{"id":"https://openalex.org/W7167071261","doi":"https://doi.org/10.48550/arxiv.2607.00319","title":"Typography-Based Monocular Distance Estimation for Advanced Driver-Assistance Systems","display_name":"Typography-Based Monocular Distance Estimation for Advanced Driver-Assistance Systems","publication_year":2026,"publication_date":"2026-07-01","ids":{"openalex":"https://openalex.org/W7167071261","doi":"https://doi.org/10.48550/arxiv.2607.00319"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2607.00319","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.00319","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2607.00319","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5107547600","display_name":"Manognya Lokesh Reddy","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Reddy, Manognya Lokesh","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5139908101","display_name":"Zheng Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Zheng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.6398000121116638,"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":0.6398000121116638,"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/T12406","display_name":"IoT and GPS-based Vehicle Safety Systems","score":0.046300001442432404,"subfield":{"id":"https://openalex.org/subfields/2210","display_name":"Mechanical 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/T12707","display_name":"Vehicle License Plate Recognition","score":0.037300001829862595,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/character","display_name":"Character (mathematics)","score":0.6288999915122986},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5166000127792358},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.489300012588501},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.4846000075340271},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4392000138759613},{"id":"https://openalex.org/keywords/distance-transform","display_name":"Distance transform","score":0.37119999527931213},{"id":"https://openalex.org/keywords/distance-measurement","display_name":"Distance measurement","score":0.3544999957084656},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.33649998903274536}],"concepts":[{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6940000057220459},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.692799985408783},{"id":"https://openalex.org/C2780861071","wikidata":"https://www.wikidata.org/wiki/Q1062934","display_name":"Character (mathematics)","level":2,"score":0.6288999915122986},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5166000127792358},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.489300012588501},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.4846000075340271},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4729999899864197},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4392000138759613},{"id":"https://openalex.org/C73621898","wikidata":"https://www.wikidata.org/wiki/Q2940504","display_name":"Distance transform","level":3,"score":0.37119999527931213},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.36329999566078186},{"id":"https://openalex.org/C2986158284","wikidata":"https://www.wikidata.org/wiki/Q6522493","display_name":"Distance measurement","level":2,"score":0.3544999957084656},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.33649998903274536},{"id":"https://openalex.org/C2779304628","wikidata":"https://www.wikidata.org/wiki/Q3503480","display_name":"Face (sociological concept)","level":2,"score":0.3248000144958496},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.3118000030517578},{"id":"https://openalex.org/C2778355321","wikidata":"https://www.wikidata.org/wiki/Q17079427","display_name":"Identity (music)","level":2,"score":0.28139999508857727},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.2808000147342682},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.28029999136924744},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.2687999904155731},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.26339998841285706},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.2612999975681305},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.26100000739097595},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2607.00319","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.00319","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2607.00319","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2607.00319","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Estimating":[0],"the":[1,53,71,98,105,114,127,130,137,142,151,158,161,164,168,173,176,220,232,236,239,283],"distance":[2,26,55,112,149,285],"to":[3,11,140,215,274],"a":[4,8,47,58,78,83,101,108,181,189,206,217,242,244,257,270,278],"leading":[5],"vehicle":[6],"is":[7,61,87,107,117,194],"basic":[9],"input":[10],"forward":[12],"collision":[13],"warning,":[14],"adaptive":[15],"cruise":[16],"control,":[17],"and":[18,40,65,82,91,147,167,180,205,213,246],"automated":[19],"emergency":[20],"braking.":[21],"Production":[22],"systems":[23],"obtain":[24],"this":[25],"from":[27,150,157,249,256,262],"radar,":[28],"laser":[29],"scanners,":[30],"or":[31,191,266],"stereo":[32],"camera":[33,50,115,152],"pairs,":[34],"which":[35],"add":[36],"cost,":[37],"power":[38],"draw,":[39],"packaging":[41],"constraints.":[42],"This":[43],"paper":[44],"asks":[45],"whether":[46],"single":[48],"ordinary":[49],"can":[51],"recover":[52],"same":[54,159,228],"by":[56,89,223],"using":[57],"target":[59],"that":[60,86,188,230],"standardized":[62],"in":[63,104,277],"size":[64,81],"present":[66],"on":[67],"every":[68],"road":[69],"vehicle:":[70],"rear":[72],"license":[73],"plate.":[74],"U.S.":[75,224],"plates":[76],"share":[77],"fixed":[79],"outer":[80],"character":[84,103,145,162,169],"height":[85,99,131],"set":[88],"regulation":[90],"varies":[92],"only":[93],"narrowly":[94],"between":[95],"states,":[96],"so":[97,187,238],"of":[100,111,132,175,203,261,264],"plate":[102,229],"image":[106],"direct":[109],"measure":[110],"once":[113],"geometry":[116],"known.":[118],"The":[119,199,227],"proposed":[120],"method":[121,240],"(Typography-Based":[122],"Monocular":[123],"Distance":[124],"Estimation)":[125],"detects":[126],"plate,":[128],"measures":[129],"its":[133,201],"printed":[134,258],"characters,":[135],"identifies":[136,235],"issuing":[138],"state":[139],"select":[141],"correct":[143],"physical":[144],"height,":[146,163],"recovers":[148],"projection.":[153],"Three":[154],"measurements":[155],"taken":[156],"plate:":[160],"stroke":[165],"width,":[166],"spacing.":[170],"Together":[171],"with":[172,219,287],"spacing":[174],"two":[177],"mounting":[178],"holes":[179],"single-image":[182],"depth":[183],"network,":[184],"are":[185,209],"combined":[186],"weak":[190],"corrupted":[192],"measurement":[193],"given":[195],"less":[196,289],"weight":[197],"automatically.":[198],"distance,":[200,243],"rate":[202],"change,":[204],"time-to-collision":[207],"estimate":[208],"smoothed":[210],"across":[211],"frames":[212],"used":[214,222],"raise":[216],"warning":[218],"timing":[221],"collision-warning":[225],"regulations.":[226],"anchors":[231],"scale":[233,255],"also":[234],"vehicle,":[237],"returns":[241],"bearing,":[245],"an":[247],"identity":[248],"one":[250],"passive":[251],"sensor.":[252],"It":[253],"reads":[254],"standard":[259],"instead":[260],"time":[263],"flight":[265],"parallax,":[267],"making":[268],"it":[269],"cheap,":[271],"low-maintenance":[272],"complement":[273],"those":[275],"sensors":[276],"fault-tolerant":[279],"perception":[280],"stack,":[281],"achieving":[282],"cost-effective":[284],"estimation":[286],"error":[288],"than":[290],"0.13":[291],"m.":[292]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-07-03T00:00:00"}
