{"id":"https://openalex.org/W2769477812","doi":"https://doi.org/10.1109/iccp.2017.8117016","title":"Automatic extrinsic camera parameters calibration using convolutional neural networks","display_name":"Automatic extrinsic camera parameters calibration using convolutional neural networks","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2769477812","doi":"https://doi.org/10.1109/iccp.2017.8117016","mag":"2769477812"},"language":"en","primary_location":{"id":"doi:10.1109/iccp.2017.8117016","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccp.2017.8117016","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 13th IEEE International Conference on Intelligent Computer Communication and Processing (ICCP)","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/A5078073621","display_name":"Razvan Itu","orcid":"https://orcid.org/0000-0001-8156-7313"},"institutions":[{"id":"https://openalex.org/I158333966","display_name":"Technical University of Cluj-Napoca","ror":"https://ror.org/03r8nwp71","country_code":"RO","type":"education","lineage":["https://openalex.org/I158333966"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Razvan Itu","raw_affiliation_strings":["Computer Science Department, Technical University of Cluj-Napoca, Cluj-Napoca, Romania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, Technical University of Cluj-Napoca, Cluj-Napoca, Romania","institution_ids":["https://openalex.org/I158333966"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5099785516","display_name":"Diana Laura Borza","orcid":"https://orcid.org/0000-0002-0276-7243"},"institutions":[{"id":"https://openalex.org/I158333966","display_name":"Technical University of Cluj-Napoca","ror":"https://ror.org/03r8nwp71","country_code":"RO","type":"education","lineage":["https://openalex.org/I158333966"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Diana Borza","raw_affiliation_strings":["Computer Science Department, Technical University of Cluj-Napoca, Cluj-Napoca, Romania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, Technical University of Cluj-Napoca, Cluj-Napoca, Romania","institution_ids":["https://openalex.org/I158333966"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5014747694","display_name":"Radu D\u0103nescu","orcid":"https://orcid.org/0000-0002-4515-8114"},"institutions":[{"id":"https://openalex.org/I158333966","display_name":"Technical University of Cluj-Napoca","ror":"https://ror.org/03r8nwp71","country_code":"RO","type":"education","lineage":["https://openalex.org/I158333966"]}],"countries":["RO"],"is_corresponding":false,"raw_author_name":"Radu Danescu","raw_affiliation_strings":["Computer Science Department, Technical University of Cluj-Napoca, Cluj-Napoca, Romania"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Science Department, Technical University of Cluj-Napoca, Cluj-Napoca, Romania","institution_ids":["https://openalex.org/I158333966"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I158333966"],"apc_list":null,"apc_paid":null,"fwci":1.2497,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.83174781,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"273","last_page":"278"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.9955999851226807,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/T10531","display_name":"Advanced Vision and Imaging","score":0.9954000115394592,"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/artificial-intelligence","display_name":"Artificial intelligence","score":0.802053689956665},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7791166305541992},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7607232332229614},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.7468807101249695},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7400729060173035},{"id":"https://openalex.org/keywords/vanishing-point","display_name":"Vanishing point","score":0.6945687532424927},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.6158414483070374},{"id":"https://openalex.org/keywords/camera-resectioning","display_name":"Camera resectioning","score":0.6066634654998779},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5974737405776978},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.5937824845314026},{"id":"https://openalex.org/keywords/camera-auto-calibration","display_name":"Camera auto-calibration","score":0.46208426356315613},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3791859745979309},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32419365644454956},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10117793083190918}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.802053689956665},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7791166305541992},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7607232332229614},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.7468807101249695},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7400729060173035},{"id":"https://openalex.org/C99404194","wikidata":"https://www.wikidata.org/wiki/Q163362","display_name":"Vanishing point","level":3,"score":0.6945687532424927},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.6158414483070374},{"id":"https://openalex.org/C110898773","wikidata":"https://www.wikidata.org/wiki/Q2933935","display_name":"Camera resectioning","level":2,"score":0.6066634654998779},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5974737405776978},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.5937824845314026},{"id":"https://openalex.org/C94816000","wikidata":"https://www.wikidata.org/wiki/Q5026006","display_name":"Camera auto-calibration","level":3,"score":0.46208426356315613},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3791859745979309},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32419365644454956},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10117793083190918},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0},{"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/iccp.2017.8117016","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccp.2017.8117016","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 13th IEEE International Conference on Intelligent Computer Communication and Processing (ICCP)","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":0.5799999833106995}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W33116912","https://openalex.org/W1522301498","https://openalex.org/W1598729455","https://openalex.org/W1910657905","https://openalex.org/W1994870715","https://openalex.org/W2115448105","https://openalex.org/W2126738871","https://openalex.org/W2163605009","https://openalex.org/W2342840547","https://openalex.org/W2465994171","https://openalex.org/W2536640360","https://openalex.org/W2963881378","https://openalex.org/W2964121744","https://openalex.org/W6601344910","https://openalex.org/W6631190155","https://openalex.org/W6635898517","https://openalex.org/W6676990836","https://openalex.org/W6684191040"],"related_works":["https://openalex.org/W2393869535","https://openalex.org/W2049337725","https://openalex.org/W2379465014","https://openalex.org/W2371509765","https://openalex.org/W9483417","https://openalex.org/W2107622275","https://openalex.org/W2540763125","https://openalex.org/W2370621620","https://openalex.org/W2110206196","https://openalex.org/W2060286486"],"abstract_inverted_index":{"Camera":[0],"calibration":[1,10],"is":[2,15,21,78],"essential":[3],"for":[4,66],"accurate":[5],"computer":[6],"vision,":[7],"and":[8,29,95,101],"automatic":[9],"of":[11,51,132],"some":[12],"extrinsic":[13],"parameters":[14],"needed":[16],"in":[17,72,128],"case":[18],"the":[19,34,41,48,52,68,122,125,133],"camera":[20],"placed":[22],"on":[23,113],"a":[24,89],"mobile":[25],"platform.":[26],"The":[27,76,99,108],"pitch":[28],"yaw":[30],"angles,":[31],"which":[32,83],"are":[33,84,104],"most":[35],"likely":[36],"ones":[37],"to":[38],"change":[39],"as":[40],"vehicle":[42],"moves,":[43],"can":[44],"be":[45],"inferred":[46],"from":[47],"image":[49],"coordinates":[50],"vanishing":[53,69,91],"point":[54,70,92],"(VP).":[55],"In":[56],"this":[57],"paper":[58],"we":[59],"present":[60],"an":[61],"artificial":[62],"neural":[63],"network":[64,77,110],"approach":[65],"detecting":[67],"position":[71],"road":[73],"traffic":[74],"scenarios.":[75],"trained":[79,109],"using":[80,88],"2500":[81],"images":[82,117],"first":[85],"automatically":[86],"annotated":[87],"classical":[90],"detection":[93],"algorithm,":[94],"then":[96],"manually":[97],"validated.":[98],"training":[100],"test":[102],"datasets":[103],"made":[105],"publicly":[106],"available.":[107],"was":[111],"tested":[112],"more":[114,129],"than":[115,130],"250":[116],"not":[118],"previously":[119],"seen":[120],"by":[121],"network,":[123],"locating":[124],"VP":[126],"accurately":[127],"90%":[131],"cases.":[134]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":2}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}