{"id":"https://openalex.org/W2135748322","doi":"https://doi.org/10.1109/icassp.2006.1660383","title":"An Automatic 3D City Model : A Bayesian Approach Using Satellite Images","display_name":"An Automatic 3D City Model : A Bayesian Approach Using Satellite Images","publication_year":2006,"publication_date":"2006-08-03","ids":{"openalex":"https://openalex.org/W2135748322","doi":"https://doi.org/10.1109/icassp.2006.1660383","mag":"2135748322"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2006.1660383","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2006.1660383","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings","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/A5076585669","display_name":"Florent Lafarge","orcid":"https://orcid.org/0000-0001-6117-976X"},"institutions":[{"id":"https://openalex.org/I1326498283","display_name":"Institut national de recherche en sciences et technologies du num\u00e9rique","ror":"https://ror.org/02kvxyf05","country_code":"FR","type":"government","lineage":["https://openalex.org/I1326498283"]},{"id":"https://openalex.org/I1327553481","display_name":"Institut national de l\u2019information g\u00e9ographique et foresti\u00e8re","ror":"https://ror.org/05jxfge78","country_code":"FR","type":"government","lineage":["https://openalex.org/I1327553481"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"F. Lafarge","raw_affiliation_strings":["Ariana Reseach Group, INRIA/I3S, Sophia-Antipolis, France","Institut G\u00e9ographique National, Saint Mande, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ariana Reseach Group, INRIA/I3S, Sophia-Antipolis, France","institution_ids":["https://openalex.org/I1326498283"]},{"raw_affiliation_string":"Institut G\u00e9ographique National, Saint Mande, France","institution_ids":["https://openalex.org/I1327553481"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5106126872","display_name":"Xavier Descombes","orcid":"https://orcid.org/0000-0002-7611-6021"},"institutions":[{"id":"https://openalex.org/I1326498283","display_name":"Institut national de recherche en sciences et technologies du num\u00e9rique","ror":"https://ror.org/02kvxyf05","country_code":"FR","type":"government","lineage":["https://openalex.org/I1326498283"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"X. Descombes","raw_affiliation_strings":["Ariana Reseach Group, INRIA/I3S, Sophia-Antipolis, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ariana Reseach Group, INRIA/I3S, Sophia-Antipolis, France","institution_ids":["https://openalex.org/I1326498283"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018158883","display_name":"Josiane Zerubia","orcid":"https://orcid.org/0000-0002-7444-0856"},"institutions":[{"id":"https://openalex.org/I1326498283","display_name":"Institut national de recherche en sciences et technologies du num\u00e9rique","ror":"https://ror.org/02kvxyf05","country_code":"FR","type":"government","lineage":["https://openalex.org/I1326498283"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"J. Zerubia","raw_affiliation_strings":["Ariana Reseach Group, INRIA/I3S, Sophia-Antipolis, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Ariana Reseach Group, INRIA/I3S, Sophia-Antipolis, France","institution_ids":["https://openalex.org/I1326498283"]}]},{"author_position":"last","author":{"id":null,"display_name":"M.-P. Deseilligny","orcid":null},"institutions":[{"id":"https://openalex.org/I1327553481","display_name":"Institut national de l\u2019information g\u00e9ographique et foresti\u00e8re","ror":"https://ror.org/05jxfge78","country_code":"FR","type":"government","lineage":["https://openalex.org/I1327553481"]}],"countries":["FR"],"is_corresponding":false,"raw_author_name":"M.-P. Deseilligny","raw_affiliation_strings":["Institut G\u00e9ographique National, Saint Mande, France"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institut G\u00e9ographique National, Saint Mande, France","institution_ids":["https://openalex.org/I1327553481"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.7188,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.97299904,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"2","issue":null,"first_page":"II","last_page":"477"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9973999857902527,"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":0.9973999857902527,"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/T12698","display_name":"3D Modeling in Geospatial Applications","score":0.9937999844551086,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T10226","display_name":"Land Use and Ecosystem Services","score":0.9919000267982483,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/a-priori-and-a-posteriori","display_name":"A priori and a posteriori","score":0.7259048223495483},{"id":"https://openalex.org/keywords/simulated-annealing","display_name":"Simulated annealing","score":0.703505277633667},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6954830884933472},{"id":"https://openalex.org/keywords/parametric-statistics","display_name":"Parametric statistics","score":0.6666419506072998},{"id":"https://openalex.org/keywords/bayesian-probability","display_name":"Bayesian probability","score":0.6460815072059631},{"id":"https://openalex.org/keywords/parametric-model","display_name":"Parametric model","score":0.6377773284912109},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5559191107749939},{"id":"https://openalex.org/keywords/satellite","display_name":"Satellite","score":0.5546476244926453},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.5400422811508179},{"id":"https://openalex.org/keywords/footprint","display_name":"Footprint","score":0.5194865465164185},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4605855345726013},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3594284653663635},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.35107576847076416},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.19242432713508606},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.16940909624099731},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11559614539146423},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.11155849695205688},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09153178334236145}],"concepts":[{"id":"https://openalex.org/C75553542","wikidata":"https://www.wikidata.org/wiki/Q178161","display_name":"A priori and a posteriori","level":2,"score":0.7259048223495483},{"id":"https://openalex.org/C126980161","wikidata":"https://www.wikidata.org/wiki/Q863783","display_name":"Simulated annealing","level":2,"score":0.703505277633667},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6954830884933472},{"id":"https://openalex.org/C117251300","wikidata":"https://www.wikidata.org/wiki/Q1849855","display_name":"Parametric statistics","level":2,"score":0.6666419506072998},{"id":"https://openalex.org/C107673813","wikidata":"https://www.wikidata.org/wiki/Q812534","display_name":"Bayesian probability","level":2,"score":0.6460815072059631},{"id":"https://openalex.org/C24574437","wikidata":"https://www.wikidata.org/wiki/Q7135228","display_name":"Parametric model","level":3,"score":0.6377773284912109},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5559191107749939},{"id":"https://openalex.org/C19269812","wikidata":"https://www.wikidata.org/wiki/Q26540","display_name":"Satellite","level":2,"score":0.5546476244926453},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.5400422811508179},{"id":"https://openalex.org/C132943942","wikidata":"https://www.wikidata.org/wiki/Q2562511","display_name":"Footprint","level":2,"score":0.5194865465164185},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4605855345726013},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3594284653663635},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.35107576847076416},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.19242432713508606},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.16940909624099731},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11559614539146423},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.11155849695205688},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09153178334236145},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2006.1660383","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2006.1660383","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2006 IEEE International Conference on Acoustics Speed and Signal Processing Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.8500000238418579}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":11,"referenced_works":["https://openalex.org/W241255630","https://openalex.org/W1546283101","https://openalex.org/W1649464328","https://openalex.org/W2056760934","https://openalex.org/W2063658793","https://openalex.org/W2115632850","https://openalex.org/W2121646224","https://openalex.org/W2616590648","https://openalex.org/W6637009331","https://openalex.org/W6677044844","https://openalex.org/W6737858283"],"related_works":["https://openalex.org/W4388311650","https://openalex.org/W5922282","https://openalex.org/W1974056099","https://openalex.org/W4245343541","https://openalex.org/W2386077341","https://openalex.org/W2150865841","https://openalex.org/W2138865713","https://openalex.org/W2169353922","https://openalex.org/W2768219013","https://openalex.org/W8534870"],"abstract_inverted_index":{"We":[0],"propose":[1],"a":[2,36,49,66,75,95],"parametric":[3,37,60],"model":[4,38],"for":[5,55],"automatic":[6,18],"3D":[7],"reconstruction":[8],"of":[9,59,69,98],"urban":[10],"areas":[11],"from":[12],"high":[13],"resolution":[14],"satellite":[15],"data.":[16],"An":[17],"building":[19,32],"extraction":[20],"method":[21,45],"based":[22],"on":[23,35],"marked":[24],"point":[25],"processes":[26],"is":[27,46,86],"used":[28,87],"to":[29,64,80,88],"provide":[30],"rectangular":[31,40],"footprints.":[33],"Based":[34],"with":[39,62],"ground":[41],"footprint,":[42],"the":[43,56,81,90,94,99],"proposed":[44],"developed":[47],"using":[48],"Bayesian":[50,100],"approach":[51],":":[52],"we":[53],"search":[54],"best":[57],"configuration":[58,91],"models":[61,70,79],"respect":[63],"both":[65],"priori":[67],"knowledge":[68],"and":[71,74],"their":[72],"interactions,":[73],"likelihood":[76],"which":[77,92],"fits":[78],"DEM.":[82],"A":[83],"simulated":[84],"annealing":[85],"find":[89],"maximizes":[93],"posteriori":[96],"density":[97],"expression":[101]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
