{"id":"https://openalex.org/W2170050278","doi":"https://doi.org/10.1109/robot.2008.4543335","title":"Towards detection of orthogonal planes in monocular images of indoor environments","display_name":"Towards detection of orthogonal planes in monocular images of indoor environments","publication_year":2008,"publication_date":"2008-05-01","ids":{"openalex":"https://openalex.org/W2170050278","doi":"https://doi.org/10.1109/robot.2008.4543335","mag":"2170050278"},"language":"en","primary_location":{"id":"doi:10.1109/robot.2008.4543335","is_oa":false,"landing_page_url":"https://doi.org/10.1109/robot.2008.4543335","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Robotics and Automation","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/A5066067492","display_name":"Branislav Mi\u010du\u0161\u00edk","orcid":"https://orcid.org/0000-0003-3896-9848"},"institutions":[{"id":"https://openalex.org/I162714631","display_name":"George Mason University","ror":"https://ror.org/02jqj7156","country_code":"US","type":"education","lineage":["https://openalex.org/I162714631"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Branislav Micusik","raw_affiliation_strings":["George Mason University, Fairfax, VA, US"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"George Mason University, Fairfax, VA, US","institution_ids":["https://openalex.org/I162714631"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007281586","display_name":"Horst Wildenauer","orcid":null},"institutions":[{"id":"https://openalex.org/I145847075","display_name":"TU Wien","ror":"https://ror.org/04d836q62","country_code":"AT","type":"education","lineage":["https://openalex.org/I145847075"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Horst Wildenauer","raw_affiliation_strings":["Faculty of Electrical Engineering and Information Technology, Vienna University of Technology, Austria, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering and Information Technology, Vienna University of Technology, Austria, Austria","institution_ids":["https://openalex.org/I145847075"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013565399","display_name":"Markus Vincze","orcid":"https://orcid.org/0000-0002-2799-491X"},"institutions":[{"id":"https://openalex.org/I145847075","display_name":"TU Wien","ror":"https://ror.org/04d836q62","country_code":"AT","type":"education","lineage":["https://openalex.org/I145847075"]}],"countries":["AT"],"is_corresponding":false,"raw_author_name":"Markus Vincze","raw_affiliation_strings":["Faculty of Electrical Engineering and Information Technology, Vienna University of Technology, Austria, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Electrical Engineering and Information Technology, Vienna University of Technology, Austria, Austria","institution_ids":["https://openalex.org/I145847075"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.346,"has_fulltext":false,"cited_by_count":32,"citation_normalized_percentile":{"value":0.91136256,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"999","last_page":"1004"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9997000098228455,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9997000098228455,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9993000030517578,"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/vanishing-point","display_name":"Vanishing point","score":0.7502087354660034},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6878401041030884},{"id":"https://openalex.org/keywords/markov-random-field","display_name":"Markov random field","score":0.6336144208908081},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5846389532089233},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5401119589805603},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.49194690585136414},{"id":"https://openalex.org/keywords/maximum-a-posteriori-estimation","display_name":"Maximum a posteriori estimation","score":0.49045273661613464},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.4798926115036011},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4727139174938202},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.444557249546051},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.42355069518089294},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.386458158493042},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.36058998107910156},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.32858625054359436},{"id":"https://openalex.org/keywords/maximum-likelihood","display_name":"Maximum likelihood","score":0.13024160265922546}],"concepts":[{"id":"https://openalex.org/C99404194","wikidata":"https://www.wikidata.org/wiki/Q163362","display_name":"Vanishing point","level":3,"score":0.7502087354660034},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6878401041030884},{"id":"https://openalex.org/C2778045648","wikidata":"https://www.wikidata.org/wiki/Q176827","display_name":"Markov random field","level":4,"score":0.6336144208908081},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5846389532089233},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5401119589805603},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.49194690585136414},{"id":"https://openalex.org/C9810830","wikidata":"https://www.wikidata.org/wiki/Q635384","display_name":"Maximum a posteriori estimation","level":3,"score":0.49045273661613464},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.4798926115036011},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4727139174938202},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.444557249546051},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.42355069518089294},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.386458158493042},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.36058998107910156},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.32858625054359436},{"id":"https://openalex.org/C49781872","wikidata":"https://www.wikidata.org/wiki/Q1045555","display_name":"Maximum likelihood","level":2,"score":0.13024160265922546},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/robot.2008.4543335","is_oa":false,"landing_page_url":"https://doi.org/10.1109/robot.2008.4543335","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2008 IEEE International Conference on Robotics and Automation","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.8100000023841858}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W89301254","https://openalex.org/W1986377419","https://openalex.org/W1986599212","https://openalex.org/W1999478155","https://openalex.org/W2033819227","https://openalex.org/W2082428831","https://openalex.org/W2102532099","https://openalex.org/W2106595755","https://openalex.org/W2125310925","https://openalex.org/W2127685556","https://openalex.org/W2133889189","https://openalex.org/W2135414191","https://openalex.org/W2154658342","https://openalex.org/W2161223669","https://openalex.org/W2161350794","https://openalex.org/W2164918853","https://openalex.org/W2169415915","https://openalex.org/W2170574795","https://openalex.org/W2209124607","https://openalex.org/W2209228044","https://openalex.org/W3141075111","https://openalex.org/W6688151676"],"related_works":["https://openalex.org/W2097090565","https://openalex.org/W2054797574","https://openalex.org/W2008444830","https://openalex.org/W2804375118","https://openalex.org/W2112506753","https://openalex.org/W2029809897","https://openalex.org/W2132110568","https://openalex.org/W2160831725","https://openalex.org/W1495937069","https://openalex.org/W4233585817"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,103],"describe":[4],"the":[5,12,34,44,89,155,158,172],"components":[6],"of":[7,14,30,36,48,77,140],"a":[8,84,91,96,105,125,138,162],"novel":[9,106],"algorithm":[10],"for":[11,88],"extraction":[13],"dominant":[15],"orthogonal":[16,51],"planar":[17,79],"structures":[18],"from":[19,112],"monocular":[20],"images":[21,141],"taken":[22],"in":[23,54,95,161],"indoor":[24],"environments.":[25],"The":[26,75,133],"basic":[27],"building":[28],"block":[29],"our":[31],"approach":[32],"is":[33,81],"use":[35],"vanishing":[37,40,52,113],"points":[38,58,114],"and":[39,115,120,149,165],"lines":[41],"imposed":[42,128],"by":[43,61,129],"frequently":[45],"observed":[46],"dominance":[47],"three":[49],"mutually":[50],"directions":[53],"man-made":[55],"world.":[56],"Vanishing":[57],"are":[59],"found":[60],"an":[62,130],"improved":[63],"approach,":[64],"taking":[65],"no":[66],"assumptions":[67],"on":[68,137],"known":[69],"internal":[70],"or":[71],"external":[72],"camera":[73],"parameters.":[74],"problem":[76],"detecting":[78],"patches":[80],"attacked":[82],"using":[83],"probabilistic":[85],"framework,":[86],"searching":[87],"maximum":[90],"posteriori":[92],"probability":[93],"(MAP)":[94],"Markov":[97],"Random":[98],"Field":[99],"(MRF).":[100],"For":[101],"this,":[102],"propose":[104],"formulation":[107],"fusing":[108],"geometric":[109],"information":[110],"obtained":[111],"features,":[116],"such":[117],"as":[118],"rectangles":[119],"partial":[121],"rectangles,":[122],"together":[123],"with":[124],"color-homogeneity":[126],"criteria":[127],"image":[131,147],"over-segmentation.":[132],"method":[134],"was":[135],"evaluated":[136],"set":[139],"exhibiting":[142],"largely":[143],"varying":[144],"characteristics":[145],"concerning":[146],"quality":[148],"scene":[150],"complexity.":[151],"Experiments":[152],"show":[153],"that":[154,166],"method,":[156],"despite":[157],"variations,":[159],"works":[160],"stable":[163],"manner":[164],"its":[167],"performance":[168],"compares":[169],"favorably":[170],"to":[171],"state-of-the-art.":[173]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":5},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":3},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":3},{"year":2012,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
