{"id":"https://openalex.org/W2160123869","doi":"https://doi.org/10.1109/ivs.2014.6856402","title":"Robust ground plane induced homography estimation for wide angle fisheye cameras","display_name":"Robust ground plane induced homography estimation for wide angle fisheye cameras","publication_year":2014,"publication_date":"2014-06-01","ids":{"openalex":"https://openalex.org/W2160123869","doi":"https://doi.org/10.1109/ivs.2014.6856402","mag":"2160123869"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2014.6856402","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2014.6856402","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","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/A5072963268","display_name":"Moritz Knorr","orcid":null},"institutions":[{"id":"https://openalex.org/I4210120115","display_name":"Robert Bosch (United States)","ror":"https://ror.org/02venad53","country_code":"US","type":"company","lineage":["https://openalex.org/I4210120115","https://openalex.org/I889804353"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Moritz Knorr","raw_affiliation_strings":["Robert Bosch GmbH, Gerlingen-Schillerhohe, Baden-W\u00c3\u00bcrttemberg, DE","Robert Bosch GmbH, Gerlingen-Schillerhohe, Baden-W\u00fcrttemberg, DE"],"affiliations":[{"raw_affiliation_string":"Robert Bosch GmbH, Gerlingen-Schillerhohe, Baden-W\u00c3\u00bcrttemberg, DE","institution_ids":["https://openalex.org/I4210120115"]},{"raw_affiliation_string":"Robert Bosch GmbH, Gerlingen-Schillerhohe, Baden-W\u00fcrttemberg, DE","institution_ids":["https://openalex.org/I4210120115"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5060037125","display_name":"W. Niehsen","orcid":null},"institutions":[{"id":"https://openalex.org/I4210120115","display_name":"Robert Bosch (United States)","ror":"https://ror.org/02venad53","country_code":"US","type":"company","lineage":["https://openalex.org/I4210120115","https://openalex.org/I889804353"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wolfgang Niehsen","raw_affiliation_strings":["Robert Bosch GmbH, Gerlingen-Schillerhohe, Baden-W\u00c3\u00bcrttemberg, DE","Robert Bosch GmbH, Gerlingen-Schillerhohe, Baden-W\u00fcrttemberg, DE"],"affiliations":[{"raw_affiliation_string":"Robert Bosch GmbH, Gerlingen-Schillerhohe, Baden-W\u00c3\u00bcrttemberg, DE","institution_ids":["https://openalex.org/I4210120115"]},{"raw_affiliation_string":"Robert Bosch GmbH, Gerlingen-Schillerhohe, Baden-W\u00fcrttemberg, DE","institution_ids":["https://openalex.org/I4210120115"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5091574711","display_name":"Christoph Stiller","orcid":"https://orcid.org/0000-0003-4165-2075"},"institutions":[{"id":"https://openalex.org/I102335020","display_name":"Karlsruhe Institute of Technology","ror":"https://ror.org/04t3en479","country_code":"DE","type":"education","lineage":["https://openalex.org/I102335020","https://openalex.org/I1305996414"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Christoph Stiller","raw_affiliation_strings":["Karlsruher Institut fur Technologie, Karlsruhe, Baden-W\u00c3\u00bcrttemberg, DE","Karlsruher Institut fur Technologie, Karlsruhe, Baden-W\u00fcrttemberg, DE"],"affiliations":[{"raw_affiliation_string":"Karlsruher Institut fur Technologie, Karlsruhe, Baden-W\u00c3\u00bcrttemberg, DE","institution_ids":[]},{"raw_affiliation_string":"Karlsruher Institut fur Technologie, Karlsruhe, Baden-W\u00fcrttemberg, DE","institution_ids":["https://openalex.org/I102335020"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5072963268"],"corresponding_institution_ids":["https://openalex.org/I4210120115"],"apc_list":null,"apc_paid":null,"fwci":0.2439,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.62040781,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"1288","last_page":"1293"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9994999766349792,"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":0.9994999766349792,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.996999979019165,"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":0.9961000084877014,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7132248878479004},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6995892524719238},{"id":"https://openalex.org/keywords/homography","display_name":"Homography","score":0.6728414297103882},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6553075909614563},{"id":"https://openalex.org/keywords/ransac","display_name":"RANSAC","score":0.6377806067466736},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6307615637779236},{"id":"https://openalex.org/keywords/image-warping","display_name":"Image warping","score":0.5468778014183044},{"id":"https://openalex.org/keywords/parallax","display_name":"Parallax","score":0.5236634612083435},{"id":"https://openalex.org/keywords/structure-from-motion","display_name":"Structure from motion","score":0.4229486882686615},{"id":"https://openalex.org/keywords/image-plane","display_name":"Image plane","score":0.41592273116111755},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3544413447380066},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.3356740474700928},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2723614275455475},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1277497112751007}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7132248878479004},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6995892524719238},{"id":"https://openalex.org/C28751775","wikidata":"https://www.wikidata.org/wiki/Q2112539","display_name":"Homography","level":4,"score":0.6728414297103882},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6553075909614563},{"id":"https://openalex.org/C114744707","wikidata":"https://www.wikidata.org/wiki/Q218533","display_name":"RANSAC","level":3,"score":0.6377806067466736},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6307615637779236},{"id":"https://openalex.org/C157202957","wikidata":"https://www.wikidata.org/wiki/Q1659609","display_name":"Image warping","level":2,"score":0.5468778014183044},{"id":"https://openalex.org/C15759828","wikidata":"https://www.wikidata.org/wiki/Q165074","display_name":"Parallax","level":2,"score":0.5236634612083435},{"id":"https://openalex.org/C146159030","wikidata":"https://www.wikidata.org/wiki/Q7625099","display_name":"Structure from motion","level":3,"score":0.4229486882686615},{"id":"https://openalex.org/C120515352","wikidata":"https://www.wikidata.org/wiki/Q2564580","display_name":"Image plane","level":3,"score":0.41592273116111755},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3544413447380066},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.3356740474700928},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2723614275455475},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1277497112751007},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C75280867","wikidata":"https://www.wikidata.org/wiki/Q877775","display_name":"Projective space","level":3,"score":0.0},{"id":"https://openalex.org/C177846678","wikidata":"https://www.wikidata.org/wiki/Q1501864","display_name":"Projective test","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivs.2014.6856402","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2014.6856402","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2014 IEEE Intelligent Vehicles Symposium Proceedings","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/14","score":0.5899999737739563,"display_name":"Life below water"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W34982941","https://openalex.org/W200697499","https://openalex.org/W1491719799","https://openalex.org/W1519594923","https://openalex.org/W1532362218","https://openalex.org/W1646998587","https://openalex.org/W1964344553","https://openalex.org/W2033819227","https://openalex.org/W2037893491","https://openalex.org/W2085261163","https://openalex.org/W2089833520","https://openalex.org/W2102090304","https://openalex.org/W2108502244","https://openalex.org/W2117551572","https://openalex.org/W2117959563","https://openalex.org/W2143191604","https://openalex.org/W2144297066","https://openalex.org/W2147122541","https://openalex.org/W2317899514","https://openalex.org/W6601414869","https://openalex.org/W6608138123","https://openalex.org/W6629564929","https://openalex.org/W6631325901","https://openalex.org/W6631707545","https://openalex.org/W6681736998"],"related_works":["https://openalex.org/W2182681094","https://openalex.org/W1968586027","https://openalex.org/W2098809595","https://openalex.org/W1982361117","https://openalex.org/W2081849558","https://openalex.org/W2994878781","https://openalex.org/W2804828343","https://openalex.org/W2792401163","https://openalex.org/W1579973560","https://openalex.org/W2581090841"],"abstract_inverted_index":{"Knowledge":[0],"of":[1,37,79,123,127,129,168,179,191,231,258,264],"motion":[2,29,147],"with":[3,63,209],"respect":[4],"to":[5,113,184,188,203,240,245,250],"the":[6,38,64,77,94,118,124,143,162,189,195,229,256,262,267],"ground":[7,33,65,196],"plane":[8,34,66,101,107,116,197],"is":[9,41,171],"required":[10],"in":[11,117,142],"many":[12],"computer":[13],"vision":[14],"applications":[15],"such":[16,67],"as":[17,30,32,43,68],"obstacle":[18],"avoidance,":[19],"egomotion":[20],"estimation,":[21],"and":[22,70,100,198,243,249,261],"online":[23],"calibration.":[24],"The":[25,165],"homography":[26,39,99],"matrix":[27,40],"comprises":[28],"well":[31,73],"information.":[35],"Estimation":[36],"challenging,":[42],"measurements":[44],"are":[45,61,150,183],"often":[46,105],"not":[47,111],"only":[48],"corrupted":[49],"by":[50,132],"sparse":[51,80],"gross":[52,81],"outliers,":[53],"but":[54],"might":[55],"also":[56],"contain":[57],"other":[58],"structures,":[59],"which":[60],"inconsistent":[62],"curbstones":[69],"sidewalks.":[71],"Several":[72],"studied":[74],"algorithms":[75],"regarding":[76],"identification":[78,136],"outliers":[82,88,104,208],"already":[83],"exist.":[84],"However,":[85],"identifying":[86],"structural":[87,103],"remains":[89],"a":[90,176,192,204,236],"challenging":[91],"problem":[92],"due":[93,187],"outliers'":[95],"inner":[96],"coherence.":[97],"In":[98],"estimation":[102,268],"cause":[106],"fits":[108],"that":[109,134,182],"do":[110],"correspond":[112],"any":[114],"physical":[115],"scene.":[119],"We":[120,254],"make":[121],"use":[122],"large":[125],"field":[126,145],"view":[128],"fisheye":[130],"cameras":[131],"exploiting":[133],"outlier":[135],"can":[137,155],"be":[138,157,185],"performed":[139],"more":[140],"robustly":[141],"near":[144],"where":[146],"parallax":[148,180],"vectors":[149],"large.":[151],"More":[152],"sensitive":[153],"data":[154],"then":[156],"tested":[158],"subsequently":[159],"based":[160],"on":[161,266],"preceding":[163],"results.":[164],"main":[166],"contribution":[167],"this":[169,216],"paper":[170],"twofold.":[172],"First,":[173],"we":[174,214,227],"present":[175],"statistical":[177,205],"analysis":[178],"amplitudes":[181],"expected":[186],"distance":[190],"point":[193],"from":[194],"measurement":[199],"noise.":[200],"This":[201],"leads":[202],"test":[206],"for":[207,223],"local":[210],"adaptive":[211],"thresholds.":[212],"Second,":[213],"embed":[215],"concept":[217],"into":[218,235],"an":[219],"extended":[220],"Kalman":[221],"filter":[222],"efficient":[224],"processing.":[225],"Furthermore,":[226],"emphasize":[228],"importance":[230],"warping":[232],"captured":[233],"images":[234],"common":[237],"frame":[238],"previous":[239],"feature":[241],"detection":[242],"matching":[244],"avoid":[246],"distortion":[247],"effects":[248,263],"equalize":[251],"search":[252],"regions.":[253],"demonstrate":[255],"robustness":[257],"our":[259],"approach":[260],"prewarping":[265],"using":[269],"real":[270],"data.":[271]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2026-01-13T01:12:25.745995","created_date":"2025-10-10T00:00:00"}