{"id":"https://openalex.org/W2736658807","doi":"https://doi.org/10.1109/ivs.2017.7995805","title":"Monocular Outlier Detection for Visual Odometry","display_name":"Monocular Outlier Detection for Visual Odometry","publication_year":2017,"publication_date":"2017-06-01","ids":{"openalex":"https://openalex.org/W2736658807","doi":"https://doi.org/10.1109/ivs.2017.7995805","mag":"2736658807"},"language":"en","primary_location":{"id":"doi:10.1109/ivs.2017.7995805","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2017.7995805","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Intelligent Vehicles Symposium (IV)","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/A5102277941","display_name":"Martin Buczko","orcid":null},"institutions":[{"id":"https://openalex.org/I31512782","display_name":"Technical University of Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]}],"countries":["DE"],"is_corresponding":true,"raw_author_name":"Martin Buczko","raw_affiliation_strings":["Control Methods & Robotics Lab, TU, Darmstadt, Germany"],"affiliations":[{"raw_affiliation_string":"Control Methods & Robotics Lab, TU, Darmstadt, Germany","institution_ids":["https://openalex.org/I31512782"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001777411","display_name":"Volker Willert","orcid":null},"institutions":[{"id":"https://openalex.org/I31512782","display_name":"Technical University of Darmstadt","ror":"https://ror.org/05n911h24","country_code":"DE","type":"education","lineage":["https://openalex.org/I31512782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Volker Willert","raw_affiliation_strings":["Control Methods & Robotics Lab, TU, Darmstadt, Germany"],"affiliations":[{"raw_affiliation_string":"Control Methods & Robotics Lab, TU, Darmstadt, Germany","institution_ids":["https://openalex.org/I31512782"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5102277941"],"corresponding_institution_ids":["https://openalex.org/I31512782"],"apc_list":null,"apc_paid":null,"fwci":1.0012,"has_fulltext":false,"cited_by_count":19,"citation_normalized_percentile":{"value":0.85074598,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"739","last_page":"745"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.9995999932289124,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9995999932289124,"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":0.9994999766349792,"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/T12549","display_name":"Image and Object Detection Techniques","score":0.9976000189781189,"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/visual-odometry","display_name":"Visual odometry","score":0.8060116767883301},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7793385982513428},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7419666051864624},{"id":"https://openalex.org/keywords/monocular","display_name":"Monocular","score":0.702995777130127},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6798117160797119},{"id":"https://openalex.org/keywords/odometry","display_name":"Odometry","score":0.5099691152572632},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.504833996295929},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.47236043214797974},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3226724863052368},{"id":"https://openalex.org/keywords/mobile-robot","display_name":"Mobile robot","score":0.18418917059898376},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.1671375036239624}],"concepts":[{"id":"https://openalex.org/C5799516","wikidata":"https://www.wikidata.org/wiki/Q4110915","display_name":"Visual odometry","level":3,"score":0.8060116767883301},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7793385982513428},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7419666051864624},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.702995777130127},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6798117160797119},{"id":"https://openalex.org/C49441653","wikidata":"https://www.wikidata.org/wiki/Q2014717","display_name":"Odometry","level":4,"score":0.5099691152572632},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.504833996295929},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.47236043214797974},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3226724863052368},{"id":"https://openalex.org/C19966478","wikidata":"https://www.wikidata.org/wiki/Q4810574","display_name":"Mobile robot","level":3,"score":0.18418917059898376},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.1671375036239624}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ivs.2017.7995805","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ivs.2017.7995805","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":22,"referenced_works":["https://openalex.org/W1522911029","https://openalex.org/W1829716368","https://openalex.org/W1966724323","https://openalex.org/W1974306404","https://openalex.org/W1999350500","https://openalex.org/W2012319351","https://openalex.org/W2031998160","https://openalex.org/W2040227412","https://openalex.org/W2069635875","https://openalex.org/W2085261163","https://openalex.org/W2123498684","https://openalex.org/W2142876261","https://openalex.org/W2147253850","https://openalex.org/W2150066425","https://openalex.org/W2155413166","https://openalex.org/W2293305166","https://openalex.org/W2505801897","https://openalex.org/W2565712281","https://openalex.org/W3003662786","https://openalex.org/W3192970765","https://openalex.org/W6682684860","https://openalex.org/W6799855136"],"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/W2499612753","https://openalex.org/W2303855011","https://openalex.org/W2312326526","https://openalex.org/W3105866016","https://openalex.org/W2412578866"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3,34,63,105,143],"propose":[4],"an":[5],"optimization":[6],"scheme":[7],"to":[8,54,92,164,193],"detect":[9],"outliers":[10],"in":[11,185],"a":[12,97,108,129,132,145,157,186],"visual":[13,188],"odometry":[14,189],"pipeline":[15,149,190],"that":[16,113],"is":[17,140],"purely":[18],"based":[19,203],"on":[20,96,136,204],"the":[21,43,48,55,58,65,68,71,75,79,83,87,101,115,118,123,137,151,165,169,176,195],"optical":[22,37,52],"flow":[23,38,53,72,84,111,154],"of":[24,47,67,70,78,100,103,117,175,197],"one":[25],"monocular":[26,146,178,198],"camera":[27,80,89,166],"without":[28],"requiring":[29],"information":[30],"about":[31],"depth.":[32],"First,":[33],"review":[35],"different":[36,44],"error":[39,50,60,112,120,134,139,155],"measures":[40],"and":[41,57,131,168],"uncover":[42],"sensitivity":[45],"changes":[46],"endpoint":[49],"for":[51,107],"directional":[56,110,153],"absolute":[59],"components.":[61],"Then,":[62],"analyse":[64],"dependency":[66],"direction":[69],"induced":[73,85,121],"by":[74,86,122],"translational":[76],"components":[77,91],"motion":[81,90,167],"assuming":[82],"rotational":[88],"be":[93],"known.":[94],"Based":[95],"reliable":[98],"estimate":[99],"focus":[102],"expansion,":[104],"solve":[106],"normalized":[109,152],"takes":[114],"influence":[116],"discretization":[119,138],"pixel":[124],"size":[125],"into":[126],"account.":[127],"Here,":[128],"circular":[130],"squared":[133],"bound":[135],"investigated.":[141],"Finally,":[142],"present":[144],"outlier":[147,179,201],"detection":[148,180,202],"including":[150],"as":[156],"suitable":[158],"constant":[159],"threshold":[160],"criterion":[161],"almost":[162],"invariant":[163],"scene":[170],"geometry.":[171],"Further":[172],"on,":[173],"evaluations":[174],"overall":[177],"method":[181],"called":[182],"FERO":[183],"included":[184],"stereo":[187],"are":[191],"given":[192],"compare":[194],"performance":[196],"against":[199],"stereoscopic":[200],"Kitti":[205],"benchmark.":[206]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":3},{"year":2018,"cited_by_count":4}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}