{"id":"https://openalex.org/W2144540691","doi":"https://doi.org/10.1109/icra.2011.5979612","title":"Batch heterogeneous outlier rejection for feature-poor SLAM","display_name":"Batch heterogeneous outlier rejection for feature-poor SLAM","publication_year":2011,"publication_date":"2011-05-01","ids":{"openalex":"https://openalex.org/W2144540691","doi":"https://doi.org/10.1109/icra.2011.5979612","mag":"2144540691"},"language":"en","primary_location":{"id":"doi:10.1109/icra.2011.5979612","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2011.5979612","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Robotics and Automation","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/A5013811117","display_name":"Chi Hay Tong","orcid":null},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":true,"raw_author_name":"Chi Hay Tong","raw_affiliation_strings":["Institute for AeroSpace Studies, University of Toronto, Toronto, ONT, Canada","University of Toronto, Institute for Aerospace Studies, Ontario M3H 5T6, Canada"],"affiliations":[{"raw_affiliation_string":"Institute for AeroSpace Studies, University of Toronto, Toronto, ONT, Canada","institution_ids":["https://openalex.org/I185261750"]},{"raw_affiliation_string":"University of Toronto, Institute for Aerospace Studies, Ontario M3H 5T6, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5004788089","display_name":"Timothy D. Barfoot","orcid":"https://orcid.org/0000-0003-3899-631X"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Timothy D. Barfoot","raw_affiliation_strings":["Institute for AeroSpace Studies, University of Toronto, Toronto, ONT, Canada","University of Toronto, Institute for Aerospace Studies, Ontario M3H 5T6, Canada"],"affiliations":[{"raw_affiliation_string":"Institute for AeroSpace Studies, University of Toronto, Toronto, ONT, Canada","institution_ids":["https://openalex.org/I185261750"]},{"raw_affiliation_string":"University of Toronto, Institute for Aerospace Studies, Ontario M3H 5T6, Canada","institution_ids":["https://openalex.org/I185261750"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5013811117"],"corresponding_institution_ids":["https://openalex.org/I185261750"],"apc_list":null,"apc_paid":null,"fwci":3.4236,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.92364799,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9991000294685364,"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":0.9991000294685364,"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":0.9902999997138977,"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/T11606","display_name":"Infrastructure Maintenance and Monitoring","score":0.9854000210762024,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/ransac","display_name":"RANSAC","score":0.8669118881225586},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.7964024543762207},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.7603750228881836},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6991535425186157},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5545058250427246},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5383215546607971},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5256073474884033},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5143905282020569},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.5126954317092896},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5055367946624756},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.43539297580718994},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3383665680885315},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.21556130051612854},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.09262052178382874}],"concepts":[{"id":"https://openalex.org/C114744707","wikidata":"https://www.wikidata.org/wiki/Q218533","display_name":"RANSAC","level":3,"score":0.8669118881225586},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.7964024543762207},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.7603750228881836},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6991535425186157},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5545058250427246},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5383215546607971},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5256073474884033},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5143905282020569},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5126954317092896},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5055367946624756},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.43539297580718994},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3383665680885315},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.21556130051612854},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.09262052178382874},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icra.2011.5979612","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icra.2011.5979612","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 IEEE International Conference on Robotics and Automation","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"No poverty","id":"https://metadata.un.org/sdg/1","score":0.699999988079071}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1531532259","https://openalex.org/W1990357615","https://openalex.org/W2024908906","https://openalex.org/W2033686935","https://openalex.org/W2049981393","https://openalex.org/W2058009001","https://openalex.org/W2085261163","https://openalex.org/W2096020743","https://openalex.org/W2107402720","https://openalex.org/W2121013842","https://openalex.org/W2127578024","https://openalex.org/W2128873520","https://openalex.org/W2571050459","https://openalex.org/W3187867541","https://openalex.org/W4231248300"],"related_works":["https://openalex.org/W2769402452","https://openalex.org/W2091258128","https://openalex.org/W4385261474","https://openalex.org/W1983540692","https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W1598471830","https://openalex.org/W3107369729"],"abstract_inverted_index":{"In":[0],"this":[1,37,49],"paper,":[2],"the":[3,24,41,51],"problem":[4,11],"of":[5,26,69,121],"outliers":[6,74],"in":[7,56,99],"a":[8,44,57,67,76,100,105,118],"batch":[9,101],"alignment":[10,102],"(given":[12],"heterogeneous":[13,52],"measurements":[14,53],"and":[15,88,110],"sparse":[16],"features)":[17],"is":[18,31,115],"considered.":[19],"The":[20],"conventional":[21],"approach":[22],"from":[23],"field":[25],"computer":[27],"vision,":[28],"pairwise":[29],"RANSAC,":[30],"shown":[32],"to":[33],"be":[34],"inappropriate":[35],"for":[36,43,72,108],"scenario,":[38],"which":[39],"motivates":[40],"need":[42],"new":[45],"method.":[46],"To":[47],"address":[48],"problem,":[50],"are":[54,79,93],"compared":[55],"common":[58],"currency":[59],"using":[60],"their":[61],"respective":[62],"scaled":[63],"measurement":[64],"innovations.":[65],"Furthermore,":[66],"family":[68],"three":[70],"algorithms":[71],"classifying":[73],"given":[75],"hypothesis":[77],"model":[78],"presented,":[80],"each":[81],"having":[82],"its":[83],"own":[84],"balance":[85],"between":[86],"speed":[87],"accuracy.":[89],"These":[90],"classification":[91],"criteria":[92],"then":[94],"incorporated":[95],"through":[96,117],"iterative":[97],"reclassification":[98],"framework,":[103],"providing":[104],"robust":[106],"estimate":[107],"localization":[109],"mapping.":[111],"Lastly,":[112],"statistical":[113],"validation":[114],"obtained":[116],"large":[119],"set":[120],"simulated":[122],"trials.":[123]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":2},{"year":2019,"cited_by_count":3},{"year":2014,"cited_by_count":1},{"year":2012,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
