"https://openalex.org/keywords/rock-mass-classification","display_name":"Rock mass classification","score":0.6316393613815308},{"id":"https://openalex.org/keywords/voxel","display_name":"Voxel","score":0.5695496797561646},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5061025023460388},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.4937489926815033},{"id":"https://openalex.org/keywords/extraction","display_name":"Extraction (chemistry)","score":0.4857824146747589},{"id":"https://openalex.org/keywords/surface","display_name":"Surface (topology)","score":0.46214330196380615},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45615071058273315},{"id":"https://openalex.org/keywords/photogrammetry","display_name":"Photogrammetry","score":0.44709885120391846},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.4348083734512329},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.41828683018684387},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.26773542165756226},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16081467270851135},{"id":"https://openalex.org/keywords/geotechnical-engineering","display_name":"Geotechnical engineering","score":0.07129231095314026}],"concepts":[{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.8722960948944092},{"id":"https://openalex.org/C41242791","wikidata":"https://www.wikidata.org/wiki/Q17105549","display_name":"Rock mass classification","level":2,"score":0.6316393613815308},{"id":"https://openalex.org/C54170458","wikidata":"https://www.wikidata.org/wiki/Q663554","display_name":"Voxel","level":2,"score":0.5695496797561646},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5061025023460388},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.4937489926815033},{"id":"https://openalex.org/C4725764","wikidata":"https://www.wikidata.org/wiki/Q844704","display_name":"Extraction (chemistry)","level":2,"score":0.4857824146747589},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.46214330196380615},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45615071058273315},{"id":"https://openalex.org/C117455697","wikidata":"https://www.wikidata.org/wiki/Q190149","display_name":"Photogrammetry","level":2,"score":0.44709885120391846},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.4348083734512329},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.41828683018684387},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.26773542165756226},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16081467270851135},{"id":"https://openalex.org/C187320778","wikidata":"https://www.wikidata.org/wiki/Q1349130","display_name":"Geotechnical engineering","level":1,"score":0.07129231095314026},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.3390/rs11060635","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11060635","pdf_url":"https://www.mdpi.com/2072-4292/11/6/635/pdf?version=1552644110","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:6d950f59130d422c9ba080dbc2a1a149","is_oa":true,"landing_page_url":"https://doaj.org/article/6d950f59130d422c9ba080dbc2a1a149","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 11, Iss 6, p 635 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.3390/rs11060635","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs11060635","pdf_url":"https://www.mdpi.com/2072-4292/11/6/635/pdf?version=1552644110","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2120959379","display_name":null,"funder_award_id":"2015361","funder_id":"https://openalex.org/F4320322847","funder_display_name":"Youth Innovation Promotion Association of the Chinese Academy of Sciences"},{"id":"https://openalex.org/G4125562610","display_name":null,"funder_award_id":"61471338","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8285737918","display_name":null,"funder_award_id":"Z171100001117048","funder_id":"https://openalex.org/F4320334978","funder_display_name":"Beijing Nova Program"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322847","display_name":"Youth Innovation Promotion Association of the Chinese Academy of Sciences","ror":"https://ror.org/031141b54"},{"id":"https://openalex.org/F4320334978","display_name":"Beijing Nova Program","ror":"https://ror.org/034k14f91"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2922396397.pdf","grobid_xml":"https://content.openalex.org/works/W2922396397.grobid-xml"},"referenced_works_count":58,"referenced_works":["https://openalex.org/W599756832","https://openalex.org/W1263619056","https://openalex.org/W1532428428","https://openalex.org/W1540766687","https://openalex.org/W1558522206","https://openalex.org/W1637459849","https://openalex.org/W1860944057","https://openalex.org/W1969366022","https://openalex.org/W1970397379","https://openalex.org/W1973441814","https://openalex.org/W1977271893","https://openalex.org/W1991472080","https://openalex.org/W1996947592","https://openalex.org/W1999889655","https://openalex.org/W2000018820","https://openalex.org/W2007200979","https://openalex.org/W2008665443","https://openalex.org/W2029895480","https://openalex.org/W2035850930","https://openalex.org/W2038771072","https://openalex.org/W2041642242","https://openalex.org/W2043237179","https://openalex.org/W2047798910","https://openalex.org/W2050601294","https://openalex.org/W2051956109","https://openalex.org/W2057088289","https://openalex.org/W2082767534","https://openalex.org/W2085261163","https://openalex.org/W2090046561","https://openalex.org/W2095905764","https://openalex.org/W2099088762","https://openalex.org/W2108569747","https://openalex.org/W2111486632","https://openalex.org/W2120270635","https://openalex.org/W2131618054","https://openalex.org/W2135249503","https://openalex.org/W2152864241","https://openalex.org/W2162971901","https://openalex.org/W2163842790","https://openalex.org/W2171363519","https://openalex.org/W2205809928","https://openalex.org/W2327498679","https://openalex.org/W2437153906","https://openalex.org/W2474934002","https://openalex.org/W2516530272","https://openalex.org/W2599022140","https://openalex.org/W2611946301","https://openalex.org/W2621534427","https://openalex.org/W2803790533","https://openalex.org/W2804872164","https://openalex.org/W2899434313","https://openalex.org/W4206021986","https://openalex.org/W4254019612","https://openalex.org/W6618229384","https://openalex.org/W6631959226","https://openalex.org/W6676467034","https://openalex.org/W6677794103","https://openalex.org/W6721076276"],"related_works":["https://openalex.org/W2365572566","https://openalex.org/W2394068580","https://openalex.org/W2525880111","https://openalex.org/W2369515111","https://openalex.org/W2051732542","https://openalex.org/W1902541973","https://openalex.org/W2101607253","https://openalex.org/W2020829175","https://openalex.org/W2379433588","https://openalex.org/W3005012932"],"abstract_inverted_index":{"In":[0,188],"the":[1,31,48,101,112,127,132,148,154,160,204,213],"fields":[2],"of":[3,7,15,21,33,38,50,56,79,118,156,176,181],"3D":[4,42,51],"modeling,":[5],"analysis":[6],"discontinuities":[8],"and":[9,23,26,53,64,95,110,123,159,195,218],"engineering":[10,54],"calculation,":[11],"surface":[12,34,98,177],"extraction":[13,37],"is":[14,105,167],"great":[16],"importance.":[17],"The":[18,179,208],"rapid":[19],"development":[20],"photogrammetry":[22],"Light":[24],"Detection":[25],"Ranging":[27],"(LiDAR)":[28],"technology":[29],"facilitates":[30],"study":[32],"extraction.":[35,99],"Automatic":[36],"rock":[39,57,69,97,171,221],"surfaces":[40,70,222],"from":[41,71],"rock-mass":[43,73,197,225],"point":[44,74,113,193,198,226],"clouds":[45,199],"also":[46],"becomes":[47],"basis":[49,155],"modeling":[52],"calculation":[55],"mass.":[58],"This":[59,76],"paper":[60],"presents":[61],"an":[62],"automated":[63],"effective":[65],"method":[66,77,163,215],"for":[67,107,202],"extracting":[68],"unorganized":[72,224],"clouds.":[75,227],"consists":[78],"three":[80,116],"stages:":[81],"(i)":[82],"clustering":[83],"based":[84,91,164],"on":[85,92,153,165],"voxels;":[86],"(ii)":[87],"estimating":[88],"major":[89,139,157],"orientations":[90,140,158],"Gaussian":[93,145],"Kernel":[94],"(iii)":[96],"Firstly,":[100],"two-level":[102],"spatial":[103],"grid":[104],"used":[106,201],"fast":[108],"voxelization":[109],"segmenting":[111],"cloud":[114,194],"into":[115],"types":[117],"voxels,":[119,129],"including":[120],"coplanar,":[121],"non-coplanar":[122],"sparse":[124],"voxels.":[125],"Secondly,":[126],"coplanar":[128,185],"rather":[130],"than":[131],"scattered":[133],"points,":[134],"are":[135,151,184,200],"employed":[136],"to":[137,169],"estimate":[138],"by":[141],"using":[142],"a":[143],"bivariate":[144],"Kernel.":[146],"Finally,":[147],"seed":[149],"voxels":[150,166],"selected":[152],"region":[161],"growing":[162],"applied":[168],"extract":[170,220],"surfaces,":[172],"resulting":[173],"in":[174,223],"sets":[175],"clusters.":[178],"sub-surfaces":[180],"each":[182],"cluster":[183],"or":[186],"parallel.":[187],"this":[189],"paper,":[190],"artificial":[191],"icosahedron":[192],"natural":[196],"testing":[203],"proposed":[205,214],"method,":[206],"respectively.":[207],"experimental":[209],"results":[210],"show":[211],"that,":[212],"can":[216],"effectively":[217],"accurately":[219]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":10},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}