{"id":"https://openalex.org/W2000521828","doi":"https://doi.org/10.1109/icapr.2015.7050670","title":"Building facade detection via plane support points clustering","display_name":"Building facade detection via plane support points clustering","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2000521828","doi":"https://doi.org/10.1109/icapr.2015.7050670","mag":"2000521828"},"language":"en","primary_location":{"id":"doi:10.1109/icapr.2015.7050670","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icapr.2015.7050670","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Eighth International Conference on Advances in Pattern Recognition (ICAPR)","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/A5087006132","display_name":"Vikram Sindhu","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"V. Sai Sindhu","raw_affiliation_strings":["Image Understanding Group, Uurmi Systems Pvt. Ltd., Hyderabad, India"],"affiliations":[{"raw_affiliation_string":"Image Understanding Group, Uurmi Systems Pvt. Ltd., Hyderabad, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062754011","display_name":"Abhishek Kumar Tripathi","orcid":"https://orcid.org/0000-0001-9627-6359"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Abhishek Kumar Tripathi","raw_affiliation_strings":["Image Understanding Group, Uurmi Systems Pvt. Ltd., Hyderabad, India"],"affiliations":[{"raw_affiliation_string":"Image Understanding Group, Uurmi Systems Pvt. Ltd., Hyderabad, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032907877","display_name":"Shanti Swarup","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Shanti Swarup","raw_affiliation_strings":["Image Understanding Group, Uurmi Systems Pvt. Ltd., Hyderabad, India"],"affiliations":[{"raw_affiliation_string":"Image Understanding Group, Uurmi Systems Pvt. Ltd., Hyderabad, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5087006132"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.04393961,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9955000281333923,"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":0.9955000281333923,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9894000291824341,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T10689","display_name":"Remote-Sensing Image Classification","score":0.9886000156402588,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/cluster-analysis","display_name":"Cluster analysis","score":0.753750205039978},{"id":"https://openalex.org/keywords/line-segment","display_name":"Line segment","score":0.645499050617218},{"id":"https://openalex.org/keywords/vanishing-point","display_name":"Vanishing point","score":0.6309758424758911},{"id":"https://openalex.org/keywords/histogram","display_name":"Histogram","score":0.6164624094963074},{"id":"https://openalex.org/keywords/plane","display_name":"Plane (geometry)","score":0.6105926632881165},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5924177169799805},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5833183526992798},{"id":"https://openalex.org/keywords/line","display_name":"Line (geometry)","score":0.574516236782074},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5483893752098083},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5072369575500488},{"id":"https://openalex.org/keywords/computation","display_name":"Computation","score":0.506546139717102},{"id":"https://openalex.org/keywords/cluster","display_name":"Cluster (spacecraft)","score":0.4733940362930298},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3722647428512573},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.35979899764060974},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.34802839159965515},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.27236369252204895},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.162823885679245}],"concepts":[{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.753750205039978},{"id":"https://openalex.org/C182124507","wikidata":"https://www.wikidata.org/wiki/Q166154","display_name":"Line segment","level":2,"score":0.645499050617218},{"id":"https://openalex.org/C99404194","wikidata":"https://www.wikidata.org/wiki/Q163362","display_name":"Vanishing point","level":3,"score":0.6309758424758911},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.6164624094963074},{"id":"https://openalex.org/C17825722","wikidata":"https://www.wikidata.org/wiki/Q17285","display_name":"Plane (geometry)","level":2,"score":0.6105926632881165},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5924177169799805},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5833183526992798},{"id":"https://openalex.org/C198352243","wikidata":"https://www.wikidata.org/wiki/Q37105","display_name":"Line (geometry)","level":2,"score":0.574516236782074},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5483893752098083},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5072369575500488},{"id":"https://openalex.org/C45374587","wikidata":"https://www.wikidata.org/wiki/Q12525525","display_name":"Computation","level":2,"score":0.506546139717102},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.4733940362930298},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3722647428512573},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.35979899764060974},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.34802839159965515},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.27236369252204895},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.162823885679245},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icapr.2015.7050670","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icapr.2015.7050670","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2015 Eighth International Conference on Advances in Pattern Recognition (ICAPR)","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":0.8299999833106995}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W15567185","https://openalex.org/W161429679","https://openalex.org/W1595520679","https://openalex.org/W1965642791","https://openalex.org/W1974064487","https://openalex.org/W2074154756","https://openalex.org/W2090426641","https://openalex.org/W2095642712","https://openalex.org/W2102532099","https://openalex.org/W2134185806","https://openalex.org/W2155256157","https://openalex.org/W2161223669","https://openalex.org/W3154120517","https://openalex.org/W6606590666","https://openalex.org/W6635774557","https://openalex.org/W6641670001","https://openalex.org/W6669186261","https://openalex.org/W6674561531","https://openalex.org/W6794183999"],"related_works":["https://openalex.org/W4386085495","https://openalex.org/W2601467812","https://openalex.org/W2506376595","https://openalex.org/W2800988540","https://openalex.org/W1557097679","https://openalex.org/W2164847519","https://openalex.org/W2434409560","https://openalex.org/W1990238906","https://openalex.org/W2284162084","https://openalex.org/W1985392633"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"a":[3,27],"building":[4,94],"facade":[5],"detection":[6,92],"algorithm":[7,11,102,122],"is":[8,31,46],"proposed.":[9],"Proposed":[10],"first":[12],"detects":[13,123],"the":[14,35,39,50,68,72,83,87],"edges":[15,69],"present":[16,85],"in":[17,38,86,110],"an":[18],"image":[19],"and":[20,60,89,106],"connects":[21],"them":[22],"into":[23],"line":[24,51],"segments.":[25],"Then":[26],"polar":[28],"histogram":[29],"mapping":[30],"used":[32],"to":[33,48,54,66,71],"find":[34],"vanishing":[36,56,63],"points":[37,64,81],"scene.":[40],"An":[41],"approach":[42],"with":[43,112,125],"low":[44,104],"complexity":[45,105],"introduced":[47],"cluster":[49,67],"segments":[52,59],"according":[53,70],"their":[55,61],"points.":[57],"Line":[58],"corresponding":[62],"help":[65],"plane":[73,79,98],"surfaces":[74],"they":[75],"support.":[76],"Clustering":[77],"of":[78,93],"support":[80,99],"determines":[82],"planes":[84],"scene":[88],"thus":[90],"enables":[91],"facades.":[95],"Our":[96],"new":[97],"point":[100],"clustering":[101],"has":[103],"less":[107],"computation":[108],"time":[109],"comparison":[111],"other":[113],"prior":[114],"art":[115],"algorithms.":[116],"Results":[117],"show":[118],"that":[119],"our":[120],"proposed":[121],"facades":[124],"78%":[126],"accuracy.":[127]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}