{"id":"https://openalex.org/W3201569612","doi":"https://doi.org/10.1109/iros47612.2022.9982173","title":"Scale-aware direct monocular odometry","display_name":"Scale-aware direct monocular odometry","publication_year":2022,"publication_date":"2022-10-23","ids":{"openalex":"https://openalex.org/W3201569612","doi":"https://doi.org/10.1109/iros47612.2022.9982173","mag":"3201569612"},"language":"en","primary_location":{"id":"doi:10.1109/iros47612.2022.9982173","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros47612.2022.9982173","pdf_url":null,"source":{"id":"https://openalex.org/S4363607704","display_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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/A5110510828","display_name":"Carlos Campos","orcid":"https://orcid.org/0000-0001-7470-2935"},"institutions":[{"id":"https://openalex.org/I255234318","display_name":"Universidad de Zaragoza","ror":"https://ror.org/012a91z28","country_code":"ES","type":"education","lineage":["https://openalex.org/I255234318"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Carlos Campos","raw_affiliation_strings":["Instituto de Investigati&#x00F3;n en Ingenier&#x00ED;a de Arag&#x00F3;n (I3A), Universidad de Zaragoza,Spain"],"affiliations":[{"raw_affiliation_string":"Instituto de Investigati&#x00F3;n en Ingenier&#x00ED;a de Arag&#x00F3;n (I3A), Universidad de Zaragoza,Spain","institution_ids":["https://openalex.org/I255234318"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030733231","display_name":"Juan D. Tard\u00f3s","orcid":"https://orcid.org/0000-0002-4518-5876"},"institutions":[{"id":"https://openalex.org/I255234318","display_name":"Universidad de Zaragoza","ror":"https://ror.org/012a91z28","country_code":"ES","type":"education","lineage":["https://openalex.org/I255234318"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Juan D. Tard\u00f3s","raw_affiliation_strings":["Instituto de Investigati&#x00F3;n en Ingenier&#x00ED;a de Arag&#x00F3;n (I3A), Universidad de Zaragoza,Spain"],"affiliations":[{"raw_affiliation_string":"Instituto de Investigati&#x00F3;n en Ingenier&#x00ED;a de Arag&#x00F3;n (I3A), Universidad de Zaragoza,Spain","institution_ids":["https://openalex.org/I255234318"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5110510828"],"corresponding_institution_ids":["https://openalex.org/I255234318"],"apc_list":null,"apc_paid":null,"fwci":1.669,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.84464432,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1360","last_page":"1366"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":1.0,"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":1.0,"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":0.9997000098228455,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9970999956130981,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.8822118043899536},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7718695402145386},{"id":"https://openalex.org/keywords/visual-odometry","display_name":"Visual odometry","score":0.7409049272537231},{"id":"https://openalex.org/keywords/odometry","display_name":"Odometry","score":0.7063809633255005},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7043484449386597},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.6043843030929565},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5990760922431946},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4946534335613251},{"id":"https://openalex.org/keywords/simultaneous-localization-and-mapping","display_name":"Simultaneous localization and mapping","score":0.44154462218284607},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.42535650730133057},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.27294921875},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.13181918859481812},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.06515631079673767}],"concepts":[{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.8822118043899536},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7718695402145386},{"id":"https://openalex.org/C5799516","wikidata":"https://www.wikidata.org/wiki/Q4110915","display_name":"Visual odometry","level":3,"score":0.7409049272537231},{"id":"https://openalex.org/C49441653","wikidata":"https://www.wikidata.org/wiki/Q2014717","display_name":"Odometry","level":4,"score":0.7063809633255005},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7043484449386597},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.6043843030929565},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5990760922431946},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4946534335613251},{"id":"https://openalex.org/C86369673","wikidata":"https://www.wikidata.org/wiki/Q1203659","display_name":"Simultaneous localization and mapping","level":4,"score":0.44154462218284607},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.42535650730133057},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.27294921875},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.13181918859481812},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.06515631079673767},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iros47612.2022.9982173","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iros47612.2022.9982173","pdf_url":null,"source":{"id":"https://openalex.org/S4363607704","display_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)","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":31,"referenced_works":["https://openalex.org/W169439271","https://openalex.org/W1539091696","https://openalex.org/W1612997784","https://openalex.org/W2021851106","https://openalex.org/W2035379092","https://openalex.org/W2115579991","https://openalex.org/W2118428504","https://openalex.org/W2171740948","https://openalex.org/W2474281075","https://openalex.org/W2520707372","https://openalex.org/W2535547924","https://openalex.org/W2606794968","https://openalex.org/W2830339951","https://openalex.org/W2902093375","https://openalex.org/W2928601293","https://openalex.org/W2951234442","https://openalex.org/W2973258311","https://openalex.org/W2985775862","https://openalex.org/W3035056458","https://openalex.org/W3043971245","https://openalex.org/W3091687063","https://openalex.org/W3102327032","https://openalex.org/W3103648783","https://openalex.org/W3104290757","https://openalex.org/W3165610079","https://openalex.org/W4226191818","https://openalex.org/W4236769309","https://openalex.org/W4289145348","https://openalex.org/W6685261749","https://openalex.org/W6756279856","https://openalex.org/W6811234694"],"related_works":["https://openalex.org/W2979950214","https://openalex.org/W87609089","https://openalex.org/W3024737167","https://openalex.org/W2414561716","https://openalex.org/W3161199934","https://openalex.org/W2303855011","https://openalex.org/W2312326526","https://openalex.org/W3105866016","https://openalex.org/W2412578866","https://openalex.org/W4312703710"],"abstract_inverted_index":{"We":[0,111],"present":[1],"a":[2,15,33,52,71,76,92],"generic":[3],"framework":[4],"for":[5,91,142],"scale-aware":[6,77],"direct":[7],"monocular":[8,78,143,155],"odometry":[9,125],"based":[10],"on":[11,122],"depth":[12,25,35,44,61,108],"prediction":[13,36,109],"from":[14],"deep":[16],"neural":[17,94,131],"network.":[18],"In":[19,46],"contrast":[20],"with":[21,101,136],"previous":[22],"methods":[23],"where":[24],"information":[26],"is":[27,172],"only":[28],"partially":[29],"exploited,":[30],"we":[31,48],"formulate":[32],"novel":[34],"residual":[37],"which":[38,57,80,171],"allows":[39],"us":[40],"to":[41,50,75,98,159,174],"incorporate":[42],"multi-view":[43],"information.":[45],"addition,":[47],"propose":[49],"use":[51],"truncated":[53],"robust":[54],"cost":[55],"function":[56],"prevents":[58],"considering":[59],"inconsistent":[60],"estimations.":[62],"The":[63],"photometric":[64],"and":[65,115,133,139,144,167],"depth-prediction":[66],"measurements":[67],"are":[68],"integrated":[69],"into":[70],"tightly-coupled":[72],"optimization":[73],"leading":[74],"system":[79],"does":[81,88],"not":[82,89],"accumulate":[83],"scale":[84],"drift.":[85],"Our":[86],"proposal":[87,119,151],"particularize":[90],"concrete":[93],"network,":[95],"being":[96,157],"able":[97],"work":[99],"along":[100],"the":[102,106,113,123,140],"vast":[103],"majority":[104],"of":[105,117,176],"existing":[107],"solutions.":[110],"demonstrate":[112],"validity":[114],"generality":[116],"our":[118,150],"evaluating":[120],"it":[121,135],"KITTI":[124],"dataset,":[126],"using":[127],"two":[128],"publicly":[129],"available":[130],"networks":[132],"comparing":[134],"similar":[137,165],"approaches":[138,166],"state-of-the-art":[141],"stereo":[145,177],"SLAM.":[146],"Experiments":[147],"show":[148],"that":[149,175],"largely":[152],"outperforms":[153],"classic":[154],"SLAM,":[156],"5":[158],"9":[160],"times":[161],"more":[162],"precise,":[163],"beating":[164],"having":[168],"an":[169],"accuracy":[170],"closer":[173],"systems.":[178]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
