{"id":"https://openalex.org/W2399453552","doi":"https://doi.org/10.1109/icassp.2016.7472200","title":"Autocalibration of lidar and optical cameras via edge alignment","display_name":"Autocalibration of lidar and optical cameras via edge alignment","publication_year":2016,"publication_date":"2016-03-01","ids":{"openalex":"https://openalex.org/W2399453552","doi":"https://doi.org/10.1109/icassp.2016.7472200","mag":"2399453552"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2016.7472200","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7472200","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5053027276","display_name":"Juan Castorena","orcid":"https://orcid.org/0000-0003-2617-5178"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]},{"id":"https://openalex.org/I10052268","display_name":"New Mexico State University","ror":"https://ror.org/00hpz7z43","country_code":"US","type":"education","lineage":["https://openalex.org/I10052268"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Juan Castorena","raw_affiliation_strings":["New Mexico State University, Mitsubishi Electric Research Laboratories, Las Cruces, NM"],"affiliations":[{"raw_affiliation_string":"New Mexico State University, Mitsubishi Electric Research Laboratories, Las Cruces, NM","institution_ids":["https://openalex.org/I4210159266","https://openalex.org/I10052268"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024602237","display_name":"Ulugbek S. Kamilov","orcid":"https://orcid.org/0000-0001-6770-3278"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ulugbek S. Kamilov","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories, MA"],"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories, MA","institution_ids":["https://openalex.org/I4210159266"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034522188","display_name":"Petros T. Boufounos","orcid":"https://orcid.org/0000-0003-1369-0947"},"institutions":[{"id":"https://openalex.org/I4210159266","display_name":"Mitsubishi Electric (United States)","ror":"https://ror.org/053jnhe44","country_code":"US","type":"company","lineage":["https://openalex.org/I1306287861","https://openalex.org/I4210133125","https://openalex.org/I4210159266"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Petros T. Boufounos","raw_affiliation_strings":["Mitsubishi Electric Research Laboratories, MA"],"affiliations":[{"raw_affiliation_string":"Mitsubishi Electric Research Laboratories, MA","institution_ids":["https://openalex.org/I4210159266"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5053027276"],"corresponding_institution_ids":["https://openalex.org/I10052268","https://openalex.org/I4210159266"],"apc_list":null,"apc_paid":null,"fwci":5.5872,"has_fulltext":false,"cited_by_count":100,"citation_normalized_percentile":{"value":0.97417005,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"2862","last_page":"2866"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10638","display_name":"Optical measurement and interference techniques","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/T10638","display_name":"Optical measurement and interference techniques","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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9987000226974487,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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":0.9984999895095825,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7690670490264893},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.7670342326164246},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.7669452428817749},{"id":"https://openalex.org/keywords/fuse","display_name":"Fuse (electrical)","score":0.762810230255127},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7194900512695312},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6927670240402222},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5091533064842224},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.5041664838790894},{"id":"https://openalex.org/keywords/joint","display_name":"Joint (building)","score":0.4933561384677887},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4802042245864868},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.46568217873573303},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.44228124618530273},{"id":"https://openalex.org/keywords/contrast","display_name":"Contrast (vision)","score":0.42942166328430176},{"id":"https://openalex.org/keywords/image-sensor","display_name":"Image sensor","score":0.4293317198753357},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.347980797290802},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13439321517944336},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.093045175075531},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.06866979598999023}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7690670490264893},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.7670342326164246},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.7669452428817749},{"id":"https://openalex.org/C141353440","wikidata":"https://www.wikidata.org/wiki/Q182221","display_name":"Fuse (electrical)","level":2,"score":0.762810230255127},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7194900512695312},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6927670240402222},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5091533064842224},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.5041664838790894},{"id":"https://openalex.org/C18555067","wikidata":"https://www.wikidata.org/wiki/Q8375051","display_name":"Joint (building)","level":2,"score":0.4933561384677887},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4802042245864868},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.46568217873573303},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.44228124618530273},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.42942166328430176},{"id":"https://openalex.org/C76935873","wikidata":"https://www.wikidata.org/wiki/Q209121","display_name":"Image sensor","level":2,"score":0.4293317198753357},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.347980797290802},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13439321517944336},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.093045175075531},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.06866979598999023},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2016.7472200","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2016.7472200","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":27,"referenced_works":["https://openalex.org/W133970677","https://openalex.org/W1553625947","https://openalex.org/W1971918169","https://openalex.org/W2051573176","https://openalex.org/W2058560716","https://openalex.org/W2064684591","https://openalex.org/W2099712288","https://openalex.org/W2103559027","https://openalex.org/W2104620097","https://openalex.org/W2106182574","https://openalex.org/W2111365302","https://openalex.org/W2111394763","https://openalex.org/W2115579991","https://openalex.org/W2118273112","https://openalex.org/W2134019518","https://openalex.org/W2138646635","https://openalex.org/W2142224912","https://openalex.org/W2153388956","https://openalex.org/W2156257921","https://openalex.org/W2159957588","https://openalex.org/W2166988749","https://openalex.org/W2295149141","https://openalex.org/W2587111463","https://openalex.org/W6666475387","https://openalex.org/W6676399903","https://openalex.org/W6684802601","https://openalex.org/W6884869577"],"related_works":["https://openalex.org/W4319317934","https://openalex.org/W2901265155","https://openalex.org/W2956374172","https://openalex.org/W3000097931","https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W4390606538","https://openalex.org/W2095903272","https://openalex.org/W3214791684","https://openalex.org/W2152662039"],"abstract_inverted_index":{"We":[0,131],"present":[1],"a":[2,14,19,46,124,157],"new":[3],"method":[4],"for":[5,13],"joint":[6,105],"automatic":[7],"extrinsic":[8],"calibration":[9,38,100,134],"and":[10,21,33,77,97,108,116,144,152],"sensor":[11,16,71,160],"fusion":[12,121],"multimodal":[15],"system":[17],"comprising":[18],"LIDAR":[20,159],"an":[22],"optical":[23],"camera.":[24],"Our":[25],"approach":[26],"exploits":[27],"the":[28,37,55,64,67,95,99,104,111,117,120,129,162],"natural":[29],"alignment":[30,61,86,115],"of":[31,48,59,69,113,119,164],"depth":[32,140],"intensity":[34],"edges":[35],"when":[36],"parameters":[39],"are":[40,80,142],"correct.":[41],"Thus,":[42],"in":[43,135,138],"contrast":[44],"to":[45],"number":[47],"existing":[49],"approaches,":[50],"we":[51,92],"do":[52],"not":[53],"require":[54],"presence":[56],"or":[57],"identification":[58],"known":[60],"targets.":[62],"On":[63],"other":[65],"hand,":[66],"characteristics":[68],"each":[70],"modality,":[72],"such":[73],"as":[74],"sampling":[75],"pattern":[76],"information":[78],"measured,":[79],"significantly":[81],"different,":[82],"making":[83],"direct":[84],"edge":[85,114],"difficult.":[87],"To":[88],"overcome":[89],"this":[90],"difficulty,":[91],"jointly":[93],"fuse":[94],"data":[96,154],"estimate":[98],"parameters.":[101],"In":[102],"particular,":[103],"processing":[106],"evaluates":[107],"optimizes":[109],"both":[110],"quality":[112],"performance":[118],"algorithm":[122],"using":[123],"common":[125],"cost":[126],"function":[127],"on":[128,150],"output.":[130],"demonstrate":[132,161],"accurate":[133],"practical":[136],"configurations":[137],"which":[139],"measurements":[141],"sparse":[143],"contain":[145],"no":[146],"reflectivity":[147],"information.":[148],"Experiments":[149],"synthetic":[151],"real":[153],"obtained":[155],"with":[156],"three-dimensional":[158],"effectiveness":[163],"our":[165],"approach.":[166]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":9},{"year":2020,"cited_by_count":13},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":12},{"year":2017,"cited_by_count":10},{"year":2016,"cited_by_count":3}],"updated_date":"2026-03-13T16:22:10.518609","created_date":"2025-10-10T00:00:00"}
