{"id":"https://openalex.org/W4416677441","doi":"https://doi.org/10.1109/sbr/wre66973.2025.11249639","title":"Analysis of Rolling Shutter Correction Techniques for Visual SLAM","display_name":"Analysis of Rolling Shutter Correction Techniques for Visual SLAM","publication_year":2025,"publication_date":"2025-10-13","ids":{"openalex":"https://openalex.org/W4416677441","doi":"https://doi.org/10.1109/sbr/wre66973.2025.11249639"},"language":null,"primary_location":{"id":"doi:10.1109/sbr/wre66973.2025.11249639","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sbr/wre66973.2025.11249639","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Brazilian Symposium on Robotics (SBR) and 2025 Workshop on Robotics in Education (WRE)","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/A5120519258","display_name":"Gabriel Pontarolo","orcid":"https://orcid.org/0009-0001-6416-4333"},"institutions":[{"id":"https://openalex.org/I52418104","display_name":"Universidade Federal do Paran\u00e1","ror":"https://ror.org/05syd6y78","country_code":"BR","type":"education","lineage":["https://openalex.org/I52418104"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Gabriel Pontarolo","raw_affiliation_strings":["Federal University of Parana,VRI,Department of Informatics,Curitiba,Brazil"],"raw_orcid":"https://orcid.org/0009-0001-6416-4333","affiliations":[{"raw_affiliation_string":"Federal University of Parana,VRI,Department of Informatics,Curitiba,Brazil","institution_ids":["https://openalex.org/I52418104"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072829468","display_name":"Felipe Gustavo Bombardelli","orcid":"https://orcid.org/0009-0004-5762-0849"},"institutions":[{"id":"https://openalex.org/I52418104","display_name":"Universidade Federal do Paran\u00e1","ror":"https://ror.org/05syd6y78","country_code":"BR","type":"education","lineage":["https://openalex.org/I52418104"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Felipe Bombardelli","raw_affiliation_strings":["Federal University of Parana,VRI,Department of Informatics,Curitiba,Brazil"],"raw_orcid":"https://orcid.org/0009-0004-5762-0849","affiliations":[{"raw_affiliation_string":"Federal University of Parana,VRI,Department of Informatics,Curitiba,Brazil","institution_ids":["https://openalex.org/I52418104"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5042177620","display_name":"Eduardo Todt","orcid":"https://orcid.org/0000-0001-6045-1274"},"institutions":[{"id":"https://openalex.org/I52418104","display_name":"Universidade Federal do Paran\u00e1","ror":"https://ror.org/05syd6y78","country_code":"BR","type":"education","lineage":["https://openalex.org/I52418104"]}],"countries":["BR"],"is_corresponding":false,"raw_author_name":"Eduardo Todt","raw_affiliation_strings":["Federal University of Parana,VRI,Department of Informatics,Curitiba,Brazil"],"raw_orcid":"https://orcid.org/0000-0001-6045-1274","affiliations":[{"raw_affiliation_string":"Federal University of Parana,VRI,Department of Informatics,Curitiba,Brazil","institution_ids":["https://openalex.org/I52418104"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.42032762,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"338","last_page":"342"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9751999974250793,"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":0.9751999974250793,"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":0.0032999999821186066,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.002899999963119626,"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/rolling-shutter","display_name":"Rolling shutter","score":0.9121999740600586},{"id":"https://openalex.org/keywords/shutter","display_name":"Shutter","score":0.8058000206947327},{"id":"https://openalex.org/keywords/visual-odometry","display_name":"Visual odometry","score":0.5968999862670898},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5044000148773193},{"id":"https://openalex.org/keywords/distortion","display_name":"Distortion (music)","score":0.49559998512268066},{"id":"https://openalex.org/keywords/scope","display_name":"Scope (computer science)","score":0.41690000891685486},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.3449999988079071},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3441999852657318}],"concepts":[{"id":"https://openalex.org/C2776166537","wikidata":"https://www.wikidata.org/wiki/Q2164193","display_name":"Rolling shutter","level":3,"score":0.9121999740600586},{"id":"https://openalex.org/C2776871301","wikidata":"https://www.wikidata.org/wiki/Q691823","display_name":"Shutter","level":2,"score":0.8058000206947327},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7694000005722046},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7342000007629395},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6748999953269958},{"id":"https://openalex.org/C5799516","wikidata":"https://www.wikidata.org/wiki/Q4110915","display_name":"Visual odometry","level":3,"score":0.5968999862670898},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5044000148773193},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.49559998512268066},{"id":"https://openalex.org/C2778012447","wikidata":"https://www.wikidata.org/wiki/Q1034415","display_name":"Scope (computer science)","level":2,"score":0.41690000891685486},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.3449999988079071},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3441999852657318},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.3231000006198883},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.3174999952316284},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3154999911785126},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.30469998717308044},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.28859999775886536},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.2775999903678894},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.2761000096797943},{"id":"https://openalex.org/C86369673","wikidata":"https://www.wikidata.org/wiki/Q1203659","display_name":"Simultaneous localization and mapping","level":4,"score":0.2721000015735626},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.2662999927997589},{"id":"https://openalex.org/C121684516","wikidata":"https://www.wikidata.org/wiki/Q7600677","display_name":"Computer graphics (images)","level":1,"score":0.2572999894618988}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sbr/wre66973.2025.11249639","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sbr/wre66973.2025.11249639","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 Brazilian Symposium on Robotics (SBR) and 2025 Workshop on Robotics in Education (WRE)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321091","display_name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","ror":"https://ror.org/00x0ma614"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1992213418","https://openalex.org/W2125281025","https://openalex.org/W2474281075","https://openalex.org/W2797929305","https://openalex.org/W2984771701","https://openalex.org/W3011907298","https://openalex.org/W3034748226","https://openalex.org/W3043971245","https://openalex.org/W3169826042","https://openalex.org/W3191254673","https://openalex.org/W4281642191","https://openalex.org/W4293731354","https://openalex.org/W4312340030","https://openalex.org/W4386065696","https://openalex.org/W4402753413","https://openalex.org/W4406137746"],"related_works":[],"abstract_inverted_index":{"Visual":[0],"SLAM":[1],"methods":[2,123],"have":[3,57,67,88],"become":[4,58],"increasingly":[5],"more":[6],"popular":[7],"in":[8,164],"the":[9,41,45,62,97,113,135,139],"latest":[10],"years,":[11],"largely":[12],"due":[13],"to":[14,17,36,75,90,145,151],"their":[15,34,52],"ability":[16],"achieve":[18,91,146],"high":[19],"accuracy":[20],"while":[21],"primarily":[22],"relying":[23],"on":[24,85,104],"passive":[25],"camera":[26],"sensors.":[27],"However,":[28],"many":[29],"of":[30,99,107,166],"those":[31,83,152],"algorithms":[32,142],"restrict":[33],"scope":[35],"Global":[37,154],"Shutter":[38,47,79,155],"cameras,":[39],"as":[40],"distortion":[42],"caused":[43],"by":[44,138],"Rolling":[46,78],"readout":[48],"can":[49,172],"significantly":[50],"degrade":[51],"performance.":[53],"Still,":[54],"CMOS":[55],"cameras":[56],"well":[59],"established":[60],"within":[61],"consumer":[63],"market":[64],"since":[65],"they":[66],"lower":[68,71],"cost":[69],"and":[70,130],"energy":[72],"consumption":[73],"compared":[74],"CCD.":[76],"Recently,":[77],"correction":[80,122],"methods,":[81],"notably":[82],"based":[84,121],"deep":[86,119],"learning,":[87],"started":[89],"remarkable":[92],"accuracy.":[93],"This":[94],"work":[95],"analyzes":[96],"performance":[98],"a":[100,147],"visual":[101,178],"odometry":[102],"solution":[103],"multiple":[105],"sequences":[106,136],"rolling":[108],"shutter":[109],"corrected":[110,137],"images":[111],"from":[112,153],"TUM":[114],"RS-VIO":[115],"dataset.":[116],"Three":[117],"state-of-the-art":[118],"learning":[120],"were":[124],"selected":[125],"for":[126,162,176],"analysis:":[127],"2F-DFRSC,":[128],"JAMNet":[129],"SUNet.":[131],"Results":[132],"indicate":[133],"that":[134],"first":[140],"two":[141],"are":[143],"able":[144],"trajectory":[148],"error":[149],"comparable":[150],"sequence.":[156],"Nevertheless,":[157],"there":[158],"is":[159],"still":[160],"room":[161],"optimization":[163],"terms":[165],"inference":[167],"time":[168],"before":[169],"these":[170],"solutions":[171],"be":[173],"effectively":[174],"used":[175],"real-time":[177],"SLAM.":[179]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-11-25T00:00:00"}