{"id":"https://openalex.org/W3214451692","doi":"https://doi.org/10.1109/mfi52462.2021.9591203","title":"SemCal: Semantic LiDAR-Camera Calibration using Neural Mutual Information Estimator","display_name":"SemCal: Semantic LiDAR-Camera Calibration using Neural Mutual Information Estimator","publication_year":2021,"publication_date":"2021-09-23","ids":{"openalex":"https://openalex.org/W3214451692","doi":"https://doi.org/10.1109/mfi52462.2021.9591203","mag":"3214451692"},"language":"en","primary_location":{"id":"doi:10.1109/mfi52462.2021.9591203","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mfi52462.2021.9591203","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)","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/A5100722002","display_name":"Peng Jiang","orcid":"https://orcid.org/0000-0002-8349-1743"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Peng Jiang","raw_affiliation_strings":["Texas A&M University, TX, USA"],"affiliations":[{"raw_affiliation_string":"Texas A&M University, TX, USA","institution_ids":["https://openalex.org/I91045830"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073742006","display_name":"Philip R. Osteen","orcid":"https://orcid.org/0000-0001-8266-9848"},"institutions":[{"id":"https://openalex.org/I2802705668","display_name":"United States Army Combat Capabilities Development Command","ror":"https://ror.org/02rdkx920","country_code":"US","type":"other","lineage":["https://openalex.org/I1304082316","https://openalex.org/I1330347796","https://openalex.org/I2802705668","https://openalex.org/I4210154437"]},{"id":"https://openalex.org/I166416128","display_name":"DEVCOM Army Research Laboratory","ror":"https://ror.org/011hc8f90","country_code":"US","type":"government","lineage":["https://openalex.org/I1304082316","https://openalex.org/I1330347796","https://openalex.org/I166416128","https://openalex.org/I2802705668","https://openalex.org/I4210154437"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Philip Osteen","raw_affiliation_strings":["DEVCOM Army Research Laboratory (ARL),Adelphi,MD,USA,20783"],"affiliations":[{"raw_affiliation_string":"DEVCOM Army Research Laboratory (ARL),Adelphi,MD,USA,20783","institution_ids":["https://openalex.org/I166416128","https://openalex.org/I2802705668"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053144325","display_name":"Srikanth Saripalli","orcid":"https://orcid.org/0000-0002-3906-7574"},"institutions":[{"id":"https://openalex.org/I91045830","display_name":"Texas A&M University","ror":"https://ror.org/01f5ytq51","country_code":"US","type":"education","lineage":["https://openalex.org/I91045830"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Srikanth Saripalli","raw_affiliation_strings":["Texas A&M University, TX, USA"],"affiliations":[{"raw_affiliation_string":"Texas A&M University, TX, USA","institution_ids":["https://openalex.org/I91045830"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100722002"],"corresponding_institution_ids":["https://openalex.org/I91045830"],"apc_list":null,"apc_paid":null,"fwci":24.8054,"has_fulltext":false,"cited_by_count":34,"citation_normalized_percentile":{"value":0.99148028,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9998999834060669,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9987999796867371,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9970999956130981,"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/computer-science","display_name":"Computer science","score":0.7665536403656006},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6766418218612671},{"id":"https://openalex.org/keywords/lidar","display_name":"Lidar","score":0.6348152756690979},{"id":"https://openalex.org/keywords/mutual-information","display_name":"Mutual information","score":0.510868489742279},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5070278644561768},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5069966316223145},{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.4685465097427368},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.46727076172828674},{"id":"https://openalex.org/keywords/calibration","display_name":"Calibration","score":0.45284759998321533},{"id":"https://openalex.org/keywords/camera-resectioning","display_name":"Camera resectioning","score":0.4107885956764221},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.38995277881622314},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.170970618724823},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14475217461585999}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7665536403656006},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6766418218612671},{"id":"https://openalex.org/C51399673","wikidata":"https://www.wikidata.org/wiki/Q504027","display_name":"Lidar","level":2,"score":0.6348152756690979},{"id":"https://openalex.org/C152139883","wikidata":"https://www.wikidata.org/wiki/Q252973","display_name":"Mutual information","level":2,"score":0.510868489742279},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5070278644561768},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5069966316223145},{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.4685465097427368},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.46727076172828674},{"id":"https://openalex.org/C165838908","wikidata":"https://www.wikidata.org/wiki/Q736777","display_name":"Calibration","level":2,"score":0.45284759998321533},{"id":"https://openalex.org/C110898773","wikidata":"https://www.wikidata.org/wiki/Q2933935","display_name":"Camera resectioning","level":2,"score":0.4107885956764221},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.38995277881622314},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.170970618724823},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14475217461585999},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/mfi52462.2021.9591203","is_oa":false,"landing_page_url":"https://doi.org/10.1109/mfi52462.2021.9591203","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.8399999737739563,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W603908379","https://openalex.org/W1531480177","https://openalex.org/W1829255258","https://openalex.org/W1985586071","https://openalex.org/W1991544872","https://openalex.org/W2111365302","https://openalex.org/W2133505209","https://openalex.org/W2154868725","https://openalex.org/W2161219841","https://openalex.org/W2213854941","https://openalex.org/W2295149141","https://openalex.org/W2609717538","https://openalex.org/W2770841999","https://openalex.org/W2799406003","https://openalex.org/W2803832867","https://openalex.org/W2887280559","https://openalex.org/W2908599206","https://openalex.org/W2948284172","https://openalex.org/W2962867954","https://openalex.org/W2963270286","https://openalex.org/W2964162504","https://openalex.org/W2966201455","https://openalex.org/W2967926749","https://openalex.org/W2970475117","https://openalex.org/W2991471181","https://openalex.org/W2995932445","https://openalex.org/W3002391935","https://openalex.org/W3009131764","https://openalex.org/W3010636877","https://openalex.org/W3024538535","https://openalex.org/W3035617611","https://openalex.org/W3088256830","https://openalex.org/W3089673743","https://openalex.org/W3091523271","https://openalex.org/W3101587859","https://openalex.org/W3109808990","https://openalex.org/W3114329284","https://openalex.org/W3120321204","https://openalex.org/W3131556920","https://openalex.org/W3133630616","https://openalex.org/W3156265036","https://openalex.org/W3206164009","https://openalex.org/W3206676377","https://openalex.org/W4295719664","https://openalex.org/W6618372016","https://openalex.org/W6680028861","https://openalex.org/W6688512011","https://openalex.org/W6736864032","https://openalex.org/W6745935785","https://openalex.org/W6752051073","https://openalex.org/W6774168932","https://openalex.org/W6776912505"],"related_works":["https://openalex.org/W4319317934","https://openalex.org/W2901265155","https://openalex.org/W2956374172","https://openalex.org/W4319837668","https://openalex.org/W4308071650","https://openalex.org/W3188333020","https://openalex.org/W1964041166","https://openalex.org/W4390887692","https://openalex.org/W4210818033","https://openalex.org/W4221065211"],"abstract_inverted_index":{"This":[0],"paper":[1],"proposes":[2],"SemCal:":[3],"an":[4,129,134],"automatic,":[5],"tar-getless,":[6],"extrinsic":[7],"calibration":[8,73,92,162],"algorithm":[9,126],"for":[10],"a":[11,21,45,54,76,89,119],"LiDAR":[12,65],"and":[13,53,99,113,133],"camera":[14,61],"system":[15],"using":[16,44,94,118,140],"semantic":[17,32],"information.":[18],"We":[19,86,122],"leverage":[20],"neural":[22],"information":[23,29,33],"estimator":[24],"to":[25,58],"estimate":[26],"the":[27,50,71,108,116,152],"mutual":[28],"(MI)":[30],"of":[31,49,110],"extracted":[34],"from":[35,60],"each":[36],"sensor":[37],"measurement,":[38],"facilitating":[39],"semantic-level":[40],"data":[41],"association.":[42],"By":[43],"matrix":[46],"exponential":[47],"formulation":[48],"se(3)":[51],"transformation":[52],"kernel-based":[55],"sampling":[56],"method":[57,93,112],"sample":[59],"measurement":[62],"based":[63],"on":[64,128],"projected":[66],"points,":[67],"we":[68,106],"can":[69],"formulate":[70],"LiDAR-Camera":[72],"problem":[74],"as":[75,146,148],"novel":[77],"differentiable":[78],"objective":[79],"function":[80],"that":[81],"supports":[82],"gradient-based":[83],"optimization":[84],"methods.":[85],"also":[87,123],"introduce":[88],"semantic-based":[90],"initial":[91],"2D":[95],"MI-based":[96],"image":[97],"registration":[98],"Perspective-n-Point":[100],"(PnP)":[101],"solver.":[102],"To":[103],"evaluate":[104,124],"performance,":[105],"demonstrate":[107],"robustness":[109],"our":[111,125],"quantitatively":[114],"analyze":[115],"accuracy":[117],"synthetic":[120],"dataset.":[121],"qualitatively":[127],"urban":[130],"dataset":[131,136],"(KITTI360)":[132],"off-road":[135],"(RELLIS-3D)":[137],"benchmark":[138],"datasets":[139],"both":[141],"hand-annotated":[142],"ground":[143],"truth":[144],"labels":[145,149],"well":[147],"predicted":[150],"by":[151],"state-of-the-art":[153],"deep":[154],"learning":[155],"models,":[156],"showing":[157],"improvement":[158],"over":[159],"recent":[160],"comparable":[161],"approaches.":[163]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":13},{"year":2022,"cited_by_count":5}],"updated_date":"2026-03-10T16:38:18.471706","created_date":"2025-10-10T00:00:00"}
