{"id":"https://openalex.org/W2112473817","doi":"https://doi.org/10.1109/ivs.2011.5940426","title":"Development and evaluation of a performance metric for image-based driver assistance systems","display_name":"Development and evaluation of a performance metric for image-based driver assistance systems","publication_year":2011,"publication_date":"2011-06-01","ids":{"openalex":"https://openalex.org/W2112473817","doi":"https://doi.org/10.1109/ivs.2011.5940426","mag":"2112473817"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2011.5940426","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2011.5940426","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE Intelligent Vehicles Symposium (IV)","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/A5110733976","display_name":"Kip Smith","orcid":null},"institutions":[{"id":"https://openalex.org/I102134673","display_name":"Link\u00f6ping University","ror":"https://ror.org/05ynxx418","country_code":"SE","type":"education","lineage":["https://openalex.org/I102134673"]}],"countries":["SE"],"is_corresponding":false,"raw_author_name":"Kip Smith","raw_affiliation_strings":["Cognitive Systems Engineering, Link\u00f6ping University, Sweden","Cognitive Engineering and Decision Making, Inc., Des Moines, WA 98198 USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Cognitive Systems Engineering, Link\u00f6ping University, Sweden","institution_ids":["https://openalex.org/I102134673"]},{"raw_affiliation_string":"Cognitive Engineering and Decision Making, Inc., Des Moines, WA 98198 USA","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109978166","display_name":"Roland Schweiger","orcid":null},"institutions":[{"id":"https://openalex.org/I891521709","display_name":"Daimler (Germany)","ror":"https://ror.org/00m0j3d84","country_code":"DE","type":"company","lineage":["https://openalex.org/I891521709"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Roland Schweiger","raw_affiliation_strings":["Research and Development, Daimler Benz Aerospace, Ulm, Germany","Daimler AG, Research and Development, Ulm, Germany#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research and Development, Daimler Benz Aerospace, Ulm, Germany","institution_ids":["https://openalex.org/I891521709"]},{"raw_affiliation_string":"Daimler AG, Research and Development, Ulm, Germany#TAB#","institution_ids":["https://openalex.org/I891521709"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103937735","display_name":"Werner Ritter","orcid":null},"institutions":[{"id":"https://openalex.org/I891521709","display_name":"Daimler (Germany)","ror":"https://ror.org/00m0j3d84","country_code":"DE","type":"company","lineage":["https://openalex.org/I891521709"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Werner Ritter","raw_affiliation_strings":["Research and Development, Daimler Benz Aerospace, Ulm, Germany","Daimler AG, Research and Development, Ulm, Germany#TAB#"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Research and Development, Daimler Benz Aerospace, Ulm, Germany","institution_ids":["https://openalex.org/I891521709"]},{"raw_affiliation_string":"Daimler AG, Research and Development, Ulm, Germany#TAB#","institution_ids":["https://openalex.org/I891521709"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032261257","display_name":"Jan-Erik K\u00e4llhammer","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jan-Erik Kallhammer","raw_affiliation_strings":["Autoliv Development, Vargarda, Sweden"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Autoliv Development, Vargarda, Sweden","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.5898,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.89481526,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"381","last_page":"386"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10525","display_name":"Human-Automation Interaction and Safety","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10525","display_name":"Human-Automation Interaction and Safety","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11963","display_name":"Impact of Light on Environment and Health","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/T10370","display_name":"Traffic and Road Safety","score":0.995199978351593,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/metric","display_name":"Metric (unit)","score":0.8596190214157104},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.7502394914627075},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6800746917724609},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.6105550527572632},{"id":"https://openalex.org/keywords/performance-metric","display_name":"Performance metric","score":0.5320642590522766},{"id":"https://openalex.org/keywords/strengths-and-weaknesses","display_name":"Strengths and weaknesses","score":0.5274432301521301},{"id":"https://openalex.org/keywords/metric-system","display_name":"Metric system","score":0.4947776198387146},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.45856961607933044},{"id":"https://openalex.org/keywords/night-vision","display_name":"Night vision","score":0.43975040316581726},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4220014214515686},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.41547542810440063},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40302157402038574},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3830646276473999},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.32182204723358154},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.17496508359909058}],"concepts":[{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.8596190214157104},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.7502394914627075},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6800746917724609},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.6105550527572632},{"id":"https://openalex.org/C2780898871","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Performance metric","level":2,"score":0.5320642590522766},{"id":"https://openalex.org/C63882131","wikidata":"https://www.wikidata.org/wiki/Q17122954","display_name":"Strengths and weaknesses","level":2,"score":0.5274432301521301},{"id":"https://openalex.org/C193429382","wikidata":"https://www.wikidata.org/wiki/Q232405","display_name":"Metric system","level":2,"score":0.4947776198387146},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.45856961607933044},{"id":"https://openalex.org/C2983470273","wikidata":"https://www.wikidata.org/wiki/Q5353651","display_name":"Night vision","level":2,"score":0.43975040316581726},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4220014214515686},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.41547542810440063},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40302157402038574},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3830646276473999},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.32182204723358154},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.17496508359909058},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","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/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivs.2011.5940426","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2011.5940426","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE Intelligent Vehicles Symposium (IV)","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":6,"referenced_works":["https://openalex.org/W192251287","https://openalex.org/W1574137424","https://openalex.org/W2056535917","https://openalex.org/W2117744191","https://openalex.org/W2125945488","https://openalex.org/W4299513681"],"related_works":["https://openalex.org/W2624903463","https://openalex.org/W3207051105","https://openalex.org/W2093384100","https://openalex.org/W4295532600","https://openalex.org/W2063823869","https://openalex.org/W4386960967","https://openalex.org/W2047973478","https://openalex.org/W2213018794","https://openalex.org/W2096892199","https://openalex.org/W3132158019"],"abstract_inverted_index":{"This":[0,166],"report":[1],"describes":[2],"the":[3,14,27,32,36,89,99,105,117,123,126,132,147,160,169,172,189],"formulation":[4],"and":[5,16,52,56,61,69,72,94,121,139,150,206],"application":[6],"of":[7,18,35,49,67,102,114,131,191,217],"a":[8,135,140],"performance":[9,34,201],"metric":[10,28,87,109,133,173],"designed":[11],"to":[12,30,158,164,196,203,207],"assist":[13],"design":[15],"development":[17,190],"automotive":[19],"active":[20],"safety":[21],"systems.":[22,45],"The":[23,46,108,129,154],"impetus":[24],"for":[25,78,178],"developing":[26],"was":[29,156],"calibrate":[31],"relative":[33],"pedestrian":[37],"detection":[38],"algorithms":[39],"used":[40,187],"by":[41,162,211],"infrared":[42,54],"(IR)":[43],"night-vision":[44],"two":[47],"types":[48],"system,":[50],"far-":[51],"near-":[53],"(FIR":[55],"NIR),":[57],"have":[58],"complementary":[59,182],"strengths":[60],"weaknesses":[62],"that":[63,143,171],"produce":[64],"different":[65],"sets":[66],"misses":[68],"false":[70],"alarms":[71],"reveal":[73],"limitations":[74],"in":[75,104,125,188,199],"traditional":[76],"methods":[77],"comparing":[79],"their":[80],"performance.":[81],"To":[82],"overcome":[83],"these":[84],"limitations,":[85],"our":[86],"quantifies":[88],"similarity":[90],"between":[91],"system":[92,118,138,142,149,200,204],"output":[93],"it":[95],"ground":[96,127],"truth":[97],"-":[98],"actual":[100],"locations":[101],"pedestrians":[103],"IR":[106],"image.":[107],"reaches":[110],"its":[111],"maximum":[112],"value":[113],"1.0":[115],"when":[116],"highlights":[119],"all":[120],"only":[122],"elements":[124],"truth.":[128],"evaluation":[130],"compared":[134],"benchmark":[136,161],"FIR":[137,148],"prototype":[141,155],"fuses":[144],"inputs":[145],"from":[146],"an":[151,175],"NIR":[152],"system.":[153],"found":[157],"outperform":[159],"10":[163],"26%.":[165],"finding":[167],"supports":[168],"contentions":[170],"provides":[174],"effective":[176],"means":[177],"assessing":[179],"systems":[180,195],"with":[181],"strengths.":[183],"It":[184],"can":[185],"be":[186],"image-based":[192],"driver":[193],"assistance":[194],"assess":[197],"changes":[198],"due":[202],"modifications":[205],"evaluate":[208],"large":[209],"databases":[210],"highlighting":[212],"situations":[213],"or":[214],"events":[215],"worthy":[216],"developers'":[218],"scrutiny.":[219]},"counts_by_year":[{"year":2019,"cited_by_count":1},{"year":2015,"cited_by_count":2},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
