{"id":"https://openalex.org/W7128633443","doi":"https://doi.org/10.1109/icves65691.2025.11376043","title":"Validating Camera Sensor Models for Virtual Testing of Vision Systems in Automated Driving","display_name":"Validating Camera Sensor Models for Virtual Testing of Vision Systems in Automated Driving","publication_year":2025,"publication_date":"2025-10-27","ids":{"openalex":"https://openalex.org/W7128633443","doi":"https://doi.org/10.1109/icves65691.2025.11376043"},"language":null,"primary_location":{"id":"doi:10.1109/icves65691.2025.11376043","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icves65691.2025.11376043","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","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/A5092678765","display_name":"Fabian Ulreich","orcid":"https://orcid.org/0009-0009-9664-4188"},"institutions":[{"id":"https://openalex.org/I4210106192","display_name":"Technische Hochschule Ingolstadt","ror":"https://ror.org/02bxzcy64","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210106192"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Fabian Ulreich","raw_affiliation_strings":["Technische Hochschule Ingolstadt,CARISSMA Institute of Automated Driving,Ingolstadt,Germany"],"affiliations":[{"raw_affiliation_string":"Technische Hochschule Ingolstadt,CARISSMA Institute of Automated Driving,Ingolstadt,Germany","institution_ids":["https://openalex.org/I4210106192"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081006630","display_name":"Maikol Funk Drechsler","orcid":"https://orcid.org/0000-0002-7360-7829"},"institutions":[{"id":"https://openalex.org/I4210106192","display_name":"Technische Hochschule Ingolstadt","ror":"https://ror.org/02bxzcy64","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210106192"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Maikol Funk Drechsler","raw_affiliation_strings":["Technische Hochschule Ingolstadt,CARISSMA Institute of Automated Driving,Ingolstadt,Germany"],"affiliations":[{"raw_affiliation_string":"Technische Hochschule Ingolstadt,CARISSMA Institute of Automated Driving,Ingolstadt,Germany","institution_ids":["https://openalex.org/I4210106192"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5050295918","display_name":"Yuri Poledna","orcid":"https://orcid.org/0000-0002-9816-9474"},"institutions":[{"id":"https://openalex.org/I4210106192","display_name":"Technische Hochschule Ingolstadt","ror":"https://ror.org/02bxzcy64","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210106192"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Yuri Poledna","raw_affiliation_strings":["Technische Hochschule Ingolstadt,CARISSMA Institute of Automated Driving,Ingolstadt,Germany"],"affiliations":[{"raw_affiliation_string":"Technische Hochschule Ingolstadt,CARISSMA Institute of Automated Driving,Ingolstadt,Germany","institution_ids":["https://openalex.org/I4210106192"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5071151548","display_name":"Pak Hung Chan","orcid":"https://orcid.org/0000-0003-1705-5430"},"institutions":[{"id":"https://openalex.org/I166337079","display_name":"Queen Mary University of London","ror":"https://ror.org/026zzn846","country_code":"GB","type":"education","lineage":["https://openalex.org/I124357947","https://openalex.org/I166337079"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Pak Hung Chan","raw_affiliation_strings":["Queen Mary University of London,SPRING: Sensing and Perception for Intelligent Systems Group,London,United Kingdom"],"affiliations":[{"raw_affiliation_string":"Queen Mary University of London,SPRING: Sensing and Perception for Intelligent Systems Group,London,United Kingdom","institution_ids":["https://openalex.org/I166337079"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125646176","display_name":"Tuomas Herraren","orcid":null},"institutions":[{"id":"https://openalex.org/I3131107225","display_name":"Lapland University of Applied Sciences","ror":"https://ror.org/047h64h89","country_code":"FI","type":"education","lineage":["https://openalex.org/I3131107225"]},{"id":"https://openalex.org/I95220073","display_name":"University of Lapland","ror":"https://ror.org/05jzt8766","country_code":"FI","type":"education","lineage":["https://openalex.org/I95220073"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Tuomas Herranen","raw_affiliation_strings":["Lapland University of Applied Sciences,Finland"],"affiliations":[{"raw_affiliation_string":"Lapland University of Applied Sciences,Finland","institution_ids":["https://openalex.org/I95220073","https://openalex.org/I3131107225"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101808600","display_name":"Martin Ebert","orcid":"https://orcid.org/0000-0001-8811-1335"},"institutions":[{"id":"https://openalex.org/I4210106192","display_name":"Technische Hochschule Ingolstadt","ror":"https://ror.org/02bxzcy64","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210106192"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Martin Ebert","raw_affiliation_strings":["Technische Hochschule Ingolstadt,CARISSMA Institute of Automated Driving,Ingolstadt,Germany"],"affiliations":[{"raw_affiliation_string":"Technische Hochschule Ingolstadt,CARISSMA Institute of Automated Driving,Ingolstadt,Germany","institution_ids":["https://openalex.org/I4210106192"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062850220","display_name":"Andr\u00e9 Kaup","orcid":"https://orcid.org/0000-0002-0929-5074"},"institutions":[{"id":"https://openalex.org/I181369854","display_name":"Friedrich-Alexander-Universit\u00e4t Erlangen-N\u00fcrnberg","ror":"https://ror.org/00f7hpc57","country_code":"DE","type":"education","lineage":["https://openalex.org/I181369854"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Andr\u00e9 Kaup","raw_affiliation_strings":["Friedrich-Alexander-Universität Erlangen-Nürnberg,Chair of Multimedia Communications and Signal Processing,Erlangen,Germany"],"affiliations":[{"raw_affiliation_string":"Friedrich-Alexander-Universität Erlangen-Nürnberg,Chair of Multimedia Communications and Signal Processing,Erlangen,Germany","institution_ids":["https://openalex.org/I181369854"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5125648641","display_name":"Werner Huber","orcid":null},"institutions":[{"id":"https://openalex.org/I4210106192","display_name":"Technische Hochschule Ingolstadt","ror":"https://ror.org/02bxzcy64","country_code":"DE","type":"education","lineage":["https://openalex.org/I4210106192"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Werner Huber","raw_affiliation_strings":["Technische Hochschule Ingolstadt,CARISSMA Institute of Automated Driving,Ingolstadt,Germany"],"affiliations":[{"raw_affiliation_string":"Technische Hochschule Ingolstadt,CARISSMA Institute of Automated Driving,Ingolstadt,Germany","institution_ids":["https://openalex.org/I4210106192"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5092678765"],"corresponding_institution_ids":["https://openalex.org/I4210106192"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.60768088,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"57","last_page":"64"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.2484000027179718,"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":0.2484000027179718,"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/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.15600000321865082,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.14090000092983246,"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-neural-network","display_name":"Artificial neural network","score":0.48089998960494995},{"id":"https://openalex.org/keywords/machine-vision","display_name":"Machine vision","score":0.38510000705718994},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.34459999203681946},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.33379998803138733},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.3183000087738037},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.31709998846054077},{"id":"https://openalex.org/keywords/image-sensor","display_name":"Image sensor","score":0.31540000438690186},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.30979999899864197}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6546000242233276},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6510000228881836},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5921000242233276},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.48089998960494995},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.38510000705718994},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.34459999203681946},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.33379998803138733},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.3183000087738037},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.31709998846054077},{"id":"https://openalex.org/C76935873","wikidata":"https://www.wikidata.org/wiki/Q209121","display_name":"Image sensor","level":2,"score":0.31540000438690186},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.30979999899864197},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.29750001430511475},{"id":"https://openalex.org/C42781572","wikidata":"https://www.wikidata.org/wiki/Q1250322","display_name":"Digital image","level":4,"score":0.29339998960494995},{"id":"https://openalex.org/C104122410","wikidata":"https://www.wikidata.org/wiki/Q1416406","display_name":"Network model","level":2,"score":0.29179999232292175},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.2904999852180481},{"id":"https://openalex.org/C115051666","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Ranging","level":2,"score":0.28119999170303345},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2809000015258789},{"id":"https://openalex.org/C112416745","wikidata":"https://www.wikidata.org/wiki/Q974213","display_name":"Digital imaging","level":5,"score":0.27480000257492065},{"id":"https://openalex.org/C2779705975","wikidata":"https://www.wikidata.org/wiki/Q62927","display_name":"Digital camera","level":2,"score":0.2741999924182892},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.2630999982357025},{"id":"https://openalex.org/C74763872","wikidata":"https://www.wikidata.org/wiki/Q5276157","display_name":"Digital sensors","level":2,"score":0.2540000081062317},{"id":"https://openalex.org/C87833898","wikidata":"https://www.wikidata.org/wiki/Q1060280","display_name":"Advanced driver assistance systems","level":2,"score":0.25029999017715454}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icves65691.2025.11376043","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icves65691.2025.11376043","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE International Conference on Vehicular Electronics and Safety (ICVES)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2015159529","https://openalex.org/W2125188427","https://openalex.org/W2136035751","https://openalex.org/W2891298711","https://openalex.org/W2999880676","https://openalex.org/W3120403167","https://openalex.org/W4280571816","https://openalex.org/W4286285636","https://openalex.org/W4309030581","https://openalex.org/W4313339049","https://openalex.org/W4386089856","https://openalex.org/W4386608621","https://openalex.org/W4387019149","https://openalex.org/W4391768416","https://openalex.org/W4400647293","https://openalex.org/W4404315742","https://openalex.org/W4406522105","https://openalex.org/W4407900266","https://openalex.org/W4408699727","https://openalex.org/W4409069880"],"related_works":[],"abstract_inverted_index":{"Vision":[0],"systems":[1],"in":[2,33,98,146,211],"automated":[3,215],"driving":[4,85,216],"deliver":[5],"information":[6],"on":[7,57],"which":[8,41],"subsequent":[9],"processing":[10],"stages":[11],"rely":[12],"to":[13,27,63,92,181,192,196],"perform":[14],"safety-critical":[15],"decisions.":[16],"With":[17],"the":[18,29,44,48,93,102,105,118,121,130,135,143,149,152,160,164,187,197,201,208],"application":[19],"of":[20,43,83,120,148,166,214],"deep-learning":[21],"models,":[22],"more":[23],"effort":[24],"is":[25,38,90],"needed":[26],"validate":[28],"sensor":[30,96],"models":[31],"used":[32,124],"virtual":[34],"environments,":[35],"as":[36],"it":[37],"not":[39],"known":[40],"features":[42],"image":[45],"data":[46],"affect":[47],"prediction.":[49],"This":[50],"work":[51,111],"proposes":[52,112],"a":[53,58,69,84,167,172],"validation":[54],"method":[55],"based":[56],"standardized":[59],"image-quality":[60],"target":[61,175],"according":[62],"ISO12233:2023":[64],"and":[65,79,100,104,138,200],"ISO14524,":[66],"together":[67],"with":[68,129],"high-precision":[70],"geometrical":[71],"digital":[72],"twin":[73],"for":[74],"direct":[75],"comparison":[76],"between":[77],"real":[78,122,202],"simulated":[80],"images":[81],"taken":[82],"scenario.":[86],"The":[87,183],"proposed":[88,131,198],"approach":[89],"applied":[91],"default":[94,144,188],"camera":[95,123],"model":[97,115,133,145,190,199,210],"CARLA":[99],"targets":[101],"geometric":[103],"radiometric":[106],"parts":[107],"separately.":[108],"Thereby,":[109],"this":[110],"an":[113,155],"enhanced":[114,209],"that":[116,186],"fits":[117],"characteristics":[119],"during":[125],"experiments.":[126],"Images":[127],"generated":[128],"simulation":[132,189],"reduce":[134],"sim-to-real":[136],"gap":[137],"are":[139],"112.73%":[140],"better":[141],"than":[142],"terms":[147],"Michelson-contrast.":[150],"Evaluating":[151],"OECF-curves":[153],"yields":[154],"85.16%":[156],"improvement.":[157],"To":[158],"demonstrate":[159],"applicability,":[161],"we":[162,205],"assess":[163],"performance":[165],"deep":[168],"neural":[169],"network":[170],"detecting":[171],"EuroNCAP":[173],"pedestrian":[174],"at":[176],"distances":[177],"ranging":[178],"from":[179],"5m":[180],"100m.":[182],"results":[184],"show":[185],"leads":[191],"overconfident":[193],"predictions":[194],"compared":[195],"camera.":[203],"Furthermore,":[204],"will":[206],"use":[207],"X-in-the-Loop":[212],"tests":[213],"systems.":[217]},"counts_by_year":[],"updated_date":"2026-04-02T13:48:15.688549","created_date":"2026-02-12T00:00:00"}