{"id":"https://openalex.org/W2738874319","doi":"https://doi.org/10.23919/mva.2017.7986826","title":"Field tests on flat ground of an intensity-difference based monocular visual odometry algorithm for planetary rovers","display_name":"Field tests on flat ground of an intensity-difference based monocular visual odometry algorithm for planetary rovers","publication_year":2017,"publication_date":"2017-05-01","ids":{"openalex":"https://openalex.org/W2738874319","doi":"https://doi.org/10.23919/mva.2017.7986826","mag":"2738874319"},"language":"en","primary_location":{"id":"doi:10.23919/mva.2017.7986826","is_oa":false,"landing_page_url":"https://doi.org/10.23919/mva.2017.7986826","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA)","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/A5109048428","display_name":"Geovanni Mart\u00ednez","orcid":null},"institutions":[{"id":"https://openalex.org/I31944674","display_name":"Universidad de Costa Rica","ror":"https://ror.org/02yzgww51","country_code":"CR","type":"education","lineage":["https://openalex.org/I31944674"]}],"countries":["CR"],"is_corresponding":true,"raw_author_name":"Geovanni Martinez","raw_affiliation_strings":["Image Processing and Computer Vision Research Laboratory (IPCV-LAB) Escuela de Ingenier\u00eda El\u00e9ctrica, Universidad de Costa Rica, San Jos\u00e9, Costa Rica"],"affiliations":[{"raw_affiliation_string":"Image Processing and Computer Vision Research Laboratory (IPCV-LAB) Escuela de Ingenier\u00eda El\u00e9ctrica, Universidad de Costa Rica, San Jos\u00e9, Costa Rica","institution_ids":["https://openalex.org/I31944674"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5109048428"],"corresponding_institution_ids":["https://openalex.org/I31944674"],"apc_list":null,"apc_paid":null,"fwci":1.0888,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.83439037,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":"31","issue":null,"first_page":"161","last_page":"164"},"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":0.9994999766349792,"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/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.9984999895095825,"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/visual-odometry","display_name":"Visual odometry","score":0.7499333620071411},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7219099998474121},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7101799845695496},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.6897839307785034},{"id":"https://openalex.org/keywords/odometry","display_name":"Odometry","score":0.6110357046127319},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.603282630443573},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.5962983965873718},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5556233525276184},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5542833805084229},{"id":"https://openalex.org/keywords/terrain","display_name":"Terrain","score":0.4380491077899933},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3625723719596863},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.35820332169532776},{"id":"https://openalex.org/keywords/geodesy","display_name":"Geodesy","score":0.3213597536087036},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.23180389404296875},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.22074148058891296},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.21041780710220337},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.20922943949699402},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.13827550411224365}],"concepts":[{"id":"https://openalex.org/C5799516","wikidata":"https://www.wikidata.org/wiki/Q4110915","display_name":"Visual odometry","level":3,"score":0.7499333620071411},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7219099998474121},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7101799845695496},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.6897839307785034},{"id":"https://openalex.org/C49441653","wikidata":"https://www.wikidata.org/wiki/Q2014717","display_name":"Odometry","level":4,"score":0.6110357046127319},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.603282630443573},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.5962983965873718},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5556233525276184},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5542833805084229},{"id":"https://openalex.org/C161840515","wikidata":"https://www.wikidata.org/wiki/Q186131","display_name":"Terrain","level":2,"score":0.4380491077899933},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3625723719596863},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.35820332169532776},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.3213597536087036},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.23180389404296875},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.22074148058891296},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.21041780710220337},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.20922943949699402},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.13827550411224365},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.23919/mva.2017.7986826","is_oa":false,"landing_page_url":"https://doi.org/10.23919/mva.2017.7986826","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA)","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":15,"referenced_works":["https://openalex.org/W18295417","https://openalex.org/W1612997784","https://openalex.org/W1639227073","https://openalex.org/W2015996585","https://openalex.org/W2039982410","https://openalex.org/W2069635875","https://openalex.org/W2097197771","https://openalex.org/W2110729215","https://openalex.org/W2124535811","https://openalex.org/W2125240024","https://openalex.org/W2166502824","https://openalex.org/W2167777630","https://openalex.org/W3103648783","https://openalex.org/W4239050505","https://openalex.org/W6600788238"],"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":{"In":[0],"this":[1],"contribution,":[2],"the":[3,32,37,57,61,85,105,114,119],"experimental":[4],"results":[5],"of":[6,36,60,64,118,140,142,152],"testing":[7],"a":[8,14,52,96],"monocular":[9,97],"visual":[10],"odometry":[11],"algorithm":[12,30],"in":[13,23],"real":[15],"rover":[16,38,106],"platform":[17],"over":[18,43],"flat":[19],"terrain":[20],"for":[21],"localization":[22],"outdoor":[24],"sunlit":[25],"conditions":[26],"are":[27,93],"presented.":[28],"The":[29,45,91],"computes":[31],"three-dimensional":[33],"(3D)":[34],"position":[35,138],"by":[39,50,95],"integrating":[40],"its":[41],"motion":[42,46],"time.":[44],"is":[47,56],"directly":[48],"estimated":[49],"maximizing":[51],"likelihood":[53],"function":[54],"that":[55,100],"natural":[58],"logarithm":[59],"conditional":[62],"probability":[63],"intensity":[65],"differences":[66],"measured":[67],"at":[68],"different":[69],"observation":[70],"points":[71],"between":[72],"consecutive":[73],"images.":[74],"It":[75],"does":[76],"not":[77],"requiere":[78],"as":[79],"an":[80,135,146],"intermediate":[81],"step":[82],"to":[83,108,113],"determine":[84],"optical":[86],"flow":[87],"or":[88],"establish":[89],"correspondences.":[90],"images":[92],"captured":[94],"video":[98],"camera":[99],"has":[101],"been":[102],"mounted":[103],"on":[104],"looking":[107],"one":[109],"side":[110],"tilted":[111],"downwards":[112],"planet's":[115],"surface.":[116],"Most":[117],"experiments":[120],"were":[121],"conducted":[122],"under":[123],"severe":[124],"global":[125],"illumination":[126],"changes.":[127],"Comparisons":[128],"with":[129,145],"ground":[130],"truth":[131],"data":[132],"have":[133],"shown":[134],"average":[136,147],"absolute":[137],"error":[139],"0.9%":[141],"distance":[143],"traveled":[144],"processing":[148],"time":[149],"per":[150],"image":[151],"0.06":[153],"seconds.":[154]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2018,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
